MIT Assistant Professor Thomas Rose, an expert in ancient metallurgy, passed away on Sept. 2 due to injuries sustained during a bicycle accident in Cambridge, Massachusetts. The incident, currently under investigation, occurred at the intersection of Memorial Drive and Massachusetts Avenue. Rose was 37.
Rose, who was MIT’s POSCO Professor of Materials Science and a member of MIT’s Center for Materials Research in Archaeology (CMRAE), joined MIT in January of this year and was still putting the finishing touches on his laboratory. But he had already endeared himself to colleagues and students by going the extra mile in mentorship, encouraging others to use his new equipment, and even using a portion of his lab startup funds on things the department needed.
“Everyone can look at his papers and his past and understand why he was such a good fit here technically,” Senior Lecturer Michael Tarkanian says. “But in the time he was here, it was even more impressive how likable, friendly, and open he was. He was everything you could have asked for as a colleague and a person. I thought, ‘What luck to be able to work with this person for the rest of my career.’ He was that good.”
Rose was born in Berlin, Germany. He discovered his life’s passion as a child, through a set of books about ancient Egypt.
“Thomas had a strong interest in archaeology already from a young age and participated in an excavation before he began his studies of archaeology,” Katrin Westner of the Deutsches Bergbau Museum Bochum and Professor Sabine Klein of the Ruhr University of Bochum wrote in a joint email tribute. “He was an incredibly inspired and enthusiastic researcher and was always bursting with new research ideas. We remember Thomas not only as a brilliant and dedicated researcher but also as a very close friend. We miss him deeply.”
Rose received his bachelor’s and master’s degrees from Goethe University Frankfurt and earned his PhD in archaeology through a joint doctoral program at Ben-Gurion University of the Negev in Israel and Sapienza University of Rome in Italy. Before coming to MIT, Rose held research and coordination roles in Germany at the Deutsches Bergbau Museum Bochum and Goethe University Frankfurt.
Rose’s research focused on ancient metallurgy and pyrotechnology that shaped early human societies, including how copper and its alloys were produced, transformed, and circulated.
The work integrated geochemistry, mineralogy, experimental archaeology, and materials science, making Rose an excellent fit in MIT’s tight-knit CMRAE group, which merges materials science with archaeology.
“The field of archaeometallurgy is unique,” explains Professor Polina Anikeeva, head of the Department of Materials Science and Engineering. “We had been looking for a faculty with the right skill set for at least 20 years. We needed someone who was world class in archaeology and materials science. We were looking for a unicorn, and we found him.”
Following the announcement of Rose’s hiring, a group from CMRAE traveled to a conference in Italy and heard from scholars based around the world about how lucky they were to have him.
“Thomas was an exceptionally talented and versatile scientist,” says University of Tuebingen Professor Silvia Amicone. “His ability to bring together archaeology, archaeometallurgy, geoscience, and materials science was remarkable. He was also committed to developing digital tools and promoting open, accessible, and reusable archaeological data. This combination of scientific rigor, methodological creativity, and engagement with broader archaeological questions made his work especially valuable. I was always impressed by Thomas’s brilliant intellect, collegial spirit, enthusiasm, and dedication to his work. Above all, he was a genuinely kind and good person.”
Rose had never taught before coming to MIT, but he was excited to begin his first courses this fall. His lab’s first batch of graduate researchers just arrived at MIT, but Rose had already begun mentoring students.
“He was the kindest person you could meet,” says Assistant Professor Tania Lopez-Silva, whose office was close to Rose’s. “He was always smiling. He really cared about his students, and he had a lot of momentum here. He was here first thing in the morning and late into the night.”
Several colleagues recalled the energy and enthusiasm he brought to work.
“He was so excited every day,” Anikeeva says. “Every day was a dream come true for Thomas. He was at the right place at the right time. He was so excited to collaborate and learn. He felt like he got his dream job, and everything he’d ever imagined was about to happen. It’s an unrealized vision.”
Tarkanian had recently restarted weekly meetings among researchers in CMRAE, which Rose attended consistently. Forging connections was a theme of Rose’s career.
“He had a long reach with both young and established scholars, and he inspired his friends and colleagues to show up,” says postdoc Benjamin Sabatini. “His work in archaeometry was paramount, and it showed in the people who gathered around him.”
Rose was also the co-founder of the Young Researchers in Archaeometry workshop, which brought together early-career researchers from around the world to present work and connect.
“Since [its founding], he accompanied every year’s workshop organizing meeting, always with immense kindness and support, making a lasting impact on each of us,” researchers Sinem Haciosmanoglu and Baptiste Solard wrote together in an email. “He was an exceptionally talented and dedicated researcher. Even at an early stage of his career, he brought new ideas and perspectives to the field. For many of us, he also played an important role in bringing together all fields of archaeological sciences, natural sciences, and cultural heritage.”
Outside of research, Rose was fond of rowing on the Charles River and was an avid member of MIT’s Archery Club. He loved manga Japanese comics and dancing. Lopez-Silva described Rose as humble and sometimes reserved, but on a recent recruitment outing with students, he fully committed himself to a very memorable karaoke performance.
“The students loved him,” Tarkanian says. “You could see that he cared about them, and they cared about him. He was going to be that kind of mentor.”
Fabrication platform could enable flexible, transparent next-generation photonic chipsThis scalable process produces high-performance chips for applications like discreet wearables or pliable augmented-reality displays.The field of silicon photonics, which uses light rather than electricity to transmit and process data on semiconductor chips, has enabled optical systems to evolve from bulky setups to compact and advanced systems. Typically, however, these silicon-photonics chips are rigid and opaque.
MIT scientists have now figured out a scalable way to make silicon-photonics chips flexible and transparent, opening a route to advanced microchips that could be used in applications such as discreet health monitors that conform to the body or transparent augmented-reality displays that fit the curve of a pilot’s helmet.
While scientists have recently performed lab demonstrations of chips that were flexible or transparent, they could only fabricate a few devices at a time.
The MIT researchers, in close collaboration with engineers at NY Creates at the Albany NanoTech Complex, created a fabrication process that uses standard semiconductor manufacturing techniques to generate flexible and transparent silicon-photonics chips on large-scale wafers.
To validate this platform, the researchers bent a single chip thousands of times around cylinders with various diameters — down to the width of a small screw — with no drop in performance. They also determined that looking through the chips would not cause much haze or distortion.
“We’ve now developed a wafer-scale process that produces wafers that are mechanically flexible and optically transparent, enabling novel applications that weren’t previously possible with silicon photonics. We hope that, by working closely with our colleagues at NY Creates and using the foundry at the Albany NanoTech Complex, there’s the potential for us to make the platform accessible to other groups within our research community and open these new application areas to the field of silicon photonics as a whole,” says Jelena Notaros, the Robert J. Shillman Career Development Associate Professor of Electrical Engineering and Computer Science (EECS) at MIT, a member of the Research Laboratory of Electronics, and senior author of a paper on this fabrication platform.
Her co-authors include lead author Tal Sneh and Andres Garcia Coleto, EECS graduate students; Thomas Dyer and Kevin Fealey of the New York Center for Research, Economic Advancement, Technology, Engineering, and Science (NY Creates); and Milica Notaros PhD ’23. The paper appears in the journal Optica.
Flexible and transparent
Over the past decade, researchers have developed techniques to fabricate precise and highly reliable silicon-photonics devices at scale.
They use advanced microelectronics foundry processes to produce 300-millimeter-diameter wafers with billions of nanoscale optical devices. But these methods yield silicon-photonics chips that are rigid and opaque.
“We realized that there are a lot of applications that would benefit from having a chip that is flexible and transparent,” Notaros says.
Scientists have previously made single silicon-photonics chips that were either transparent or flexible, but these techniques weren’t scalable. To address this scaling challenge, Notaros’ group recently demonstrated a foundry-scale process for making silicon-photonics chips on a flexible substrate.
Now, the team pushed these innovations even farther with a scalable process that produces 300-millimeter silicon-photonics wafers that are both transparent and flexible.
Their fabrication process begins as if they were making a traditional, rigid silicon wafer. The researchers carefully deposit and pattern tiny optical wires known as waveguides onto this rigid silicon substrate.
Then they bond a temporary silicon wafer on top. They flip the wafer over and remove all of the original silicon substrate from what is now the top of the wafer. They are then left with a flat layer of material with a thickness less than a tenth of a human hair.
“Thanks to the fact that we added that rigid temporary support before we flipped the wafer over, we can go all the way down so we are just left with the oxide and waveguiding layers,” Sneh says.
They use an adhesive to stick a thin, transparent polyester film on top of these ultrathin layers and “de-bond” the temporary silicon wafer from the bottom to remove it.
This leaves them with a flexible, transparent wafer only a few microns thick that contains the oxide and waveguide layers needed to capture and transport light for silicon photonics.
“Because we are using stable 300-millimeter foundry fabrication tools, we can design systems with a very large number of devices and feel confident that they are going to perform up to specifications, which is extremely important,” Sneh adds.
The biggest challenge in developing this fabrication process was removing enough material from a large 300-millimeter-diameter silicon wafer to leave only a few microns of material behind.
During fabrication, stress on the wafer typically causes it to bow slightly, making this silicon removal process especially challenging.
“As we were flipping the wafers over on these substrates, if the strain isn’t properly managed and the wafer isn’t perfectly flat, it is going to get ripples across its surface or even shatter in the fabrication line,” Dyer says.
The researchers carefully managed that stress by sticking to low temperature processes at or below 500 degrees Celsius.
They also had to find the right ordering and combination of removal methods.
They used industrial processes to thin the silicon layer, but switched to a more precise selective chemical etch for the last bit. This ensured they would not damage the ultrathin layers left behind.
An eye on performance
The researchers performed three experiments to test different functionalities of these flexible, transparent silicon-photonics wafers.
First, they tested the optical performance of chips with integrated waveguides of different lengths to determine their waveguiding properties.
Then they tested flexibility by bending a chip thousands of times around cylinders with different diameters. These experiments showed no degradation in performance even when they bent it around a cylinder about the size of a small screw. The device didn’t start to degrade until the researchers bent it around a toothpick several times.
“This experiment validated that the platform can be used for our proposed applications, performing even well beyond the metrics required for these intended systems,” Garcia Coleto says.
They also evaluated transparency by setting up a bionic eye and testing whether the chip would distort the user’s vision when placed in front of the eye. They found that the chip causes only minimal haze for the viewer and would not noticeably distort images the eye perceives when looking through it.
These characteristics could make these chips especially well-suited for enabling silicon-photonics systems for applications like curved augmented-reality displays that conform to a heads-up-display windshield or airplane pilot’s visor. In a pilot’s visor, for instance, such an augmented-reality display could replace the heavy bulk-optical systems that currently provide real-time information to help the pilot react to dangerous conditions.
In the future, the researchers want to add more complex components and functionality to the chips as they move toward enabling these and other new applications. They also want to refine the design to further improve waveguide efficiency and boost transparency performance.
This research was funded, in part, by the National Science Foundation, the U.S. Defense Advanced Research Projects Agency, and a MathWorks Fellowship. Wafer processing was performed at NY Creates, and chip dicing was conducted at MIT.nano.
New qubit architecture enables faster, more accurate operationsThis advance could be a big step toward developing a scalable, practical quantum computer.Researchers from MIT have designed a new qubit architecture that enables qubits to interact with each other much more quickly while remaining very stable. This advance could someday help scientists build practical quantum computers that can run long, complex algorithms with high accuracy.
Qubits, which are the building blocks of a quantum computer, usually only store data and rely on other electronics to perform operations and communicate. But qubits are so fragile and error-prone that it is difficult for scientists to connect enough qubits before they lose their information and need to be reset.
The MIT team designed a dual-purpose qubit with two separate parts: one component that stores data and one component that interacts with other qubits and electronics. This design improves the reliability of the qubit and enables it to operate with a reduced error rate, so it can perform more computations in the same time span.
Their simulations indicate that this new qubit architecture could allow significantly faster and higher-fidelity operations than existing designs.
While this research is still in its early days, it holds the potential to help scientists build large-scale, useful quantum computers that can solve real problems which are too difficult for traditional supercomputers to handle.
“This work feels like a big step. It is a new architecture that shows how much these systems can be engineered. We have taken two ideas and put them together in a way that can help us accomplish this qubit codesign that we are looking for, creating a pretty rare combination of the things we need to do quantum error correction,” says Alec Yen, who earned his electrical engineering and computer science (EECS) PhD this spring and is co-author of a paper describing the new architecture.
He is joined on the paper by lead author Jeremy Kline, an EECS graduate student; Stanley Chen, an MIT undergraduate; and senior author Kevin O’Brien, an associate professor in EECS and principal investigator in the Research Laboratory of Electronics (RLE). The work appears in Physical Review Applied.
A dual-purpose qubit
Just like the bits in a classical computer, quantum bits store information. But unlike classical bits, quantum bits have very short lifespans and can break down quickly when scientists connect them to make a quantum computer.
This degradation, known as decoherence, introduces errors in computations that rapidly build up, derailing long calculations before they are complete.
“The goal for doing all this is to build a fault-tolerant quantum computer where you can correct these errors as they happen, so then you can do long computations and actually do useful things with a quantum computer,” O’Brien explains.
To make qubits more reliable, the MIT researchers developed a new design that includes two separate but connected components: one which stores data and one which interacts with every other part of the quantum circuit.
This interaction component is like an arm that reaches out to other parts of the system, so the researchers call their design the “arm qubit.”
“It is engineered for these two, dual purposes — accomplished together by the data mode and arm mode — and these two goals really matter when you try to do quantum error correction,” Yen says.
Essentially, their design combines two different types of qubits. To make the data mode, they use one popular qubit design which has been known to have a very long lifespan, or coherence.
The arm mode utilizes a different design that exhibits very strong interactions with other components such as a resonator, which is an electronic component that allows for readout of quantum computations. Readout is the process of measuring a quantum system’s state and translating it into a classical value.
The key to this new architecture is a special coupling unit the researchers previously developed, which they used to connect the data mode and the arm mode.
Stronger coupling
Normally, coupling the modes together could cause unwanted interactions between them that would build up as more qubits are linked to the system.
One way to avoid this mixing is to use a technique called nonlinear coupling, which occurs when two components are linked in such a way that changing the state of one causes the other to change in response. Nonlinear coupling is essential for running most quantum algorithms.
The special device the researchers used, known as a quarton coupler, enables very strong nonlinear coupling between the data mode and arm mode, which significantly reduces unwanted mixing. This coupling allows the qubit to perform operations faster before it decoheres.
“By dedicating the ‘arm’ component to coupling, we were able make a design that is scalable, robust to manufacturing errors, and still uses a quarton coupler to achieve strong nonlinear coupling,” Kline says.
When they tested the design in simulations, the arm qubit outperformed other superconducting qubit architectures by yielding state-of-the-art coherence time as well as faster operations and readout.
The speed and reliability of this new architecture may accelerate quantum error correction, which is an important step in making quantum computers practical.
From here, the researchers plan to work toward fabricating the arm qubit so they can further study its properties and capabilities and integrate it into real quantum systems.
“This work leaves me with a lot of suspense because our simulations are very promising. Next, we’ll need to see if we can make it, and determine whether we missed anything in the modeling or design. If we can fabricate this qubit, it could be a building block for future error-correcting quantum computers,” O’Brien says.
This work is funded, in part, by the Army Research Office, the Air Force Office of Scientific Research, a Doc Bedard Fellowship from the MIT Center for Quantum Engineering and the Laboratory for Physical Sciences.
Giving farmers a more sustainable way to protect cropsLed by Andee Wallace PhD ’20, Robigo uses cutting-edge biotechnology to engineer microbes to fight pests, reducing the need for harmful chemical pesticides.Each year, farmers around the world spend $80 billion on pesticides for their crops. Those pesticides impact not only harmful insects but also bees and beneficial bacteria in the soil. They can also run off into waterways and harm the environment. And, they are increasingly being linked to human diseases like Parkinson’s and cancer.
Amid growing awareness of those problems, pesticides made from living microbes are gaining popularity. Unfortunately, such microbial pesticides are often less effective, forcing farmers to choose between potential environmental damage and higher crop yields.
Now, Robigo is equipping naturally occurring microbes with more potent pest-fighting capabilities. The company, which was co-founded by Andee Wallace PhD ’20, uses technologies more commonly associated with medical applications, like RNA interference and CRISPR, to engineer self-replicating microbes that target plant pathogens more precisely than chemical pesticides and more effectively than other biologically based solutions.
“Chemical pesticides have been a cornerstone of agricultural production for the past 70 years, to the point that it’s nearly impossible to envision an agricultural system without them,” Wallace says. “But that’s the long-term vision we have: providing growers new tools to enable a food system that is in balance with the environment, and that is productive, resilient, and safe.”
In field trials across five states, the company has already shown its microbes offer comparable results to chemical pesticides. In one trial comparing Robigo’s product with another commercial microbial product last summer, Robigo’s system led to a 250 percent increase in crop yield.
“Many crops, like lettuce, are harvested by hand, and the grower told me if a disease reduces yield even by just 25 percent, it’s not economical for them to pay workers to harvest the field at all,” Wallace says. “Growers are just trying to produce enough food to feed everyone. That’s why they use pesticides in the first place. We’re trying to give them a better choice.”
Engineered biology for agriculture
Wallace did her PhD in the lab of Chris Voigt, MIT’s Daniel I.C. Wang Professor and the head of the Department of Biological Engineering. She joined the lab after working at Bolt Threads, a startup spun out of the Voigt lab that was designing a material for the fashion industry inspired by spider silk.
“I came into MIT knowing that I wanted to join Voigt’s lab,” Wallace says. “I was really enamored with biomaterials in general. There are so many examples of animals and organisms that make incredible materials that we humans can’t replicate.”
Wallace’s PhD focused on engineering microbes in an attempt to replicate intricate glass nanostructures produced by single-cell algae called diatoms.
Wallace enjoyed her startup experience and explored entrepreneurship throughout her time at MIT. But it wasn’t until after graduation that she reconnected with two MIT students, Jai Padmakumar PhD ’23 and Connor Sweeney ’21, and decided to start her own company.
The founders’ initial idea was to engineer microbes to deliver CRISPR to target and kill bacteria that are harmful to crops. They used a number of MIT resources to get the company off the ground, including the Venture Mentoring Service, MIT Sandbox, delta v, and the MIT $100K Entrepreneurship Competition. Sweeney was involved in the venture for about a year. Padmakumar left Robigo in 2022.
Today Robigo is addressing a problem of growing importance to the agriculture industry.
“Chemical pesticides are under incredible pressures: increasing scrutiny from consumers and regulators, and increasing pesticide resistance among pests, diseases, and weeds,” Wallace explains. “Over the past 40 years, only two new herbicide chemistry modes of action have been commercialized, so people are understandably worried. If we can’t develop new solutions, resistance is only going to grow and will leave growers without effective tools to protect their crops. I think biotechnology has the potential to solve that problem.”
Farmers hope so, too: In an attempt to address environmental and health concerns, they have increasingly turned to so-called biological pesticide solutions, which are mostly made from natural sources like plant extracts, microbe-derived natural products, and increasingly biotechnology solutions like peptides and RNA.
“They are safer and better for the environment, but currently they just don’t perform as well or as reliably as synthetic chemistry pesticides, so there’s a big distrust among growers,” Wallace says. “Growers are being asked to choose between high performance or safety and sustainability. Robigo is trying to solve that problem by giving them products that do both.”
Robigo’s ARGO biotechnology platform combines synthetic biology and proprietary computational design processes to engineer microbes that perform at a similar level to chemical pesticides, but with improved safety profiles for people and the planet. A key part of that approach is leveraging microbes’ self-replicating abilities to continuously produce and deliver bioactive molecules in the field over the course of the growing season.
The company has moved in recent years from delivering CRISPR to RNA-interference, or RNAi, which inhibits key functions in the pathogens they want to target.
Robigo also differs from other microbial pesticide companies in its approach. Wallace says other companies screen to discover new microbes with the properties they want, then cultivate those for sprays and other modes of applications. But these specialized microbes may not be able to thrive in, say, the microbiome of California farm soil where they’re needed. That means they may die off soon after being deployed. Robigo, conversely, focuses on equipping robust, industry-proven microbes with the ability to target specific pests and diseases.
“Our starting point is ‘What crops will this be used for? and ‘What diseases do we want to control?’” Wallace says. “To design safer products, we need to be direct in how we’re designing RNAi to target different diseases. Another layer of our technology is what we call RNAi stacking, where we combine multiple RNAi into a single microbe to broaden the spectrum of pathogens we can control with a single product.”
Lab to farm to table
Last year, Robigo ran field trials for its two lead products, with soybeans and lettuce across the U.S. Midwest and West. Working with third-party testing companies, they showed a single application of their microbes offered protection for crops over the entire growing season and matched the performance of the leading chemical pesticide at a fraction of the cost.
“That’s very unusual for biological products, and even many chemical products, so we’re really optimistic about engineered microbes being a new solution that disrupts the conventional chemical pesticide paradigm,” Wallace says.
Wallace says Robigo is expanding fourfold this year and plans to expand even faster next year with the help of major agrochemical companies interested in more sustainable solutions. The company is also partnering to expand to other crops as it helps farmers around the world.
“There are a lot of opportunities we’re excited about, and we’re working with a number of partners as we scale,” Wallace says. “Over the past nine months, we’ve systematically used our ARGO platform to tackle new opportunities, and we have a number of products in the pipeline we’re working to bring to growers around the world.”
Building foundations that lastAssistant Professor Iwnetim Abate creates space for ambitious research and sustainable growth for his graduate students.How do you build something that lasts? For MIT Assistant Professor Iwnetim "Tim" Abate, the answer is the same whether he’s reimagining how the materials beneath our feet can store energy and manufacture essential chemicals, or mentoring MIT’s future researchers: focus on the foundation.
Rocks provide an unexpected thread connecting Abate’s research and his approach to mentorship. His research brings together electrochemistry, materials science, and Earth sciences to explore how the materials that make up our planet can be harnessed to address some of society’s most pressing challenges in energy and sustainable manufacturing.
In one line of inquiry, his group uses Earth-abundant elements found in rocks, such as manganese and iron, to develop high-energy, low-cost, and more sustainable batteries. In another, they are exploring how the Earth’s subsurface itself could function as a chemical factory. By harnessing naturally reactive rocks, geothermal heat, and injected fluids, they seek to pioneer new ways of producing valuable fuels and chemicals underground, with lower external energy requirements and emissions than conventional industrial processes.
Although batteries and subsurface chemical manufacturing operate at vastly different scales, they share a common philosophy: understanding the intrinsic chemistry of Earth’s materials deeply enough to harness it for useful transformations.
While Abate's research spans a broad range of scientific disciplines, his approach to mentorship is guided by a simple principle: helping students lay the groundwork for their careers after graduate school. Rather than measuring success solely through publications or technical accomplishments, he strives to equip students with the scientific skills, resilience, curiosity, and perspective needed to navigate any path their career may take.
"I often think about mentorship through the image of a rock," Abate explains. "A structure built on rock can withstand storms and the test of time. In the same way, I believe the most important role of a mentor is not simply to help students complete a project or publish papers, but to help them build a strong foundation."
Abate puts this philosophy into practice through his investment in his students' growth as researchers, professionals, and individuals.
In celebration of his exemplary mentorship, Abate has been recognized through MIT's Committed to Caring initiative, a student-driven program that honors graduate mentors who foster supportive and inclusive research environments.
Building holistic relationships
Students often arrive at graduate school with different ambitions. Whether they hope to pursue academia, industry, entrepreneurship, or public service, Abate begins by learning about each person's long-term goals.
Each time a new student joins his group, he meets with them individually to discuss their aspirations and helps tailor aspects of their PhD experience accordingly. Students say these conversations continue throughout their time in the lab, with regular one-on-one meetings focused on both research progress and career development, homing in on their opportunities beyond MIT.
For students interested in entrepreneurship, Abate leverages his own network, introducing them to venture capital firms, philanthropic organizations, and collaborators working across academia and industry. He encourages his students to pursue internships, recognizing that experiences outside the university can strengthen both their research perspective and their future careers.
Students also emphasize his ability to connect them with the expertise they need to push research forward. Whether facilitating access to specialized instrumentation or identifying researchers with complementary knowledge, Abate actively builds the relationships that allow his students and their projects to thrive.
Despite leading a growing research group while balancing teaching responsibilities and launching a startup, nominators wrote that Abate "consistently [shows] up for his students."
He makes time for individual chats with students, subgroup discussions, and weekly lab meetings, all while actively seeking their perspectives on research challenges. "Tim is often curious [to hear] our point of view on research problems and actively looks for our feedback," reflected one nominator.
This openness creates a synergistic environment where students are encouraged to help shape the direction of the group's work.
Creating space for ambitious ideas
Innovation, Abate believes, depends on more than technical expertise.
"Students need to know that it is OK to pursue ideas that may not work, and that setbacks are part of discovery, rather than signs of failure," he says. "My goal is to create an environment where ambitious ideas are welcomed, careful thinking is valued, and students know they have someone who believes in them through both successes and disappointments."
Students say this philosophy is reflected in the way that Abate approaches advising. Rather than directing every decision, he encourages them to think independently, remaining available whenever guidance is needed. His vast professional network often becomes an extension of that mentorship, opening doors to partnerships and expertise that help students tackle increasingly ambitious research questions.
This commitment to building strong foundations extends beyond his own research group. Since graduate school, Abate has worked to expand access to STEM education through his nonprofit Sci-Fro, which supports educational outreach across Africa. He has also contributed to broader efforts to strengthen scientific infrastructure and research institutions across the continent.
For Abate, these efforts reflect the same philosophy that guides his mentorship: lasting scientific progress depends not only on individual discoveries, but also on investing in people, communities, and institutions that enable future generations of scientists to thrive.
Supporting the person behind the PhD
Abate regularly checks in during one-on-one meetings, asking how his students are doing and what support they need. He believes these conversations are an essential part of advising.
"Graduate school is one of the most formative periods of a person's life," he says. "While research is important, I don't think success should come at the expense of health, relationships, or personal growth."
He encourages students to build lives that remain meaningful beyond the laboratory, recognizing that the habits, friendships, and perspectives developed during graduate school often shape them just as much as their scientific accomplishments.
Through steady guidance, meaningful connections, and genuine care for each student's well-being, Abate demonstrates a passion for developing exceptional researchers.
"I hope they leave MIT with a strong foundation — both scientifically and personally — that enables them to navigate future challenges, lead with integrity, and build fulfilling lives wherever their careers take them."
From MIT to IBM, expediting AI and quantum deployment MIT affiliates engage with the MIT-IBM Computing Research Lab to bring rigorous theory to production systems.The experience of transitioning from research based in theory to focusing on real-world application can vary significantly for different researchers. However, for two former MIT graduate students and a former postdoc, all now at IBM, working with the MIT-IBM Computing Research Lab (formerly the MIT-IBM Watson AI Lab) during their formative years enabled them to not only close the gap between education and employment, but also to generate ideas promising to business impact.
Despite pursuing varied careers in quantum machine learning, reinforcement learning and artificial intelligence agents,and trustworthy and fair AI, respectively, Srinivasan Arunachalam, Zhang-Wei Hong PhD ’25, and Irene Ko PhD ’24 have consistently found ways to tackle problems defined by novelty and rigor, and translate them to systems with real constraints. Here, the MIT-IBM Computing Research Lab served as a conduit for research relationship building and the flow of their expertise to industry applications.
“Among all the industrial labs, I think MIT-IBM has way better academic collaboration policy and opportunity [than the others],” says Hong, an IBM research staff member with the MIT-IBM Computing Research Lab who began his PhD at MIT in 2020 in the Department of Electrical Engineering and Computer Science (EECS).
Hong has been captivated with reinforcement learning since discovering that DeepMind could play Atari and learn from raw screen pixels via feature engineering. During his graduate work with EECS Associate Professor Pulkit Agrawal, who is also a principal investigator with the lab, Hong sought to build on this: improving value function learning for reinforcement learning in video games, using “Montezuma’s Revenge” in Atari, in order to predict and optimize the policy performance of an agent. With the lab, Hong developed techniques to ground AI for more realistic applications and provide better reward feedback, which he applied to domains such as robotics, large language models (LLMs), and reinforcement learning for science.
“I’m very excited about curiosity-driven exploration,” says Hong of the MIT-IBM graduate work that helped propel him into his profession. This, he says, allows agents to be inquisitive about new data, like humans, and perform a variety of tasks — from generating test cases to stress-test LLMs to exploring new environments. Now, as a mentor for students of his own, Hong continues to pursue similar lines of open-ended reinforcement learning research, leading him to investigate test-time training for agents and foundation models, and develop infrastructure for IBM’s agentic framework for enterprise tasks like chart reading and tool calling for database queries. This includes evolutionary computing to drive better optimization for exploration and leveraging neuroscience to inform deployment time model improvement.
“If successful, I think that it would be a very useful system and framework for all of the practitioners in reinforcement learning, because it will be the first framework that enables a model to improve — self-evolve their model weights online at a deployment time,” says Hong.
Irene Ko’s research has also been value-driven, from a personal and professional standpoint. “I started to work [on trustworthy AI] with IBM researchers from day 1 in my PhD, because it was funded by MIT-IBM,” says Ko. This, she says, was particularly advantageous since her goals to develop frontier-safe, robust, accurate, and fair AI also align with that of MIT and IBM, closing the gap between development and real-world deployment. “That really strikes a balance between pure research and something that’s of industry standard or value.”
Further, her MIT-IBM collaboration through her advisor in EECS, Joseph F. and Nancy P. Keithley Professor Luca Daniel, and IBM Principal Research Scientist Pin-Yu Chen, helped define the direction and parameters of her work to maximize impact, first in neural networks and later with foundation models and LLMs. After graduating in 2024, Ko joined IBM Research to continue her work on trustworthy AI as a research scientist.
“The reason I chose to go into industry after my PhD, and IBM specifically, is that I found great joy in the collaboration during my PhD. That process, those five years, gave me very high rewards in personal fulfillment,” says Ko. “I wanted to continue the momentum.”
Her current project focuses on finding pain points in current trustworthy methods that are not widely deployed in AI inference platforms. Unlike using low-rank adapters, which add extra steps to monitor and modify model behavior, her work on vLLM Hook provides a way to access internal model signals, like hidden states or activations, for decoding LLMs. This vector acts on transformer modules to analyze safety scores, such as identifying the likelihood of prompt-injection and hallucination. Here, Ko has developed a lightweight vLLM inference engine plugin framework to program the model internals that could provide significant cost savings over other methods. “I’m very proud of this project because this is really, as far as we know, the first bridge between the deployment and development in trustworthy AI with the inference engines.”
While Srinivasan Arunachalam has always dabbled in quantum research, he constantly explores other areas of theory, seeking to find quantum insights and deep math in unexpected lines of inquiry and papers. “Right off the bat, you don’t see it. You think, maybe this is just a vanilla problem, and then once you start investigating it further, you find some really interesting math that comes out of it, which I think is pretty cool,” he says.
This drew Arunachalam to MIT as a postdoc in 2018 in the group of Professor Aram Harrow in the Department of Physics. With a learning theory-first perspective, Arunachalam looked for target algorithms, subroutines, and circuits where quantum speed-ups might be possible. Conversations with Isaac Chuang, the Julius A. Stratton Professor in Electrical Engineering and Physics and an MIT-IBM PI, led him to collaborate with the lab and IBM researcher Kristan Temme.
With a seamless transition to IBM, Arunachalam more closely involved himself with problems that are potentially implementable on a near-term quantum device, keeping in mind constraints like nearest-neighbor architecture, noise, and simpler observable measurements. During this time, Arunachalam focused on quantum machine learning and areas where quantum computing would be superior to classical computing, increasingly prioritizing provability grounded in theory to heuristics. That MIT-IBM connection helped turn theoretical questions into concrete research directions, shaping work that culminated in two prominent papers: one on Hamiltonian learning, which gave rigorous guarantees for learning the dynamics of quantum systems, and another on quantum kernels, which provided theoretical evidence that quantum feature spaces can offer advantages over classical kernels under widely believed hardness assumptions.
Arunachalam also continued to expand his knowledge base by pouring himself into different branches of computer science to uncover structure in problems others may have missed. “One thing which I’ve been a huge fan of is exposing connections between different fields.” This has allowed him to explore learning quantum states — from completely classically simulatable quantum objects to the extremely complicated quantum objects.
Although Hong, Arunachalam, and Ko navigate different domains, they share an instinct: to move ideas across the space between what is possible in principle and what is useful in practice. In their own way, each is applying knowledge gained from collaborations, like that of MIT-IBM Computing Research Lab, to develop “killer applications” — a real-world use case that proves the underlying research can matter beyond the lab.
System helps humans predict when self-driving cars will make mistakesA new method, called CW-Net, translates the reasoning process of an autonomous vehicle’s AI system into understandable concepts that explain its behavior.Self-driving cars are often controlled by deep learning models that sometimes fail in unexpected situations. For instance, the car might inexplicably brake and block the path of an oncoming emergency vehicle. A human driver or passenger may need to react rapidly to prevent a collision.
To help humans better anticipate a vehicle’s mistakes, researchers from MIT and autonomous vehicle technology company Motional developed a new method that provides clear explanations of the underlying model’s decisions.
Usually, the internal reasoning process of a deep learning model is opaque and difficult to understand. But the new method, called the Concept-Wrapper Network (CW-Net), translates that reasoning process into concepts that faithfully describe the autonomous vehicle’s decisions without altering its driving performance.
CW-Net explains the decisions of machine learning-based planners using understandable concepts, like “approaching stopped vehicle” or “close to cyclist.” These explanations can correct misconceptions drivers and passengers have about vehicle behavior and improve their situational awareness.
In road tests on a private track, CW-Net explanations helped safety drivers more accurately predict vehicle behavior; a larger simulation study with nonexpert users yielded similar results. These experiments show how CW-Net can provide important feedback for engineers as they troubleshoot in-vehicle artificial intelligence systems. In the longer term, this technique could boost the safety and transparency of autonomous vehicles, while building appropriate trust in drivers and passengers.
“This work shows how explanations are supportive to the human’s mental model and understanding of the behavior of a system, and how it could be used in engineering and development to improve the technology,” says Julie Shah, an MIT professor of aeronautics and astronautics, director of the Interactive Robotics Group in the Computer Science and Artificial Intelligence Laboratory (CSAIL), and co-senior author of the paper on CW-Net. “Unless we are building these technologies in a way that we can rely on and predict their behavior, then it is a shaky and unsafe foundation for their use.”
She is joined on the paper by lead author Eoin Kenny, a former MIT postdoc who is now a senior AI researcher at J.P. Morgan Chase; co-senior author Momchil Tomov, a staff research scientist at Motional; as well as Motional team members Akshay Dharmavaram, Sang Uk Lee, Tung Phan-Minh, Shreyas Rajesh, Yunqing Hu, and Laura Major, president and CEO of Motional. The research appears today in Nature.
Faithful explanations
Machine-learning-based planners act as the “brain” of a self-driving car. These powerful deep-learning architectures process data from the vehicle’s cameras and lidar sensors, generate a high-level summary of the vehicle’s environment, decide what the car should do next, and output a trajectory for it to follow.
The planners are usually black-box models, which means their internal decision-making process is so complex it is difficult to understand. This can leave scientists and safety drivers in the dark about why an autonomous vehicle made an unexpected decision, like phantom braking.
The researchers designed CW-Net to explain a vehicle’s decisions using understandable concepts, while ensuring those explanations accurately reflect the true reasons behind its behavior.
“Especially in high-stakes settings like self-driving cars, it’s important that the explanations are not potentially misleading. Because CW-Net is causally faithful in how it makes decisions, that provides certain guarantees around the explanations,” Kenny says.
CW-Net is a “concept classifier,” an AI algorithm that has been trained to predict the high-level concepts that exist within input data. The researchers plug the CW-Net module into the middle of an autonomous vehicle’s existing machine-learning planner architecture.
It translates the model’s internal reasoning process into understandable concepts, like “approaching stopped vehicle” or “close to cyclist.” Then it forces the final piece of the planning model architecture to use those concepts when it decides what the vehicle should do next. In this way, CW-Net ensures the concepts faithfully explain the vehicle’s actions.
At the same time, CW-Net uses the concepts it classified to generate clear explanations that are output along with the vehicle trajectory, in real-time.
“Instead of just wondering why the car stopped, having real-time data provides feedback that lets you test the system during deployment. You could also give that data to an engineer to potentially improve the system,” Kenny says.
The researchers trained CW-Net to predict concepts using a dataset of 130 million examples of scenes from self-driving cars, with multiple labeled concepts in each scene. Using such a large, labeled dataset enables it to identify concepts accurately in a wide range of settings.
They also designed CW-Net to mimic the driving decisions of machine-learning-based planners, so the module would not negatively impact vehicle performance.
In the end, CW-Net generates accurate, understandable explanations without altering the original deep learning model.
Improving situational awareness
To test CW-Net, the researchers deployed the module on a real autonomous driving test vehicle (a Motional robotaxi) on a private track with a safety driver. They found that CW-Net helped the safety driver better predict how the vehicle would behave in surprising situations.
For instance, the vehicle consistently stopped when it approached a cyclist, and the safety driver assumed it did so because it detected that cyclist. But CW-Net explanations revealed that the model wasn’t properly configured to detect the cyclist and chose a trajectory that would have caused a collision. Instead, it stopped because its emergency braking procedure kicked in when it got too close.
Armed with this information about the model’s mistake, the safety driver could reduce speed or engage manual driving mode sooner in similar situations. This could also help engineers fix the model to avoid this failure in the future.
In larger online simulation studies using real driving situations captured on the roads of Las Vegas, the researchers saw similar results. CW-Net explanations significantly improved participants’ abilities to predict how an autonomous vehicle will behave.
In the future, the researchers could extend CW-Net so the module can cover more concepts and explore different training and design techniques that could boost performance and improve interpretability.
“Our study shows how crucial interpretability can be to these high-stakes environments, and how it should be on the mind of people as they are making AI in the future, for self-driving cars or other safety-critical environments,” Kenny says.
New research shows a neutrino laser is impossibleDue to physical and fundamental limitations, an earlier proposal for producing laserlike beams of neutrinos cannot be achieved, scientists report.Neutrinos are the pervasive yet intangible particles that permeate the universe, streaming through whole planets, stars, and our bodies by the trillions each second. The elementary particles are often described as “ghostly” for their near-zero mass and their elusive nature, as they have very little interaction with normal matter.
Since their discovery in 1956, neutrinos have continued to surprise physicists with their unexpected properties and behaviors. For instance, the particles come in multiple “flavors” and can morph from one to the other like subatomic shape-shifters. Neutrinos may also be their own anti-particle, in a Jekyll-and-Hyde-like quantum duality. And their extremely weak interactions make them nearly impossible to detect.
Last year, scientists seemed to add to the particle’s mystique, with a concept for a neutrino laser. They proposed that a concentrated beam of neutrinos could be produced by cooling a cloud of radioactive atoms to nanokelvin temperatures, one-billionth the temperature of interstellar space. Slowed to a near-frozen crawl, the atoms would form a Bose-Einstein condensate and should act as one quantum, coherent whole, in a way that speeds up and amplifies their radioactive decay. The physicists assumed that neutrinos, being a natural byproduct of radioactive decay, should also be amplified, and that such a process should emit a laser-like beam of the ghostly particles.
But work by MIT physicists has now shown that the neutrino laser concept, and a similar proposal for gamma-rays, is impossible. In two companion papers appearing today in Physical Review Letters, Wolfgang Ketterle, the John D. MacArthur Professor of Physics at MIT, together with postdocs Hanzhen Lin and Yu-Kun Lu, presents a two-part analysis that demonstrates both concepts are physically and fundamentally not possible. More specifically, they have shown that the neutrino laser concept is flawed, due to “recoil” (as in, the kinetic energy created by the reaction), and due to a neutrino’s fundamental “fermionic” nature.
“These two papers are sort of punch one and punch two,” Ketterle says. “Each paper would have killed the proposal.”
MIT professor of physics Joe Formaggio, who put forth the neutrino laser proposal with Ben Jones, who at the time was associate professor of physics at the University of Texas at Arlington, sees the new results as a convincing and constructive challenge.
“When a new idea — such as the one we proposed — is shared, it is the duty of the community to scrutinize it. Such is the scientific process,” Formaggio says. “Indeed, it was great to see how our paper generated a lot of thinking outside of our original concept. We suspect that will continue.”
A quantum amplifier
The proposal for a neutrino laser was based on the idea of “superradiance” — a quantum, amplifying effect that had only been observed for photons.
One form of superradiance occurs when a cloud of atoms is cooled to near absolute zero, at which point an atom’s motion is determined not by thermal effects, but purely by quantum uncertainty. In this state of near standstill, which is known as a “Bose-Einstein condensate,” (BEC) the atoms move in sync, as a quantumly correlated whole.
If photons are pumped into the condensate as a laser beam, the atoms synchronize to scatter the photons back out, in the exact same direction. In contrast, a cloud of atoms at room temperature would simply scatter the photons in random directions, generating, at best, a soft glow. As photons scatter off atoms, the atoms should in turn “recoil,” as if they were physically pushed backward from the impact. In a BEC, because the atoms recoil in sync, the rate at which they scatter photons, in the same direction, grows exponentially. This amplifying effect results in a “superradiant” laser of photons, which scientists have observed.
In their proposal, Formaggio and Jones, who is now at the University of Manchester, suggested that the same superradiant effect could be possible for radioactive atoms, which naturally emit neutrinos as they decay. If a cloud of radioactive atoms were cooled to form a Bose-Einstein condensate, a similar amplifying effect should kick in and generate a concentrated beam of neutrinos as the atoms decay in sync. To illustrate their point, they outlined a scenario in which a cloud of radioactive rubidium atoms, once cooled into a BEC, would accelerate its radioactive decay, from a half-life of 86 days, to one minute.
No one has ever produced a BEC from radioactive atoms. But if it could be done, then the quantum state should, in theory, produce a neutrino laser.
Instant recoil
For Ketterle, the idea seemed too good to be true. Ketterle is the leading expert on Bose-Einstein condensates, which he co-discovered in 1995, and for which he shared the Nobel Prize in Physics in 2001. He and his group at MIT have revealed many surprising properties in Bose-Einstein condensates and other ultracold matter, where the energy of atoms is at their lowest.
“My experience has always been that the condensate can do marvelous things at low energy — superfluidity, vortices — and if you were to speak in a room filled with condensate, it would take one hour for you to hear my voice. That’s how slow the condensate is,” Ketterle says. “And I had always come to the conclusion that for anything violent, like nuclear reactions, the condensate would not do anything.”
Compared to visible photons, which have an energy of 1 electron volt, neutrinos are naturally emitted as atoms decay, with a million times more energy. When a neutrino blasts out from an atom, the emission should cause the atom in turn to recoil a million times more strongly than for visible photons.
“As long as the recoil atom stays in the condensate, it can make the condensate superradiant,” Ketterle says. “But when a neutrino is emitted at a million electronvolts, the atom recoils at velocities equivalent to Mach 10, faster than a fighter jet. This is so fast that the atom would almost instantly disappear.”
Even so, the neutrino laser proposal assumed that the escaped atom should leave a sort of quantum imprint in the condensate, which tells the condensate as a whole to emit future neutrinos in the same exact, laser-like direction.
But in the first of two new papers, Ketterle and his team show through a theoretical analysis that this is not the case. They considered a model that describes superradiance. This model determines the conditions that would lead to superradiance of photons. Ketterle applied the model to the case of radioactive atoms and neutrinos, taking into account the range of energies at which the particles are emitted, as well as the resulting recoil of the decaying atom and the dynamics of the condensate throughout.
These calculations showed that, in every scenario the team considered, superradiance was not possible. The atom simply recoiled too fast for any quantum imprint to build up. It was as if the condensate instantly loses the “memory” of the neutrino emitted, and therefore would continue emitting neutrinos as atoms normally would, without enhancement.
An anti-memory
In their second paper, the MIT researchers showed that in addition to being impossible due to a physical recoil effect, the concept of a neutrino laser is flawed due to the fundamental nature of neutrinos.
They found that even if a recoiling atom were to leave a quantum imprint in the condensate, the imprint would not be of what to emit next, but rather, what not to emit. In other words, the memory of the emitted neutrino would tell the condensate to emit the next neutrino in any other direction, preventing the buildup of a directional neutrino beam. The researchers showed that this opposing memory, or “anti-correlation,” is due to the fact that a neutrino is, fundamentally, a fermion.
Fermions and bosons are the two fundamental classes of particles that make up all the matter in the universe. Bosons are particles with whole-integer spins, such as photons. In contrast, fermions, such as electrons and neutrinos, have half-integer spins. Whether a particle has a whole or half integer spin determines how it interacts at a quantum level with other particles.
“In superradiance, it is about a memory effect, or quantum correlations in the condensate. And in that context, people had thought that whatever is emitted from the condensate, it doesn’t matter if it is a boson or a fermion,” Ketterle explains. “But we analyzed it, and if you describe it correctly for emitted fermions, you get an anti-memory, which makes the condensate not accelerate in a superradiant form. It rather has the memory to not do it.”
Ketterle, Formaggio, and Jones have met on numerous occasions to talk through the original neutrino laser proposal, and Ketterle’s challenge to it.
“I suspect that someday, someone will do the experiment,” Formaggio says. “Nature, as always, is the final arbiter of such things. And here I would be remiss to not point out that every prior prediction about neutrinos has been wrong. The one thing about neutrinos that never surprises physicists is that they never fail to surprise.”
In part, Ketterle agrees:
“Creative ideas and discussions among scientists are needed to uncover nature’s surprises,” he says. “But in the case of neutrino lasers, the surprise was too good to be true.”
This research is supported, in part, by the National Science Foundation, the Center for Ultracold Atoms, the Vannevar-Bush Faculty Fellowship, the Gordon and Betty Moore Foundation, and the U.S. Army Research Office.
Walter Torous named executive director of MIT Center for Real EstateThe senior lecturer, already director of the degree program, will now oversee all aspects of the center’s activities and operations.Walter Torous, senior lecturer in the MIT Department of Urban Studies and Planning (DUSP) and the MIT Sloan School of Management, and director of the Master of Science in Real Estate Development Program (MSRED), was recently named executive director of the MIT Center for Real Estate (CRE) — effective July 1, 2026.
In announcing Torous’ appointment, School of Architecture and Planning Dean Hashim Sarkis also said that Justin Steil, professor of law and urban planning, will represent CRE as faculty chair of the Academic Curriculum Council.
“Together, Walter and Justin will guide CRE’s academic and strategic direction as it continues to strengthen its role within our school and the Institute,” Sarkis said. “Their appointments reflect the center’s distinctive position at the intersection of finance, design, planning, technology, and public policy — and its long-standing commitment to understanding real estate not only as a market force, but also as a driver of urban transformation and social change.”
As executive director, Torous will lead the CRE’s teaching, consortium activities, fundraising, and major events, while continuing to direct the MSRED program. He will also oversee the center’s staff, budget, and strategic direction, and work closely with Steil on the continuing evolution of CRE’s academic programs and industry engagement.
His appointment as executive director follows the tenure of STL Champion Professor Siqi Zheng, who served as CRE faculty director from July 2020 to June 2026.
Before coming to MIT in 2013, Torous was a professor at the Anderson School of Management at the University of California at Los Angeles and founding director of its Ziman Center for Real Estate. In addition to those positions, he also has held faculty appointments at the University of Michigan and the London Business School.
“Since joining MIT, Walter has played an important role in the growth and development of the MSRED program, educating generations of students in real estate finance and mortgage securitization,” Sarkis says.
“Real estate, both commercial and residential, is undergoing a tremendous change in the U.S., as well as in Europe and Asia,” Torous says. “Demographic changes, as an aging population stays longer in their homes, are creating an imbalance in residential real estate markets. New technologies and work from home are buffeting commercial real estate. Retail is changing. We’re in a period of turmoil, and I view the center’s role as being primarily to educate the next generation of leaders, especially in technology and financial markets, which are becoming ever more important to the functioning of real estate assets and markets. That requires that we train our students to be very facile with technology, so that they’re not affected by the ebbs and flows of changes, can maintain a strong career trajectory, and be stewards of the real estate industry going forward.”
For this reason, he would like to see the MSRED curriculum expand beyond DUSP to add more content from architecture, civil and environmental engineering, the Media Lab, MIT Sloan, and other areas of the Institute.
Torous also wants to more fully engage the 1,200-plus alumni from the center’s 43 years educating graduate students.
“A lot of our alums have assumed important positions in the real estate industry around the world,” he says. “In terms of training the next generation of real estate leaders, there’s a lot that we can learn from the industry leaders we’ve already produced.”
An economist and expert in the financial aspects of real estate known for his empirical studies of derivatives, options, mortgages, and other debt instruments, Torous’ research interests include the reorganization of financially distressed firms and statistical issues in finance.
His recent research has focused on better understanding why homeowners default on their mortgages. He is also interested in the application of machine learning to investigate how the dynamics of the U.S. commercial office market changed with the Covid-19 pandemic, and the lessons developers can learn about the new office market landscape. This research reflects the growing importance of AI and large language models to every aspect of real estate decision-making. Because of this, the MSRED curriculum now includes a class on AI and real estate, and Torous and Steil plan to add other, similar offerings.
“It’s important going forward that we focus on all aspects of real estate,” he says. “I look forward to working with Justin to create a curriculum that goes across the Institute and that will prepare CRE students to be leaders in the field.”
Cognition and consciousness arise from analog computations, says new theoryThe brain's ability to generate quick, nimble volitional thought — and a unified awareness of thought and experience — arises from analog computations, MIT neuroscientists argue in a new review.A new theory, published in The Journal of Neuroscience by three scientists in The Picower Institute for Learning and Memory at MIT, offers an explanation of how the brain produces cognition and consciousness: It uses traveling waves of rhythmic neural activity to coordinate nimble neural networks with analog computations.
The metaphor that the brain operates with “circuits” is incomplete, says Picower Professor Earl K. Miller, the paper’s senior author. Indubitably, the brain’s physically connected circuits provide the infrastructure to store our memories and represent our ongoing needs and goals. But when we need to make improvised use of that knowledge in the rapid-fire, anything-goes sensory context the world constantly throws our way, we can’t just depend on the relatively slow chemical process of rewiring those circuit connections called “synapses,” he says.
Instead, the brain needs a control system that can coordinate millions of neurons to process information in a fraction of a second. Brain waves, long understood to be the synchronized rhythmic fluctuations of large groups of neurons, turn out to be performing that crucial service, Miller and his colleagues argue, citing years of experimental evidence from his lab and many others.
“Circuits and synapses are important and fundamental, that’s the start. But there is more going on,” says Miller, a member of MIT’s Department of Brain and Cognitive Sciences faculty. “The brain generates waves, and wave dynamics are a highly efficient way to coordinate and perform computation.”
While digital circuits make calculations one step at a time through sequential switches and gates, analog computation, which can be performed via the interference of waves, processes multiple calculations in parallel. That’s not only more efficient, but also locally focused traveling waves happen to be a ubiquitous feature of the brain, the scientists note.
“The brain exploits its own physics,” wrote Miller and co-authors Scott L. Brincat and Jefferson E. Roy, who are research scientists in Miller’s lab.
The new theory is important not only because it provides an explanation of cognition and consciousness, but also because it asserts the potential importance of considering waves in clinical treatment. Conveniently, waves can be manipulated non-invasively.
“Developing treatments based on brain wave dynamics is not just an opportunity, but also an obligation,” says Miller, whose lab is part of a collaboration studying brain waves in autism.
Building the analog argument
To make the case that the brain uses waves to coordinate neurons to produce cognition and consciousness, the scientists begin with the now well-established observation that many neurons don’t just do one job. Instead, they respond to multiple cues and contexts, essentially participating in multiple functional networks at once, a property called “mixed selectivity.” Miller and colleagues have argued for years that this gives the brain immense computational horsepower, but it also initially raised the question of how the brain organizes these multiple overlapping networks with such speed and flexibility to produce the nimble thought we all depend on.
After numerous studies, the answer that has emerged for Miller and many other neuroscientists is that brain waves organize neural ensembles to process information. Miller has shown that brain waves of different frequencies govern cognitive processes such as working memory and predictive coding. Relatively slow “alpha” and “beta” frequency waves, representing memories and goals, regulate faster frequency “gamma” waves, which represent and report incoming sensory information.
The new theory posits that these alpha/beta control waves emerge from the coordinated spiking of neurons in circuits (connected at junctions called “synapses”) that encode stored memories and goals.
“Synapses store representations, while wave dynamics help determine which representations are active at any given time,” the authors wrote.
In some of the Miller lab’s newer research, the team has found evidence that even as waves emerge from neural spiking, the waves can rapidly grow to directly influence and coordinate spiking via an electric field-mediated process called ephaptic coupling. Importantly, electric fields can exert this coordinating influence very rapidly.
Another essential component of the theory, which Miller’s lab has also shown experimentally, is that alpha/beta waves are capable of exerting their control spatially, by affecting local areas of the cortex, and temporally, by traveling along the cortex. Essentially, the beta waves act as mobile stencils that govern where and when gamma waves can process sensory information and which ensembles of neurons will participate. Taken together, this suggests that the brain engages in “spatiotemporal computing,” the authors write. And where the waves intersect, they can add and subtract, enabling analog computations.
Miller acknowledges that his lab’s next step should be to provide direct evidence that the analog computations are taking place.
“This is a theory. We aim to test it by looking for signatures of analog computation in brain wave patterns,” Miller says.
Connection to consciousness
The article asserts that consciousness “emerges when these dynamic wave patterns bring the cortex in an organized, globally integrated state, one that naturally links and influences widespread activity.”
Some of the most compelling evidence linking wave dynamics to consciousness comes from studies of general anesthesia that Miller has conducted with Picower Institute colleague Emery N. Brown, who is an Institute professor at MIT, an anesthesiologist at Massachusetts General Hospital, and a professor in Harvard Medical School. Their labs have shown that three different drugs, each with different molecular mechanisms of action, all similarly disrupt brain wave dynamics to produce unconsciousness.
“Consciousness depends less on specific receptors or cell types and more on the integrity of large-scale wave organization,” the authors write in the review.
In other words, much like cognition, consciousness depends on how the brain efficiently organizes itself with brain waves.
“Electric field dynamics offer a low-overhead substrate for organizing and coordinating information across cortical networks,” they conclude. “Given strong evolutionary pressure to maximize computation per unit energy, it would be surprising if evolution did not exploit such a built-in analog computing substrate.”
The Freedom Together Foundation, The Picower Institute for Learning and Memory, the U.S. Army Research Office, the U.S. Office of Naval Research, a MURI grant, the National Institutes of Health, and the Simons Center for the Social Brain supported the research.
Atlas of the brain’s striatum could guide researchers to new drug treatmentsA new study reveals insights into populations of neurons affected by Huntington’s disease, schizophrenia, addiction, and other disorders.A region of the brain called the striatum is critical for many cognitive and motor functions, including decision-making, control of movement, habit formation, and processing of reward. It also plays a role in addiction and is significantly affected by Huntington’s disease, schizophrenia, and other disorders.
In work that could help scientists devise new treatments for those diseases, MIT researchers have generated a new atlas of the neurons found within the striatum. Using single-cell RNA sequencing and other techniques, they were able to identify 31 subgroups of neurons based on which genes they express.
These groups include neurons that are involved in addiction, depression, and schizophrenia. The researchers also discovered why some neurons of the striatum are more vulnerable to Huntington’s disease. All of these results, the researchers say, could help scientists develop new drugs to combat these conditions.
“We see this as the foundation that will allow more studies in our Huntington’s disease and opioid use disorder projects. We needed a roadmap of what is there,” says Myriam Heiman, the Picower Professor of Neuroscience and director of MIT’s Picower Institute for Learning and Memory.
Heiman; Manolis Kellis, a professor of computer science in MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) and a member of the Broad Institute of MIT and Harvard; and Dana Gabuzda, a principal investigator at Dana-Farber Cancer Institute and a professor of neurology at Brigham and Women’s Hospital and Harvard Medical School, are the senior authors of the study, which appears today in Cell. MIT postdoc Raleigh Linville and MIT graduate student Benjamin James are the paper’s lead authors.
Mapping the striatum
The striatum, located deep within the brain, receives diverse inputs from the cortex, midbrain, hippocampus, and other regions, which it uses to coordinate planning, movement, and decision-making, as well as processing reward. In this study, the researchers focused on the most populous cell type in the striatum, a type of inhibitory neuron called the medium spiny neuron, which responds to dopamine.
Most of these medium spiny neurons belong to either the direct pathway, which helps to promote movement, or the indirect pathway, which suppresses unwanted movements. These pathways are distinguishable by what type of dopamine receptor they express — dopamine receptor 1 (D1) or dopamine receptor 2 (D2).
Beyond these two divisions, scientists knew that there were many subpopulations performing different roles, especially in the anatomically ventral (lower) regions of the striatum. However, it has been difficult to generate a consensus on how to classify these cells, in part because prior studies focused on specific subregions, meaning that overarching principles of striatal cellular organization were lacking.
To overcome that challenge, the researchers worked closely with brain banks in the United States and Canada to collect postmortem striatal samples representing diverse anatomical regions.
Then, they used three different techniques to analyze the samples, including single-cell RNA sequencing — a method that can measure RNA molecules within individual cells to reveal which genes are being expressed. Two additional techniques — multiplexed fluorescent in situ hybridization and spatial transcriptomics — allowed the researchers to identify spatial principles of organization within the tissue.
Using these techniques, the researchers were able to identify 31 different subpopulations of neurons, including nine types of medium spiny neurons. Among their medium spiny neuron types are two “outlier” populations that appear to play important roles in schizophrenia, substance use disorder, and depression.
One of those populations, known as D1 outliers, showed high expression of genes involved in addiction and substance use disorder, especially genes related to opioid response. Another population, called D2 outliers, showed high expression of genes that respond to antidepressants. And, both populations appeared to respond strongly to clozapine, an antipsychotic drug used to treat schizophrenia.
Clozapine is among the most effective antipsychotics available, but it’s not widely used in the United States because it can cause a fatal blood disorder in a small percentage of patients. Now that researchers know which cells the drug acts on, they may be able to design more targeted therapeutics to overcome psychosis, but without the harmful side effects, Heiman says.
Huntington’s vulnerability
Another key finding of the paper helps to shed light on why the dorsal (upper) part of the striatum is more vulnerable to Huntington’s disease. The disease is caused by an inherited version of the huntingtin gene that carries too many repetitive DNA segments, called CAG repeats.
The researchers found that dorsal populations of medium spiny neurons express higher levels of the genes MSH2 and MSH3, which play a role in increasing the number of CAG repeats found in the huntingtin gene. As more of those repeats accumulate, the mutated version of the huntingtin protein becomes more harmful to cells.
The researchers also found that a rare population of medium spiny neurons that forms island-like structures in the ventral striatum was more resistant to the accumulation of CAG repeats. Further study of this class of cells might help researchers learn how to induce other medium spiny neurons to become more resistant to the disease, Heiman says.
“Looking at the genes that these neurons express or don’t express might give us some clues as to how to make other medium spiny neurons resilient like them,” she says.
Insights into substance use disorders
The researchers also compared their findings from human tissue samples to samples from mice and found several differences, especially in the expression of genes related to drug response and substance use disorders. One such gene, which encodes the mu opioid receptor (OPRM1), is highly expressed in the human D1 outlier population, but not in the corresponding population of neurons in mice.
This means that standard mouse models may not fully capture the biology of opioid responses, and that engineering mice to express this receptor in a similar manner to humans could make those models significantly more accurate.
“Some of the diversity we’re seeing in the human ventral striatum is species-specific and has implications for modeling substance use disorder in rodents,” Heiman says. “Now that we understand better the species differences, we can use the rodent models for specific questions that apply for conserved genes, but we could also think about humanizing some models.”
The researchers hope that this map, built from tissue contributions by brain donors and their families, and assembled across disciplines and institutions, will provide an important starting point for researchers pursuing new treatments for some of the most difficult-to-treat brain disorders.
The research was funded, in part, by the National Institutes of Health, the G. Harold and Leila Y. Mathers Charitable Foundation, the Freedom Together Foundation, the Natalia Mental Health Foundation, the Biswas Family Foundation, and the Milken Institute.
Ila Kumar: Innovating with communities The PhD student works to give young people an active role in shaping digital technologies that can support their own well-being.Before Ila Kumar thinks about how to build technology, she asks a different question: What is the context that technology will operate in, and who needs to be involved in the design?
For Kumar, meaningful innovation doesn’t result from engineers or designers working in isolation. Instead, she believes the best innovations emerge when the people who stand to benefit from a technology help create it from the very beginning.
That philosophy has guided her research in the Lifelong Kindergarten group, where she works alongside young people who have experienced trauma during childhood, particularly those involved in the child welfare system, to reimagine how technology can support healing, connection, and independence.
“I really think that community-based design is the only way that we can make technology that accounts for communities’ needs, but also their barriers, their cultures, their concerns,” Kumar says. “It’s the only way that we can make really sustainable and positively impactful technology.”
Today, Kumar is preparing to enter the sixth and final year of her PhD. But when she first arrived at MIT in 2021, she envisioned staying only long enough to complete a master’s degree. However, Kumar quickly fell in love with her work and decided to stay at MIT and pursue her doctorate.
Before graduate school, Kumar grew up in Philadelphia, attended the University of Pennsylvania, and worked on several projects at the intersection of technology and mental health or psychology research.
Through those experiences, Kumar began to question whether the technology she was helping to develop was having the sustained impact she hoped for. “I had done a number of projects that were ‘tech for good,’” she says. “And I wasn’t seeing that what I was doing had a long-term impact.”
Rather than walking away from technology altogether, Kumar began to rethink how it was created. “If we design technology in community-based ways and really think about holistic well-being,” she says, “maybe we can actually create things that help people.”
That conviction eventually became the foundation of her doctoral research, and over the course of her PhD, Kumar has increasingly moved from simply listening to communities to building with them.
Public conversations about technology often present a choice: Embrace it or reject it. Kumar believes that it’s not that simple.
Kumar sees the way digital platforms have the potential to both harm young people’s mental health and development, and help young people process emotions, strengthen relationships, and practice healthy vulnerability — if those tools are designed thoughtfully and embedded in the systems where young people already receive care and support.
Much of her work explores exactly what that could look like.
One project Kumar worked on, in partnership with Stepping Forward LA and with the input of the young people who would use the app, replaces text-heavy communication with a visual collage system to help young people impacted by trauma and the child welfare system to express emotions that may be difficult to put into words, and to build a sense of connectedness with one another.
In an ongoing project, Kumar is collaborating with the Justice Resource Institute to design a mobile app that supports youth in playing an active role in their treatment-planning process and helps them work toward the goals they set outside of the therapy office. The group is working with clinicians and youth to design and evaluate the system.
“We are not sitting at MIT designing tools and just throwing them at people,” Kumar says. “We’re designing it together. We need to actually have the folks that are relevant to providing the care in the room.”
That idea became even clearer to Kumar through a 10-month technology leadership circle she co-facilitated with Foster America. The program brought together people with lived experience of foster care and technology experts to envision how digital technologies could fill gaps in care for young people in the child welfare system.
This project surfaced the importance of not just designing tools that center youths’ needs but also considering the ways in which social services need to be brought into the innovation process.
Those ideas have also led Kumar to explorations that involve one of technology’s newest frontiers: artificial intelligence. She began asking questions after she realized that young people who had experienced trauma had already been turning to AI to make critical life decisions, even as many caregivers were not aware of it.
As a result, Kumar has increasingly focused on supporting care providers in talking with young people about AI. She has led training workshops with organizations that serve young people impacted by trauma or involved in the child welfare system.
Kumar’s passion for advocating for young people extends far beyond the lab. She also volunteers as a court-appointed special advocate, working one-on-one with a young person in the child welfare system while pursuing her PhD.
The role has deepened both her understanding of the challenges young people face and her belief that lasting change depends on relationships.
Some of her most meaningful moments have come while working directly with young people. Last summer, she, alongside another graduate student in her lab, mentored two interns with foster care experience during a six-week program that blended technology, creativity, and personal growth.
“It felt like a real privilege,” Kumar says. “Even the six weeks was not enough.”
Those relationships have also inspired Kumar to address how community-based research is conducted at MIT.
Recognizing that many students interested in community-engaged work often feel isolated, she collaborated with the Priscilla King Gray Public Service Center to co-teach a course on community-driven innovation. She later established a biweekly community of practice connecting researchers across MIT and Harvard University who are navigating the benefits and challenges of conducting research alongside communities rather than simply studying them.
Outside of research, Kumar enjoys birdwatching, cooking with friends, and creating graphic illustrations — creative pursuits that, much like her research, reward patience, observation, and careful attention.
As technology becomes increasingly woven into young people’s lives, Kumar hopes innovation will move beyond the lab and into the communities it is meant to serve.
“The future of actually impactful technologies,” Kumar says, “is when researchers are making decisions with communities instead of for them.”
Translating economic growth into better livesGraduate student Lyonel Tanganco investigates how to improve public policy interventions and address challenges in nutrition, climate, and development.Solving complex social problems with multiple interrelated causes can involve juggling a variety of factors. Securing funding, designing the right programs, and sustaining the political will necessary to implement them demands a targeted approach.
Lyonel Tanganco, a graduate student in MIT’s Master in Data, Economics, and Design of Policy (DEDP) program, seeks to connect data, policy, and practice-based community interventions to improve living conditions and service delivery in middle-income countries. His studies have allowed him to work with innovative practitioners making real improvements in the world, he says.
“There’s innovation at work in middle-income countries,” says Tanganco, a native of the Philippines. “Seeing the attitudes to adopt and scale new policies and procedures to improve lives has been very interesting to me.”
Taking those innovative practices and investigating their adaptability and potential to scale is at the heart of Tanganco’s research and work. “How do we make growth broad-based and inclusive?” he asks.
The DEDP master’s program, jointly run by MIT’s Department of Economics and the Abdul Latif Jameel Poverty Action Lab (J-PAL), equips development professionals from across the globe with the practical skills and theoretical knowledge needed to tackle these and other kinds of challenges. J-PAL seeks to reduce poverty by ensuring that policy is informed by scientific evidence — conducting randomized impact evaluations; helping governments, nongovernmental organizations, donors, and the private sector apply the resulting evidence to their work; and training researchers, policymakers, practitioners, and donors to generate and use that evidence.
Designing a path to more effective policies and practices
Before arriving at MIT, Tanganco earned degrees in management science and economics, graduating at the top of his class from Ateneo de Manila University in the Philippines. He was previously the director of the Policy, Research, and Liaison Office in the Philippine Department of Finance. His work focused on helping develop the nation’s response to the Covid-19 outbreak, tax policy reform, and communications support for key policy initiatives.
“During my time in government, we sought to increase revenues for health care and increase outlays for health-care programs,” he says. “We were thinking about health care from the financing perspective.”
Tanganco’s efforts helped increase taxes on cigarettes, vaping, and alcohol products, which funded a sixfold increase in the health-care budget. Allocating more funding for health care, he says, may yield better outcomes.
Additionally, Tanganco supported reforms to increase taxation on top Filipino income earners while lowering taxes for others, which the government subsequently implemented. Later, he and some of his colleagues formed a “policy think-and-do tank” — Malusog at Matalinong Bata Coalition (Smart and Healthy Kids Coalition) — that collaborates closely with government agencies on large-scale social programs.
There, he played a key role in designing and advancing a conditional cash transfer program aimed at addressing malnutrition that now reaches more than 190,000 Filipino households. “The program gives families the equivalent of $12 per month under the condition that they bring their children for regular monthly checkups,” Tanganco says. “It increased health-seeking behavior eightfold.”
While he saw success in implementing these programs, Tanganco still found gaps in both knowledge and implementation he thought he could close by enrolling in a program like DEDP. “I wanted a graduate program that taught me what I couldn’t get from a professional career,” he says.
Expanding research into targeted areas
Tanganco describes living in a middle-income country as “living in two contradictory worlds at the same time.”
“I’ve seen gleaming metropolitan skylines alongside underserved communities; pockets of affluence surrounded by persistent poverty; world-class hospitals alongside children who still lack access to basic health care,” he says. “The through line in my work is figuring out how to help middle-income countries translate economic growth to better lives and better human outcomes.”
His DEDP studies have taken him to Indonesia this summer for work on a capstone project with economist Benjamin Olken, the TEPCO Professor of Economics and co-faculty director of J-PAL. The research, conducted in collaboration with Indonesian local governments, involves the design and rollout of a randomized evaluation of a tax intervention.
“So far, I’ve visited and conferred with several local Indonesian governments to assess tax administration issues,” he says. Investigating Indonesian governmental interventions may help improve service delivery and support. One of the ways Tanganco hopes to help Indonesians, Filipinos, and others is by developing tools to raise revenues in simple, effective, and fair ways, making it easier to improve constituent sentiment and service delivery.
Tanganco wants to help policymakers and others understand how politics and other factors influence areas like investments in nutrition and environment. His studies have sharpened his investigative approach in these critical areas.
In the Philippines, for example, one-in-four children is malnourished. “Children who lack proper nutrition before age 2 develop smaller brains, perform worse in school and work, and are far more likely to remain in poverty,” Tanganco reports. “Their potential is capped before they get the chance to use it.”
Middle-income countries also suffer disproportionately from climate-change-related impacts. “Typhoons and extreme heat severely disrupt learning and economic growth in the Philippines,” Tanganco says. “More than a tenth of school days are lost because of climate issues.”
Essentially, without improved policies and practices alongside a sustained effort to improve lives, “we’re losing extraordinary opportunities for human advancement to wasted potential,” Tanganco believes. “Experiences like that abound,” he says.
From the classroom to the next chapter
Tanganco values opportunities to range beyond his DEDP studies. He fondly remembers completing a doctoral-level course in environmental economics co-taught by Olken and Jacob Moscona, the 3M Career Development Assistant Professor of Economics. Its focus on research appealed to him. “I was glad to have time to think about the problems I’m trying to solve,” he says.
Tanganco also enjoyed exploring Greater Boston with his wife — a graduate student at Harvard University — and his fellow DEDP students. From restaurants to concerts with other music nerds, he appreciates the time they spent outside the classroom. “We discuss our hopes and our home countries’ challenges,” he enthuses. “I’m excited to see what folks will do after this.”
Tanganco is especially pleased with the Institute’s commitment to ensuring scholarship centers an interdisciplinary approach. He likens the MIT educational style to “Avatar: The Last Airbender’s” Uncle Iroh, who recommends drawing wisdom from a variety of elements to ensure wisdom doesn’t grow stale.
These and additional opportunities to step outside his previously defined areas of expertise left a lasting impact on him. “Everyone at MIT is open to collaboration,” he says. “There are a lot of thinkers and doers here, and you don’t have to work hard to convince other students to help you.”
As Tanganco continues his work, he encourages practitioners — doctors, nutritionists, and community health workers, for example — to partner with economists and other researchers to translate their expertise into quantifiable metrics policymakers can understand. “Develop an eye for impact,” he adds.
Enrolling in the DEDP program “has been game-changing,” Tanganco concludes. “The program provides a solid foundation for understanding the world and how to make a positive, measurable difference in the lives of other people, especially the least fortunate among us.”
Gulfstream IV makes its long-awaited return to Lincoln LaboratoryThe modified aircraft will support an ongoing US Air Force program to assess and enhance the survivability of air and space vehicles.After extensive modifications over the past seven years, the Gulfstream IV (G-IV) aircraft operated and maintained by MIT Lincoln Laboratory's Tactical Defense Systems Group and Flight Test Facility (FTF) recently flew home from Canada.
Transforming the standard business jet into a highly specialized research platform — which will support the U.S. Air Force's Air Vehicle Survivability Evaluation (AVSE) program for decades to come — represented the largest and most complex airborne test bed modernization in Lincoln Laboratory history. The Tactical Defense Systems Group, assisted by the FTF, coordinated the effort with the Toronto-based aerospace company Field Aviation.
"Our team made hundreds of trips to Canada and dedicated countless weekends to keep the project moving along," says David Culbertson, FTF manager. "Seeing the aircraft finally return to the laboratory invoked a sense of pride and satisfaction."
An airborne testing infrastructure
For more than 40 years, the Tactical Defense Systems Group has supported the AVSE program, leveraging airborne test beds to assess how U.S. aircraft and space assets fare against current and emerging threats. The group had been conducting airborne testing for the AVSE program with a modified Gulfstream II (G-II) since the early 1990s. In 2013, they began a series of studies to replace the G-II because parts availability issues were looming. These studies concluded that the G-IV was the best option, given its performance and capabilities, including its respectively higher altitude and longer range; long-term sustainability; and cost. The laboratory purchased the G-IV in 2015.
To avoid repeatedly reopening the costly Federal Aviation Administration (FAA) certification process over the planned operational lifetime of the G-IV (25 to 30 years), the group decided to complete all anticipated aircraft modifications at once, rather than in phases. Following a competitive bidding process, the laboratory selected Field Aviation to perform the modifications. Field Aviation had modified the G-II, in addition to other laboratory aircraft. In December 2018, FTF pilots flew the G-IV to Toronto, where it was expected to remain for approximately three to four years.
However, Covid-19 pandemic-related disruptions and contractor management shifts extended this timeline. To help bring the aircraft home, the laboratory stepped in to oversee aircraft modifications, maintenance, and reassembly. Laboratory engineers, mechanics, pilots, program managers, and legal teams worked together to secure Canadian work permits and maintain a continuous onsite presence. Senior aircraft mechanic Craig Rowe served as lead crew chief, traveling monthly with team members to Canada; for his efforts, he was recognized with a 2026 MIT Excellence Award for Outstanding Contributor.
A structural overhaul
To modify the aircraft, mechanics removed, tracked, and ultimately reinstalled more than 2,000 components. The revamped G-IV incorporated 12 major modifications that required sweeping structural changes.
For example, on the wings, mechanics installed four pylons for carrying external sensor pods weighing anywhere from 200 to more than 1,000 pounds. The wings had to be structurally fortified to withstand the added weight, stress, and aerodynamic loads that would be experienced during flight. They added a fifth sensor pylon, capable of holding up to 2,000 pounds and accommodating systems nearly 19 feet long, to the forward lower fuselage. Development of the pylons spanned nearly five years because of intensive reverse engineering, including purchasing and disassembling a wing from a scrapped G-IV to measure the internal structural components. Installation took almost two years because access to the inner wing structure was limited to small panels normally used for inspections.
Mechanics modified the roof and lower fuselage to create flat surfaces to allow rapid mounting of external antennas and sensor systems without repeated incursions into the aircraft's pressurized fuselage. They extended the aircraft's nose and tail with standardized sensor-mounting interfaces to enable rapid placement of sensors for both forward- and aft-facing test scenarios. The six-foot nose extension required completely gutting the cockpit so the internal structure could be reinforced to bear the weight of the mounting interface and test systems.
In the interior, the team installed 14 equipment racks; workstations for six onboard operators; fiber-optic, Ethernet, and coaxial cables; liquid- and air-cooling systems; and dedicated power-distribution infrastructure separated from the baseline aircraft for safety reasons.
The remodel also required developing a means to generate sufficient electrical power to operate the test systems in flight while meeting FAA fire-containment standards. The aircraft’s original auxiliary power unit (APU) — normally intended to assist only with engine startup — was far too small for the mission requirements and could not operate airborne. Field Aviation engineers designed an entirely new fireproof titanium enclosure to house a larger APU capable of producing nearly double the original electrical output up to the 45,000-foot G-IV altitude ceiling. The laboratory's Engineering Division ran simulations to validate that the APU inlet airflow would allow for maximum APU power output throughout the flight duration.
Steps toward mission qualification
After reassembling the G-IV, FTF mechanics conducted hundreds of operational checks to ensure every aircraft system disturbed during the modification worked properly and to validate aircraft safety and readiness to resume flight operations. The aircraft completed multiple post-modification flights without a single maintenance write-up.
"It's extremely rare for a heavily modified aircraft of this complexity to have no write-ups," says program manager Paul Mancini from the Tactical Defense Systems Group. "That's a testament to the quality of work of the FTF mechanics who put the airplane back together and the Field Aviation engineers who completed the modifications."
Since the G-IV returned home this spring, test pilots have been evaluating its airworthiness — i.e., in-flight safety and functionality. The Tactical Defense Systems Group expects approximately another 18 months to complete flight testing, mission systems modification, test systems installation, and FAA certification before the aircraft becomes fully mission-qualified to operationally support the AVSE program.
At MIT convocation, a warm welcome for the Class of 2030 The Institute is “so glad and so grateful” to have this year’s new undergraduates aboard, President Kornbluth said at the annual greeting ceremony.MIT President Sally Kornbluth formally welcomed the undergraduate Class of 2030 to campus on Sunday, noting that the Institute quickly “feels like home” to new students.
The annual event, officially called the President’s Convocation for First-Years and Families, is held at the Johnson Ice Rink on campus on the weekend most new undergraduates arrive on campus.
The Class of 2030 consists of more than 1,100 first-year undergraduates from all over the map, representing a broad variety of academic interests and backgrounds. Yet even for such a wide-ranging group, Kornbluth observed, “It is very, very common for new students to say that in coming to MIT, they have finally found their place. They have finally found their people. And it feels like home.”
Kornbluth’s remarks outlined some of the binding forces that connect students, through the shared culture of inquiry and discovery at MIT.
“I was struck right away by the wall-to-wall enthusiasm for fundamental science, what we like to think of as curiosity on a mission,” Kornbluth said. “Every day here, hundreds of people are pushing the boundaries of human knowledge.”
This month alone, she noted, “astronomers here just discovered an entirely new type of astrophysical object, a black hole star. … And then, two days later, an MIT research team discovered that a drug that blocks a certain enzyme can reduce the risk of developing lung cancer.”
Kornbluth added: “And that’s just a regular [occurrence] here. As you’ll see, the discoveries just keep on coming in everything, from climate science to computer science, nuclear science to neuroscience, from chemistry to quantum.”
Secondly, Kornbluth said, people in the MIT community are frequently motivated by a desire to have an impact through their work.
“We’re also driven to make a positive difference in the world,” she told the audience of more than 2,000, which frequently applauded at key junctures.
A third common feature of campus life, Kornbluth told the crowd, is the “spirit of entrepreneurship” on campus, generally defined as a propensity to take action.
“Now, I don’t mean that everybody has to start a company, though a lot of people do,” Kornbluth said. “But at MIT, when we talk about entrepreneurship, we also mean the broad spirit of, do something, try something, with your whole heart … and let the doing teach you how to make a difference.”
Kornbluth also made a series of remarks about AI, noting that MIT has “deep ties” to the development of the technology and that AI tools are expanding and accelerating work in many fields of research.
That said, she added, “As educators, it is our challenge to derive AI’s benefits and counteract its harms.” And she called a recent report MIT has issued about AI and education “a powerful reminder that MIT was founded to help human beings develop their own powers of discovery, problem-solving, and invention. That is still and will always be our essential work. It is the experience you all came here for.”
All told, Kornbluth said, “We’re so glad and so grateful that you chose to bring your talent, your energy, your curiosity, and your creativity to MIT. And we’re thrilled to be starting this new year with all of you.”
Kornbluth then introduced the audience to other campus administration leaders who were sitting onstage for her remarks: Provost Anantha Chandrakasan, Chancellor Melissa Nobles, and Vice Chancellor for Graduate and Undergraduate Education David L. Darmofal.
Attendees also heard remarks from two faculty members who are also alumni, per convocation tradition.
Anna Huang SM ’08, the Robert N. Noyce Career Development Professor in both the Music and Theater Arts program and the Department of Electrical Engineering and Computer Science, discussed her work as well as the student experience on campus.
Huang studies human-computer interactions and develops human-AI collaborations in music making, and urged the students to follow their interests — which, in Huang’s case, are quite broad. She spent years working at Google and is also a composer herself.
“You’re going to discover so much here at MIT,” Huang said. “I discover something new every day.”
She urged students to participate in campus activities and to pursue programs such as MISTI, the global experiences program at MIT that enables internships, study abroad, and more. Huang also emphasized that MIT is a collaborative, interdisciplinary place where students can thrive by working with others.
“MIT is a very, very supportive environment,” Huang added. “And we value the perspective and the combinations of unique interests you bring.”
Huang was followed at the podium by Desirée Plata PhD ’09, associate dean of engineering, School of Engineering Distinguished Climate and Energy Professor, and professor of civil and environmental engineering, who urged the students to cultivate an ethos of optimism about their studies and ability to improve the world.
Plata’s wide-ranging work applies chemical engineering to climate issues — for instance, as she noted, by working to replicate methane-capture processes observed in nature onto new technologies that could be located in mines. Deploying such techniques to reduce the presence of greenhouse gases could help slow the worldwide rise of temperatures.
“Modulating the warming rate of the planet is admittedly ambitious,” Plata said. “But it’s not impossible. At least not from a thermodynamic perspective. And that’s just the kind of problem we like to solve.”
Plata also encouraged students to cultivate a feeling of open-minded optimism about their own pursuits.
“When I walk onto MIT’s campus each morning, I take a deep breath. I feel that same sense of possibility that I felt the [first] time I set foot here,” Plata said. “A high privilege of my life is being able to engage some of the most talented minds of our time. To engage all of you. To help develop your respective paths. And enjoy the amplifying impact you’re going to go on and have in this world.”
After Plata spoke, Kornbluth, who is from a musical family and enjoys singing, joined the campus a capella group The Chorallaries onstage for a spirited rendition of the songs “Arise All Ye of MIT” and “Take Me Back to Tech.” And with that, students filed out of the rink, ready to explore their new home.
MIT Quantum Initiative launches postdoctoral fellowship programThe Institute welcomes its first cohort of QMIT Fellows this fall to advance interdisciplinary quantum research.The MIT Quantum Initiative (QMIT) has launched a new postdoctoral fellowship program to accelerate interdisciplinary quantum research and develop the next generation of scientific leaders working at the frontiers of quantum science and technology.
Supported by a grant from the Gordon and Betty Moore Foundation, the program reflects QMIT’s vision of expanding the boundaries of quantum science by encouraging researchers to connect quantum approaches with other disciplines and emerging applications.
As opportunities in quantum research expand, investing in outstanding early-career researchers has never been more important. These fellowships are designed to help cultivate the next generation of quantum leaders, providing the resources and collaborative environment needed to advance transformative research at MIT.
“Quantum science and technology is in a period of extraordinary opportunity, opening new pathways to solving problems across computation, materials, sensing, and communication. Programs like this help MIT attract outstanding researchers whose ideas will shape the future of the field,” says Anantha Chandrakasan, MIT provost and the Vannevar Bush Professor of Electrical Engineering and Computer Science.
Launched in December 2025 as an MIT strategic initiative, QMIT brings together researchers from across the Institute to accelerate quantum discovery and apply quantum advances to some of society’s most consequential scientific, technological, industrial, and national security challenges.
“Quantum science is becoming increasingly interdisciplinary,” says Danna Freedman, the Frederick George Keyes Professor of Chemistry and faculty director of QMIT. “Some of the most exciting breakthroughs will come from researchers who combine deep expertise in quantum with new perspectives from other fields. This fellowship is designed to create exactly those kinds of opportunities.”
The QMIT Fellowship is intentionally designed to foster an interdisciplinary research community. Eligible applicants are outstanding quantum researchers working in a range of fields across physics, chemistry and materials science, and fundamental aspects of biological and Earth sciences. The program specifically seeks researchers whose work combines deep expertise in quantum science with a willingness to explore new intellectual frontiers.
One example of the interdisciplinary vision behind the program is the possibility of applying quantum systems to better understand biological processes, bringing together expertise in atomic physics, quantum algorithms, and biology. The fellows will be embedded across the research areas that define QMIT, including quantum computing, quantum sensing and precision measurement, quantum materials, quantum simulation, and quantum networks. Their research may also explore emerging interdisciplinary approaches that combine artificial intelligence and quantum science.
Fellows supported through the program will join MIT’s extensive quantum ecosystem, working alongside researchers across the Institute, including those affiliated with the Research Laboratory of Electronics, MIT Lincoln Laboratory, the Department of Physics, the Department of Electrical Engineering and Computer Science, the MIT-Harvard Center for Ultracold Atoms, and numerous interdisciplinary research centers and laboratories.
Beyond supporting individual research projects, the fellowship program is intended to strengthen the broader quantum community at MIT by fostering collaboration, mentorship, and intellectual exchange across disciplines.
“Quantum research, in the next few years and across a wide range of domains, is going to make the impossible possible,” says Ian Waitz, MIT’s vice president for research and the head of QMIT. “The QMIT fellowship program is an investment in outstanding postdoctoral scholars who will help bring tremendous new quantum capabilities to unforeseen, creative, and transformative applications in science and technology.”
The inaugural QMIT Fellows will begin their appointments during the 2026 academic year. QMIT expects to open applications for a new cohort in fall 2026 as it continues building a community of researchers working across disciplines to advance the future of quantum science.
Study: Peptides can form well-defined structures in harsh, Venus-like conditionsNew research offers support for the possibility that complex biological molecules could exist in the highly acidic environment of Venus’s cloud layer.When exploring solar system bodies for signs of past or present life, scientists have mainly focused on planets that have (or had) a liquid surface similar to Earth’s. However, mounting evidence suggests that the ingredients for life may exist in a very different environment: the highly acidic clouds that blanket Venus.
Those clouds are made up of about 98 percent sulfuric acid, which scientists had believed to be too acidic for complex biological molecules to survive. But in a new study, MIT researchers have shown that short peptides can not only remain stable in these extremely acidic conditions, they can also fold into shapes that may allow them to have biological functions.
“If peptides find their way to that cloud layer of concentrated sulfuric acid, they will stay and be stably preserved in that cloud of droplets. And once these macromolecules have a defined three-dimensional structure, they can potentially have a function,” says Mei Hong, an MIT professor of chemistry and one of the senior authors of the new study.
The findings suggest that scientists should not rule out planets that don’t resemble Earth in their search for life, says Sara Seager, the Class of 1941 Professor of Planetary Sciences in the Department of Earth, Atmospheric and Planetary Sciences and a professor in the departments of Physics and of Aeronautics and Astronautics.
“We really don’t know the full extent of what planet archetypes are out there. We’re seeking exoplanets that might be a true Earth twin, but what if they’re all Venuses? Our findings definitely open up a whole range of possibilities,” says Seager, another senior author of the study. She will be joining the University of Toronto faculty in September.
Janusz Petkowski, a research assistant professor at Wroclaw University of Science and Technology, is also a senior author of the paper, which appears this week in the Proceedings of the National Academy of Sciences. Jia Yi Zhang, an MIT graduate student, is the paper’s lead author, and former MIT postdoc Aurelio Dregni is also an author.
Surviving harsh conditions
While Venus’s surface is too hot to be hospitable to life, its cloud layer, which extends from 30 to 40 miles above the planet’s surface, features milder temperatures suitable for life. The clouds are made from droplets of sulfuric acid, which can dissolve metals and destroys most biological molecules on Earth.
Meteorites that contain peptide building blocks regularly enter Venus’s atmosphere, raising the possibility that those peptides could serve as building blocks for simple life forms — if they could survive the clouds’ corrosive environment.
In 2020, Seager’s lab began a series of studies looking at whether different types of biological molecules could persist under those highly acidic conditions. In their initial experiments, working with MIT’s Department of Chemistry Instrumentation Facility (DCIF), they used nuclear magnetic resonance (NMR) spectroscopy — which measures the magnetic properties of atomic nuclei within molecules — to analyze the structures of a variety of molecules in a solution of nearly pure sulfuric acid.
Those studies showed that nucleic acids, the building blocks of DNA, could remain intact under highly acidic conditions, as could lipids and amino acids. The next step was to figure out if peptides — short strings of amino acids — could persist, and more importantly, whether they could then fold into shapes that might give them biological functions.
For that challenging task, researchers at DCIF suggested that Seager join forces with Hong, an NMR expert who has an advanced 800-megahertz solution NMR spectrometer in her lab.
To their surprise, the researchers found that the peptides they studied remained stable for many weeks. They believe this is a result of the lack of water in such highly acidic solutions. At 98 percent sulfuric acid, there are very few water molecules, which means that hydrolysis, the chemical reaction that breaks peptide bonds in acid, can’t happen.
“Without water, an acid that you would consider a harsh solvent suddenly is not as menacing as one might think,” Hong says.
After confirming that the peptides remained intact, the researchers began to explore their structures. One of the peptides that the researchers analyzed, a molecule known as HHQ, is a synthetic seven-amino-acid peptide that Hong had previously studied for its role in forming catalytic amyloid fibrils.
In water, this peptide forms flat beta sheets that eventually form long fibrils. However, in concentrated sulfuric acid, the researchers found that it takes on an entirely different shape — a loop shaped like the Greek letter omega. Such so-called omega loops are occasionally found in some naturally occurring proteins, where they form links between other structural motifs such as sheets or helices.
The other two peptides that the researchers analyzed were a longer variation of HHQ, called HHQ13, and a completely different peptide called K7, which contains seven amino acids. These peptides also formed omega loops in sulfuric acid.
The researchers believe that molecules of sulfuric acid act as a scaffold for the loops, sliding into the center of each loop and holding it in that shape.
“What hadn’t been known is that peptides can survive so well and have specific three-dimensional shapes in an acidic environment,” Hong says.
Structure and function
In naturally occurring proteins in aqueous solution, omega loops are thought to play a role in protein folding and molecular recognition. Whether they could have other biological functions is not known. However, the fact that peptides can form well-defined, folded structures in acidic environments is an important step in showing that peptides may be able to perform biological functions in such environments.
“Life needs to have specially shaped proteins so that they have a specific target they can latch onto and perform their function. Before this, people thought that peptides couldn’t survive in sulfuric acid, so showing peptides are not only stable, but also fold, is a really big deal,” says Seager, who is leading the Morning Star Missions to Venus.
Adriaan Bax, chief of the Section on Biophysical NMR at the Laboratory of Chemical Physics at the National Institute of Diabetes and Digestive and Kidney Diseases, described the results as “important and unexpected.”
“The observation that these peptides retain a substantial degree of conformational order in concentrated sulfuric acid raises the prospect that folded oligopeptide/protein structures can exist in such environments, potentially supporting the possibility of life in atmospheric conditions that are very different from Earth,” says Bax, who was not involved in the research.
Seager now hopes to pursue additional studies of a molecule called peptide nucleic acid (PNA) — an artificially synthesized molecule that is similar to DNA but with the sugar-phosphate backbone replaced by a peptide backbone. Her lab has previously shown that this molecule, which doesn’t naturally exist on Earth but could offer a potential alternative to DNA, is stable as a single strand in highly acidic environments. She now hopes to study the stability of double-stranded PNA.
The researchers also hope to analyze longer peptides to see if they also take on omega loop shapes, or other structures, in highly concentrated sulfuric acid.
The research was funded by the Alfred P. Sloan Foundation, the NOMIS Foundation, and the National Institutes of Health.
Playing against climate riskClimate scientist Sai Ravela is using games to help coastal communities find creative adaptations to climate change.Sai Ravela, principal research scientist in MIT’s Department of Earth, Atmospheric and Planetary Sciences (EAPS), works with a team of researchers, local partners, and community collaborators to develop game-based computer models to help local communities find solutions to their unique geographical and environmental challenges.
Ravela came to MIT as a postdoc in 2002. Prior to that, he had been working on robotics and computer vision, but he was excited by the idea of studying the climate system and wanted to work in the field of sustainability. “Suddenly, overnight, I became a climate person,” Ravela says.
His project, funded by a 2025 Abdul Latif Jameel Water and Food Systems Lab (J-WAFS) India Grant, explores how agricultural decision-making occurs under climate stress. Using localized climate projections and a participatory approach, the project aims to help communities discover ways to improve their collective agricultural resilience.
EAPS postdoc Anamitra Saha is a key contributor on the grant, working with Ravela and local collaborators to combine downscaled climate modeling, participatory decision-making, and community-based adaptation planning. Other team members include Myisha Ahmad (Carthago Consultancy), Jayanta Basu (University of Calcutta), Anusree Ghosh (Bangladesh Open University), Showmitra Sarkar (Khulna University of Engineering and Technology), and Bivuti Sikder (Dhaka University).
In a process known as downscaling, researchers take large-scale climate projections and turn them into highly detailed local projections. From these hazard maps, Ravela and Saha can estimate the risk of extreme weather phenomena such as flooding, drought, heat waves, and salinity-related stress.
“We kind of simulate what the outcome could be in that region,” Ravela explains. “Would it improve agricultural productivity? Would it reduce agricultural productivity? Would it change certain land use patterns? Would the land be less livable, more livable?”
The team combines surveys, scientific models, and local knowledge to build an impact graph that allows them to explore what might happen to a region during simulated weather events.
Although Ravela knew hazard maps could be useful, he was troubled by how rarely they reached the people whose lives were most affected by the risks they described. “We had clients like insurance companies,” he says. “But I never saw it reach people in a way that made a difference in their lives. And that really bothered me.”
To address this gap, he began thinking about how to help communities engage with hazard maps directly and take part in the decision-making process. In conversations that informed the game’s development, Ravela heard people whose livelihoods are vulnerable to climate events voice immediate concerns about what would happen if a future season failed: “If I don’t plant next season — if I can’t — what would I do?” Ravela wanted to help people think instead about possible choices, different paths, and their respective risks.
When he asked himself what circumstances allow someone to think about risk, the answer began to take shape. “Well, roll a die. Toss a coin,” he thought. “And where do you do these things? In a game.”
How it works
The process the collaborating team developed takes place in three stages. The first is a “snakes and ladders” game, played with physical game pieces and tokens. The second is a mixed game that still uses the gameboard, but a computer generates events and manages portfolios, allowing the system to calculate risk percentages. Once players become comfortable with the mixed game, the final stage, developed by Ravela, abandons the board game and moves fully into a more detailed computer simulation that can be played on a cellphone app.
“We tried this in different stages in three places,” says Ravela. Two villages, Bally Island and Joygopalpur, are in India's Sundarbans region. The third is a village in Bangladesh just across the border. In each location, the work depends on collaboration with local residents, community organizers, and regional partners who help shape the game around local land, water, livelihood, and governance conditions. During development, informal community-engagement sessions helped the team refine and adapt the game. Those interactions also led to intriguing observations that are now helping the team formulate hypotheses for future formal research.
The three villages lie in a coastal region that faces numerous extreme weather events threatening water availability and agricultural productivity. As riverbeds rise from sediment accumulation over time and the land sinks from groundwater extraction, saltwater can more easily intrude into groundwater aquifers, while freshwater drainage, recharge, and flushing become increasingly difficult, intensifying waterlogging and drought.
“There’s a vicious cycle that’s happening with salinization of the soil,” Ravela explains.
One visible result is that Boro rice leaves now often begin browning far too early in the season, as salinity and water stress damage crops before they can mature. This cycle occurs in many coastal communities, suggesting to Ravela that the outcomes of the J-WAFS project could have applications around the world.
That broader potential comes from what the game is able to reveal. Instead of treating potential interventions — such as embankments, canals, recharge, crops, fisheries, and energy — as separate choices, the simulation lets players see how each intervention affects the coupled system of land, water, salinity, and livelihoods. When players test different options, simply raising embankments often proves less effective than expected, because it does not break the underlying cycle that causes the land to flood.
More-integrated strategies — combining mangrove restoration, canal excavation, groundwater recharge, diversified agriculture and fisheries, better water management, and merging solar panels into farming with agrivoltaics or aquavoltaics — can generate better long-term returns while also making the landscape more resilient.
The game also creates space to consider dramatic alternatives to embankment-based protection, including seasonal migration, livelihood shifts, and other difficult choices. These possibilities can be explored safely inside the game, even when they would be almost unimaginable to raise in real life. In this way, difficult questions that might otherwise be avoided can be explored, rather than ignored. And if the game reveals that a difficult choice could lead to better long-term outcomes, that result is not a prescription, but a basis for informed conversation between the community, government, and other decision-makers.
Competition or cooperation?
To make the game effective at developing strategies, Ravela’s team had to understand how many people should play at one time. Too few players may not generate enough diversity of ideas, while too many can slow the process significantly. During game development, groups of roughly ten to twelve people seemed especially workable: large enough to support active interaction, but small enough for practical discussion and learning.
“Once it crosses a dozen people,” Ravela explains, “it becomes very, very viable as a way to solve problems.”
The games have sparked interest and generated new strategies. People are often excited by the prospect of playing, and repeated play reveals different kinds of expertise. Some participants become especially engaged strategy-explorers; others contribute through discussion, critique, memory, and local knowledge. Together, the process helps identify players who are especially adept at thinking across different dimensions of the problem.
Ravela emphasizes the social aspect of the games as central to their efficacy. “Even though the game is on a phone,” he says, “players are within each other’s reach.” An emcee or facilitator encourages players to engage with one another by asking them to explain their gameplay, discuss their reasoning, and learn from one another’s choices.
While competition is not an explicit feature of the game, there can be zero-sum outcomes. One household’s decision about land, water, drainage, or energy may improve its own outcome while making conditions worse for others. Initially, players may aim for individual success. As they explore longer simulated time horizons, they often shift toward cooperative strategies.
After each game, the research team and local facilitators lead an educational session where people can learn from each other’s strategies. At first, players often attempt to copy the previous winner’s gameplay — usually, making as much money as possible and saving it in case of disaster. But some disasters are too large for one person to handle alone.
“That strategy is only optimal up to a certain horizon,” Ravela explains, “because when everyone replicates that strategy, the community doesn’t necessarily thrive.”
As players recognize this, they begin to evolve collective modes of behavior, such as creating a common insurance pool where everyone contributes money to a disaster relief fund. Through multiple iterations of the game, players often appeared to converge on cooperative solutions.
“The community in this way, playing a game against nature, simulated nature, comes upon solutions that work for them,” says Ravela. “We would love to formally explore this in the future,” Ravela adds.
Why the game works
Ravela’s team sees three advantages to game-based decision-making. First, the game brings new perspectives to the table that formal decision-making often misses. Many communities have strong hierarchies that can discourage women or less powerful community members from participating openly. The game allows people to offer insight without necessarily violating cultural norms. One recurring impression was that women — often responsible for managing family affairs — diversified their portfolios earlier, while men more often concentrated on a single livelihood strategy. The observation was striking enough that the team hopes to test and quantify it formally in future studies.
Second, in the game, all players begin on a level playing field, regardless of status, gender, or wealth. “It democratizes the process,” explains Ravela. In the simulation, a wealthy, influential community figure has no intrinsic advantage over a seamstress. The game reduces natural biases by giving everyone’s ideas a chance to be tested under the same conditions.
Third, because the game is a simulation, people can explore choices that might be too risky, too expensive, or too socially difficult to consider in real life. People may not want to discuss a large aquifer management system, a new land-use arrangement, or a difficult livelihood transition if the real-world implications feel too overwhelming. But inside the game, they can test possibilities without immediate consequence. “So, what, you lose? You start again,” says Ravela.
This is where the game becomes more than a communication tool. It turns uncertainty into a shared decision space. Players can test interventions, observe trade-offs, compare outcomes, and discover strategies before real disasters force those choices upon them. The game shifts the conversation from avoiding risk to reasoning about it, and from fatalistic thinking to collective agency.
Ravela and his collaborators also see the games as a way to address roadblocks in policy implementation by allowing community members to own the solutions they discover. Traditionally, donors may give money to a nongovernmental organization (NGO) that has proposed a project, and the NGO then distributes resources in the community. But it is not always obvious what has actually been implemented, or whether the community has had meaningful ownership of the decision. “In seeking solutions to problems, often the difficulty is developing the policy that provides metrics for the effectiveness of those solutions,” Ravela says. “Games enable people to quickly see the policy space, rather than approaching problems only reactively.”
When people test policies in the game, see how they work, and revise them through repeated play and refinement, they can begin to propose those policies themselves. The result is not simply a technical recommendation from outside experts, but a community-informed basis for action.
What's next?
The broader project, developed with collaborators and community partners in India and Bangladesh, has attracted interest in Bangladesh and Thailand, where similar game-based coastal agricultural resilience projects are being explored. Some customization is necessary to adjust the game to local conditions, but the simulations are highly adaptable. Between 75 and 80 percent of the game can remain the same across locations, while the rest can be tuned to local geography, livelihoods, hazards, and governance structures. Although each place brings its own challenges, “the way land and water and people interact is very similar,” says Ravela.
Building on insights from these game-development and informal community-engagement sessions, Ravela hopes the project can eventually expand to other locations, including members of the Association of Southeast Asian Nations and some places in Latin America. But he emphasizes the importance of establishing longitudinal outcomes before scaling. “The critical question is, does it answer real problems?” he says.
Future formal research will test these emerging hypotheses prospectively and longitudinally. The resulting evidence will help determine whether, where, and how to scale the approach.
If computationally assisted decision-making proves useful over time, the impact could spread far beyond the initial development locations. But the work is not only about finding an optimal solution. It is also about helping people work with one another. As Ravela puts it, “the process really is about helping the people work with each other as much as it is about finding an optimal solution, because part of finding the optimal solution is finding people to work with each other.”
How an MIT research project became a global programming languageWith millions of users across the world, Julia has been used to conduct cutting-edge research and to design new drugs, jet engines, heat pumps, and more.It all started with some exasperated emails. Back in 2009, a group of researchers began venting their frustration with the programming languages designed to help scientists and other researchers perform complex mathematical operations and statistical simulations without learning how to code. These programming languages were rigid and slow. If scientists built something that really worked, they’d need to rewrite the entire program in another language just to run it more quickly.
The emails turned into a research project at MIT with the mission of building an easy-to-use, high-performance programming language called Julia, which is designed for scientific research, data analysis, and modeling complex systems such as jet engines, drugs, financial markets, and robots, to name a few examples.
That research project turned into a lab at MIT, and the lab turned into the company JuliaHub. Along the way, Julia gained a loyal following among scientists, engineers, mathematicians, and others. Today, the free and open-source language counts more than 1 million users, including people working in thousands of companies and universities around the world.
It is only a slight exaggeration to say Julia has been used to model everything under the sun, from the behavior of tiny atoms to semiconductors, neural networks, race cars, and airplanes. It has also been used to study much beyond the sun, with astronomers using Julia for imaging black holes.
Julia’s secret sauce is in the way it compiles code depending on the type of data being used. Such “just-in-time compilation” makes Julia faster and more flexible than other numerical programming languages.
“Scientists and engineers are not programmers. Building scientific applications with multidisciplinary teams of scientists, engineers, and programmers is challenging,” JuliaHub co-founder and CEO Viral Shah says. “We asked: What if you could equip the scientists and engineers with a programming language that allowed them to express their ideas at a high level and also get great software performance?”
Making programming easy for non-programmers has been a north star for JuliaHub’s founders, who include Julia co-creators Shah, MIT professor of mathematics Alan Edelman, Jeff Bezanson SM ’12, PhD ’15, and former MIT research scientist Stefan Karpinski.
In April, JuliaHub’s team took another big step in that direction with the launch of Dyad 3.0, the latest version of its AI platform to help engineering teams accelerate the development of complex physical systems like rockets, heat pumps, and satellites. Engineers are already using Dyad to direct autonomous AI agents as they work through physics simulations, safety analyses, quality controls, and more.
“With Dyad 3.0, you can upload data and design documents and the system will design an entire aircraft for you,” Shah says. “Working with customers like Boeing, we are building agentic hardware design capabilities for engineers. Simplistically, you want to say, ‘Okay computer, build me a plane’; upload the design documents; and have the system account for all the physics, compile all the code, verify everything, and build the entire design agentically.”
Humble beginnings
After discussing the need for better programming languages for scientists and other researchers, Julia’s co-creators started the Julia Lab around 2009. The Julia Lab remains active in MIT’s Computer Science and Artificial Intelligence Laboratory.
The core idea was to create a high-performance platform that would excel at engineering, scientific, and mathematics applications. Shah says before Julia, scientists and engineers would either have to hire someone to build software for them or accept the slow performance of the few programming languages designed for them.
“We wanted to create something as easy to use as Python or MATLAB but as fast as the C programming language,” Shah says. “We built Julia for ourselves.”
Edelman says at first, the researchers didn’t think anyone would want their creation.
“We figured it would take 10 years before anyone was interested, but we said, ‘Patience is a virtue, so let’s do it,’” Edelman recalls.
The MIT researchers announced Julia with a blog post in 2012. They quickly realized many other researchers shared their frustration.
“When we first started, we were targeting interactive research workflows, but increasingly people are using it for everything,” Bezanson says. “Now we’re moving the whole stack of the language onto smaller, embedded devices as we evolve with our users.”
Since those early days, Edelman has taught a class on Julia with students from nearly every department at MIT. Today, he often learns students are already using Julia when they enroll in the class for applications as wide ranging as robotics, astronomy, physics simulations, and finance.
“Researchers come up to me and say, ‘I tell my supervisor I’m using Julia because it’s fast, but don’t tell them I’m using Julia because it’s really fun,’” Edelman says. “The key thing is Julia’s abstractions. A lot of times a coding language forces you to solve the one problem you’re thinking about. Julia’s language makes it so you’re solving not only the problem you’re thinking about, but other people’s problems around the world too. It encourages you to solve problems more generally.”
As Julia gained popularity, researchers around the world started asking the Julia team for support. By 2015, the demand became strong enough that they decided to start JuliaHub and help users through the company full-time. They received support from the MIT Deshpande Center for Technological Innovation and others at MIT to get the company off the ground.
JuliaHub’s work has evolved from simply helping users to advancing the language more generally. That’s powered an impressive list of creations from Julia’s loyal users. Julia has been used to simulate computer circuits, detect health disparities, model global climates and oceans, analyze brain activity, and more.
After someone built a pharmaceutical modeling platform in Julia, it was used to accelerate development of Moderna’s Covid-19 vaccine. In another case, researchers used Julia to create a program for avoiding aircraft collisions. They found it ran about 50 times faster than an earlier version built on Python. Engineers at Meta used Julia to develop a better audio codec for WhatsApp’s 4 billion users.
“Over the years we’ve seen industrial, government, and academic users doing all kinds of interesting things with the Julia language,” Edelman says. “It’s honestly surprised us in many ways, the wide-ranging things people are using it for.”
Autonomous design
JuliaHub launched Dyad 1.0 in June of 2025 as a research agent to accelerate programming and Dyad 2.0 in December. The founders believe Dyad 3.0 represents a new level of ability and autonomy for designing complex systems.
“One important thing about Dyad is that it is a physics compiler and hence enforces physical laws,” Shah explains. “General AI systems often solve physical problems in ways that violate physical laws. When using the Dyad agent, it will detect such violations and guide the agent in the direction of the physically correct solution. We expect it will decrease design times in product engineering by orders of magnitude, leading to months of work being accomplished in hours.”
One way Edelman sees the impact of Julia is through his class. One student recently used Dyad to model how robots move around in space. Another used it to build a rocket engine.
“At the end he said, ‘I couldn’t believe how easy that was — I just got a rocket engine!’” Edelman recalls.
How an MIT graduate student helped a team of young scientists test their experiment at CERNPhysics PhD student Manu Srivastava helped high school students in India develop a test that could contribute to one of the world’s largest neutrino experiments.This past spring, MIT physics graduate student Manu Srivastava opened an email from a group of high school students in India he had never met.
They were hoping to enter Beamline for Schools, an international competition that gives secondary school students the chance to design and carry out experiments using particle accelerator beams. And they were looking for a mentor.
Srivastava, who studies quantum gravity as a PhD student in the MIT Center for Theoretical Physics – a Leinweber Institute, with Professor Hong Liu, gets other requests to mentor students, often through companies charging families for access to scientists or students at prestigious universities. He usually declines, but this message came directly from the students.
“I've also cold-emailed a lot in my early career, and it usually never works,” he says. “But this email seemed very genuine. They wanted to do something nice and they just needed some guidance.”
Many months and many more emails and calls later, the students secured a place with Srivastava to attend CERN, in Geneva, where they spent two weeks turning their proposed idea into a real experiment.
Finding an experiment worth doing
Calling themselves Team attoPION, the students are one of five teams selected in the 13th annual Beamline for Schools competition from a record 712 teams representing 89 countries and more than 4,500 students. The six high schoolers met through a combination of science competitions and mutual friends, and attend four schools in four cities across India.
When they first met with Srivastava, the students already had several experimental ideas. His role, he says, was to help determine which directions were practical and scientifically interesting.
They settled on measuring pion charge exchange. Pions are short-lived subatomic particles that can carry positive, negative, or neutral charge. In the process the students want to study, a positively charged pion interacts with a neutron in a target material, producing a neutral pion and a positively charged proton. The team wants to characterize how often that reaction occurs.
Srivastava suspected such a measurement could have relevance to the Deep Underground Neutrino Experiment, or DUNE, a major international experiment designed to study neutrinos.
Dave Newbold, a co-spokesperson for DUNE, says understanding how pions interact with matter helps researchers quantify uncertainties in DUNE’s measurements. In particular, pion interactions can affect estimates of a neutrino’s flavor and energy, which researchers need to measure accurately to determine whether they have observed something new.
And although Beamline for Schools has an educational mission, Newbold says the students aren't simply reproducing a classroom demonstration. “The proposal is real experimental particle physics!” he notes.
If successful, Newbold believes the work could improve scientists' understanding of this particular interaction and potentially lead to a publishable result. Similar “test beam” experiments remain important tools in particle physics: DUNE's detector designs were themselves demonstrated using the (albeit much larger) ProtoDUNE experiments at CERN.
“This [proposal] stands out because of the work the students have put into motivating their measurement, and demonstrating that the experiment is feasible,” Newbold says. “It's certainly at a level far above anything I was thinking about at high school.”
Learning to navigate uncertainty
At CERN, the students worked hands-on with detectors and data-acquisition systems, collected and analyze data, and attended talks by CERN scientists.
In advance of the trip, the team worked with Berare Göktürk, one of the support scientists for Beamline for Schools. In their preparation sessions for the experiment, they realized that the charge-exchange process they hope to observe is extremely rare, forcing them to think through how they might reliably detect it.
With just a few months months to prepare and only 12 days of test-beam time, Göktürk cautioned that producing a result useful to a much larger experiment would be an ambitious outcome.
“We prepare in the best way possible, but we also stay humble and we are aware of the limitations we have,” she says. Her priority is for the students to “understand the journey of a scientist” as they encounter technical problems and work together to solve them.
For Srivastava, mentoring an experiment has also taken him well outside his own specialty. A theoretical physicist, he credits MIT's culture with encouraging him to follow questions beyond the boundaries of his research, including by attending seminars, colloquia, and research meetings across physics.
The experience has been personally meaningful for Srivastava, who grew up in India and sees the mentorship as a way to encourage young people there to pursue fundamental science.
“I didn't even know what CERN was in high school,” he says. “But these students, they are just that good. They deserve all the credit.”
How MIT Sandbox has turned student ideas into $8.7 billion in global impactThrough a decade of non-dilutive funding, hands-on mentorship, and a safe space to fail fast, the MIT Sandbox Innovation Fund Program has helped students translate curiosity into real-world impact.Although Jacob Becraft had two swings and two misses when he first tried to become an entrepreneur as a graduate student, the MIT Sandbox Innovation Fund Program allowed him to keep at it. This especially benefited cancer patients, as Becraft went on to co-found Strand Therapeutics: a $550-million firm whose programmable mRNA drug has shrunk tumors in patients who had exhausted all other treatment options.
Stories like Becraft’s took center stage at the recent 10-year anniversary celebration of the MIT Sandbox Innovation Fund Program, where student founders, alumni, mentors, and university leaders gathered to reflect on a decade of empowering student entrepreneurs. Speaking at the event, Becraft referred to Strand as "our third swing at the plate," explaining that the Sandbox model gave him "the freedom and ability to fail fast" — letting previous venture ideas "blow up in our faces" before moving on.
For Strand, Becraft says, MIT Sandbox helped him and his co-founder, Tasuku Kitada, to "get out, do some travel, some market research, meet with experts in the field, meet with mentors who could help us build the company — and eventually find investors who were going to back this big vision to transform medicine."
MIT Sandbox was launched in 2016 by Ian Waitz, then-dean of the School of Engineering and now MIT's vice president for research, to lower the barrier for students to try entrepreneurship. The concept of a new program focused on student-led entrepreneurship was developed in consultation with internal MIT leaders and supporters of MIT, including Alan Spoon, a life member emeritus of the MIT Corporation. From its inception, MIT Sandbox has been open to all MIT students, from undergraduates to PhD students. Teams are awarded between $500 and $5,000 to begin their process, and they are matched with two mentors and connected with other expert advisors.
As they make progress, students can go before the program’s funding board to ask for up to $25,000. Supported entirely by alumni, corporate sponsors, entrepreneurs, and investors, the program has grown to include about 350 teams each semester, some of which are new and some continuing their participation according to their own timelines.
Anantha P. Chandrakasan, MIT provost, explained in the program's decade-in-review report: "Since its inception 10 years ago, MIT Sandbox has been a defining part of MIT's innovation ecosystem, ensuring that every student with the curiosity to explore entrepreneurship has the resources, mentorship, and community to take their first steps."
MIT Sandbox is a "home," where students can "explore, seriously test assumptions, talk to customers, build prototypes, fail, pivot, learn, and grow," says Jinane Abounadi, founding executive director of Sandbox. "And they can do that with a lot of support — and I don't just mean financial support. I mean a lot of support from a lot of people."
For Samuel Udotong, co-founder and CTO of Fireflies.ai, early funding was the difference between an idea and a company. "I think largely because we had gotten a little bit of Sandbox funding, we were actually able to take the risk to move out to San Francisco and try to build the company," he says. "But it would have been really a money barrier if we hadn't gotten the initial $5,000 from Sandbox."
Startup investor and advisor Sophie V. Vandebroek says, "MIT has extraordinary students from around the globe as well as faculty who are top experts in their fields. What’s often lacking," she says, "is confidence. That is where Sandbox plays a vital role. Sandbox enables every individual student to believe that they can be an entrepreneur."
At the anniversary celebration, Fred Parietti, co-founder and CEO of Multiply Labs, recounted how his early product prototypes were developed on his kitchen table and had to be moved regularly according to the dictates of his grad school housemates. Those prototypes wouldn't have been built at all, he said, without MIT Sandbox.
The first funding he received was minimal, "but it wasn't zero, and zero represented my resources as a student. That belief in us and the possibility to build a prototype were game-changers," Parietti said.
Multiply Labs, with 60-plus employees, has raised $36 million and develops robotics technology to manufacture biological drugs safely and economically. The firm supplies pharmaceutical customers including AstraZeneca and Kyverna Therapeutics, whose chief medical and development officer, Naji Gehchan, is an MIT Sandbox mentor.
That same willingness to back an unconventional approach helped AeroShield get off the ground. "One of the things that enables me to stand here today is that Sandbox created a safe environment where it was encouraged to look at this problem backwards, rather than from the nanostructure up," says Elise Strobach, CEO and founder of AeroShield.
The anniversary celebration speakers also included Ross Finman, CEO and founder of Augmodo; Laureen Meroueh, CEO and founder of Hertha Metals; and Daris Bunadar, chief scientist at Lightmatter. All were working on their PhDs when they started exploring commercial applications of their research. All recognize the critical role that MIT Sandbox, in addition to other programs — such as the MIT I-Corps Program, the Martin Trust Center for MIT Entrepreneurship, MIT Venture Mentoring Service (VMS), and the Bernard M. Gordon-MIT Engineering Leadership Program — played in their development as entrepreneurs. These programs offered the space to explore the possibility of not only founding a deep tech company, but also taking on an executive role as their ventures raised venture capital and grew into substantial companies. Today they all have big ambitions for the growth and impact of their companies — ambitions that are made possible only thanks to innovative technologies and an entrepreneurial drive.
Over its decade of existence, MIT Sandbox has supported over 4,000 teams, representing 8,000 participants associated with a wide range of industries and nonprofit endeavors. It has disbursed more than $11 million in non-dilutive funding, meaning the program takes no stake in the resulting ventures. MIT Sandbox has been involved in the creation of 475 companies in more than 30 countries, and companies that were started in the program have raised $8.7 billion in venture funding.
MIT Sandbox collaborates with other programs across MIT — including the Martin Trust Center, VMS, Kuo Sharp Center, MITdesignX, the PKG Center for Social Impact, the MIT Climate Project, I-Corps, and others — and its teams have excelled in innovation accelerators and competitions. Nine out of 10 winners of MIT's $100K Entrepreneurship Competition have been MIT Sandbox participants.
Apart from the program's impressive results, MIT Sandbox aims to first and foremost serve as a great educational tool, developing the innovators themselves.
"From an educator's perspective, this is just another incredible way to teach," said Abounadi at the anniversary celebration. "MIT Sandbox is a place where students can start seeing themselves as people who can create a meaningful impact in the world," she said, "and that is really what innovation and entrepreneurship are all about."
Paula T. Hammond, School of Engineering dean and Institute Professor, echoed the same sentiments: "What I find most compelling, year after year, is not only what students build, but how they change. They gain confidence, learn to refine before they scale, and begin to see themselves as people who can create meaningful impact, strengthening not only their own trajectories, but the broader MIT community."
Gage Coon: An Earth scientist exploring the power of microbesThe PhD student’s research on how microorganisms digest compounds in their environment could enable advances in wastewater treatment.Growing up in Waverly, Tennessee, Gage Coon spent much of his childhood outside. His family had everything from chickens to horses and even an emu named Big Bird. Coon and his cousins would explore the woods surrounding their home, and his father, a mechanic, taught him how to build and repair things around the house. His mother, a secretary at the local high school’s vocational school who loves gardening and birdwatching, encouraged him to experience as much of the world around him as he could.
That hands-on upbringing, which taught Coon to appreciate the natural world and the processes that sustain it, continues to influence how he approaches science today.
Now entering his third year as a PhD student in MIT’s Department of Earth, Atmospheric and Planetary Sciences, Coon studies some of the smallest organisms on Earth: microbes. His research focuses on how microorganisms cycle carbon and sulfur through the environment and how to leverage those processes to help address climate change. Though he studies organisms too small to see with the naked eye, the experimental nature of his work — whether in the lab or on a research vessel in the open ocean — is especially satisfying.
“I think I enjoy that physicality of seeing what I’m working with, seeing its change, and being able to touch it,” Coon says.
Coon did not initially set out to study microbiology. His interest in science began with chemistry. A high school chemistry teacher and a summer program introduced him to the subject. But later, at the University of Tennessee at Knoxville, he joined a lab focused on microbial biogeochemistry and was delighted to find a field that brought together the different areas that interested him: chemistry, the environment, and the larger climate processes shaping our Earth.
The transition from rural Tennessee to Cambridge, Massachusetts, and MIT has been a significant one. As a first-generation student, he did not learn about PhD programs until several years into college.
Once he discovered academic research, however, Coon was drawn to the possibility of spending his career learning.
“I discovered this world of academia, and so I was really excited when I learned about it,” he says. “I was like, ‘Oh my god, constant learning. That is exactly what I want to do forever.’”
Coon began studying the microbes that drive carbon and sulfur cycling in marine sediments as an undergraduate, eventually joining research cruises to investigate these processes firsthand.
His first research cruise, in 2022 after his second year of college, took him to the Atlantic continental slope to study methane seeps and how microbes prevent this methane from escaping to our atmosphere. For Coon, experiencing the ocean up close changed the way he understood the microscopic organisms he was studying.
“It is very powerful seeing yourself in the middle of the ocean, with a whole other world of complex life beneath you,” he says.
At MIT, working with his advisor Tanja Bosak, a professor of geobiology, Coon has continued studying microbial carbon and sulfur cycling, but with a greater emphasis on the applications. One of his major projects explores how microbes could be used to reduce methane emissions from wastewater treatment.
When wastewater is treated, microbes break down organic material in large tanks called anaerobic digesters. One of the final products of this process is the powerful greenhouse gas methane. However, Coon and his colleagues found a way to change what the microbes produce by adding gypsum, a waste product that is created from fertilizer manufacturing
The system uses the added gypsum to turn the methane into carbonate, which can be used to make cement, agriculture, and pharmaceuticals. The process also produces elemental sulfur, necessary for global fertilizer production, which is currently sources from oil and gas refinement. The approach effectively turns two waste products, sewage and waste gypsum, into useful materials while reducing greenhouse gas emissions.
For Coon, the possibility of creating a system that is both environmentally beneficial and economically useful is central to the project. Now that the laboratory experiments have ended, the researchers are looking toward conducting pilot-scale testing. Coon and his advisors have been communicating with companies interested in adapting the system to larger facilities, and hope the technology can eventually move beyond the laboratory.
“If enough small places start doing their pilot-scale studies, then hopefully you could convince some place like Boston or another big city to do this and really make a contribution to our global goal to decrease emissions on the gigaton scale,” he says.
The wastewater project is only one part of Coon’s PhD research. He also studies geological processes that could produce molecular hydrogen, a potential carbon-free energy source. His work examines how iron-rich rocks break down and generate hydrogen underground. He is continuing his thesis work by focusing on microbial competition for acetate, and what this means for global methane emissions from coastal wetlands. This work could improve future climate predictions and support engineered mitigation efforts to decrease emissions from these wetlands.
Across these projects, Coon is interested in the connection between the microscopic and the massive. But Coon’s PhD has also given him an opportunity to think about science beyond his own research.
One of the parts of graduate school he has enjoyed most is mentoring younger researchers. He has worked with a handful of students through MIT’s Undergraduate Research Opportunities Program and from Tufts University, teaching them laboratory techniques and experimental geobiology.
Outside the lab, Coon maintains some of the same connection to the natural world that characterized his childhood in Tennessee. He spends time hiking to explore local geology, playing bluegrass guitar, and speed-solving Rubik’s Cubes.
Looking ahead, Coon sees himself continuing in academia, working in government, or helping to bring environmental technologies into practice.
What matters most, he says, is continuing to produce knowledge that can help people understand and potentially improve the world around them.
“I do think, no matter what,” he says, “I’ll be somewhere thinking about how microscopic life connects to the global ecosystem and carbon emissions.”
Looking beyond natural sequencesA new machine-learning framework aims to improve the success rate of computational protein design while moving away from results that reproduce sequences found in nature.A protein’s function is determined by its structure, and structure — the way a protein folds — is determined by its sequence of amino acids, the building blocks of proteins.
Many methods for designing novel proteins, including examples that could bind to a disease-causing molecule in our cells, involve a two-step process: The structure comes first, and then a machine-learning framework generates a repertoire of sequences that could potentially adopt that structure.
In nature, many different amino acid sequences can fold into the same structure. At the same time, one amino acid sequence can potentially adopt different structures depending on the protein’s flexibility or a functional trigger. Therefore, when researchers use artificial intelligence to design new proteins, the challenge is to guide AI to “see” that there are many potentially useful answers — that many sequences can adopt the same fold
“For years, the field has measured success by asking whether a model can reproduce the protein sequence that evolution happened to select — our work shows that this isn’t the best metric for protein design,” says Amy E. Keating, Department of Biology head, Jay A. Stein (1968) Professor of Biology, professor of biological engineering, and senior author of a paper recently published in PNAS.
PottsMPNN, a new machine-learning framework developed in the Department of Biology, incorporates the physical principles that govern protein structure and stability, improving sequence generation and the ability to predict how mutations will affect a protein’s stability. In other words, the model has a better understanding of the sequence-energy landscape, meaning the relationship between the identity of each amino acid and the stability of the protein.
Adding this framework to a protein design pipeline will allow researchers to design structurally feasible proteins with sequences that don’t resemble those of any native protein.
“If we’re thinking about a completely novel, designed structure, there would be no native sequence to compare it to,” says graduate student and lead author Foster Birnbaum. “What we actually care about is how likely the generated sequences are to fold into the desired structures, how well the model understands the sequence-energy landscape, and how well it can predict the effect of mutations on the stability of the protein.”
Beyond the noise
In the same way that AI has recently powered some dramatic social changes, so too has machine learning impacted the pace and breadth of fundamental biological research. Only recently has it become possible to reliably use a computational model to generate a protein structure or sequence. Perhaps the most widely used model today, however, was released in 2022.
“For a field that’s moving as fast as machine learning in biology, that model has not been surpassed — we’ve been trying to understand why that is, and what it is about that model that makes it so useful,” Birnbaum says.
Birnbaum was first interested in strategic applications of something researchers call “noise,” or adding variations to a protein structure during training. Noise decreases the tendency of the model to overly mimic native sequences, increasing the diversity of structures for which it’s able to generate sequences.
PottsMPNN also uses a pairwise distribution to capture interactions between amino acids. The ability to account for the physical interactions between all 20 possible sequence options at a pair of positions in the protein is a key reason that PottsMPNN more accurately models the sequence-energy landscape than other methods.
Finally, Birnbaum says, they introduced sets of evolutionarily related sequences into training the PottsMPNN framework to teach the model how different sequences can adopt the same folded structure.
Birnbaum acknowledges that in trying to shift away from adhering to native sequences, incorporating evolutionary information is, in some ways, still a reliance on them. But PottsMPNN succeeded in demonstrating that as the model depends less and less on native sequences, structural compatibility and energy prediction, including for novel proteins, improve.
Protein design in the age of AI
“Once we can design any protein we want, that enables us to do a potentially scary amount of biological engineering,” Birnbaum says. “It’s a difficult task, but I’m really optimistic about this century’s progress in biology.”
Birnbaum hopes that the model could be further improved and fine-tuned for a specific task, which has in the past led to better predictions, for example, on the outcome or consequence of a particular mutation.
Ultimately, according to Keating, “Our methods move the field toward designing useful new-to-nature proteins for diverse applications while providing a stronger foundation for future advances.”
MIT engineers create a system for building shape-changing smart devices Dubbed “bifur-circuits,” these interactive building blocks could be used to develop reconfigurable robotic grippers or customized assistive devices.A new set of modular components allows users to create reconfigurable smart devices with electrical connections that keep working no matter which shape the structure forms.
This electrical modularity can enable engineers to design interactive devices that can sense which shape they have taken, without the need for external wires. For instance, the modular components, which the researchers call “bifur-circuits,” could be used to rapidly design and prototype adaptable smart devices, like assistive furniture that helps individuals change body positions while recovering from injuries or reconfigurable robotic grippers that remain electrically connected when they change shapes for different applications.
Developed by MIT researchers, these 3D-printed building blocks, which are a type of structure known as a mechanical metamaterial, can be combined to form many more possible configurations than traditional metamaterial structures.
In a study presenting the new system, the researchers demonstrated several interactive objects, including a chair that converts to a table with storage and can also flatten for stowing. The structure senses its configuration and sends corresponding messages to an electronic display.
These new metamaterials could also be used to design antennas for communications and sensing that form new shapes to adjust their frequencies in changing environmental conditions, without bulky mechanical parts.
“Metamaterials can make complex mechanical assemblies easy to manufacture just by using repeating units. Our work expands on this design space. If we think of mechanical metamaterials as building blocks, then our work is one way to take advantage of their geometry to embed intrinsic intelligence into hardware, which could open many possibilities,” says Marwa AlAlawi, a mechanical engineering graduate student and lead author of a paper on the devices.
AlAlawi is joined on the paper by co-senior authors Ticha Sethapakdi, an electrical engineering and computer science (EECS) graduate student at MIT; and Stefanie Mueller, an associate professor in MIT’s departments of EECS and Mechanical Engineering and leader of the Human-Computer Interaction Group at the Computer Science and Artificial Intelligence Lab (CSAIL). Their co-authors include others at MIT, the University of Tokyo, and the University of Michigan. The research will be presented at the ACM Symposium on User Interface Software and Technology.
Shape-changing interactive structures
Mechanical metamaterials are programmable, three-dimensional structures of repeating units that can form complex shapes due to their geometries. When squeezed, pushed, or pulled, metamaterials can bend or twist in precise ways.
For instance, “auxetic” metamaterials get wider when stretched, instead of narrowing.
In prior work, the MIT researchers used auxetic metamaterials to build reconfigurable antennas that formed three shapes depending on how the structure was stretched. This allowed the antenna to dynamically adjust its frequency range without complex, moving parts.
Next, the team wanted to expand the number of antenna configurations but were limited because the auxetic metamaterials could only form three fixed states.
In this work they created “bifur-circuits,” which are auxetic metamaterials that can form many more shapes based on how the modular units are connected and rotated.
The units are also designed to be electrically modular. Due to the way conductive material is integrated into the bifur-circuits, electrical connections throughout the structure are maintained no matter how the object is rotated, pressed, or twisted to form new shapes.
To create interactive objects with many possible configurations, bifur-circuits leverage a property known as mechanical bifurcation.
Mechanical bifurcation is a sudden change in how a mechanism behaves when a force exerted on it passes a tipping point. For instance, when you gently bend the ends of a plastic ruler, once that force reaches a critical threshold, the ruler buckles.
In bifur-circuits, this bifurcation occurs when connected blocks are rotated in certain ways around a pivot point. The property allows connected blocks to form more stable configurations than one block could on its own.
Adding more bifur-circuits to a structure exponentially increases the number of potential configurations.
“Bifurcation allow us to significantly expand on this reconfigurability space. Just adding one extra unit gives us so many more combinations out of the same structure,” says AlAlawi.
Connecting and rotating components activates a unique circuit between adjacent units. This interactivity allows the units to communicate with one another, enabling the structure to sense its configuration.
One of the biggest challenges the researchers faced was incorporating a conductive material that was flexible enough to bend, but still offered enough efficiency in the flow of electricity.
“The conductive material was a constraint we had to work around in the design process, and it dictated how the sensing between blocks would happen,” AlAlawi says.
Once they perfected the design, the researchers tested the durability of reconfigurable structures by compressing them more than 10,000 times. The structures showed no degradation in electrical connectivity.
The researchers also developed a user-friendly construction and simulation tool to simplify the bifur-circuit design process. The software generates instructions for a multimaterial 3D printer, which can fabricate the reconfigurable objects in one pass.
They demonstrated the versatility of bifur-circuits by fabricating a chair that can sense its geometry when its shape is changed to a tea table, as well as a shape-shifting controller that will launch one of several video games based on its configuration.
Bifur-circuits could someday be used in applications like interactive rehabilitation tools, shape-changing grippers for modular soft robots, or reconfigurable shelters that could respond to changing environmental conditions after a natural disaster.
In the future, the researchers want to explore more applications for bifur-circuits. They also want to add more interactivity into the structures and investigate additional metamaterial shapes.
“Bifur-circuits are one step toward developing mechanical building blocks with integrated intelligence. It would be interesting to build on this work and come up with building blocks that allow us to create a structure with any form or shape we want, and which are structurally stable and can be actuated,” AlAlawi says.
This work was funded, in part, by Japan’s Science and Technology Agency and the Bahrain Crown Prince International Scholarship Program.
AI helps design new materials that work in the real worldThe “CrysVCD” tool developed at MIT could cut the huge amounts of time and money spent on screening out chemically unstable designs.Today, anyone with a large enough artificial intelligence model can generate millions of new material designs in minutes. Unfortunately, that hasn’t led to a huge leap in the number of new materials being used to improve the performance of products like computer chips and rockets.
One reason for the translation gap is that current models don’t reliably factor in the chemical stability of the materials they generate, and unstable materials aren’t very useful in the real world. That forces industries to allocate huge computational budgets to screening out all the unstable materials they generate, in some cases leaving behind a tiny fraction of usable options.
Now, MIT researchers have developed a framework that can be applied at the beginning of the materials generation process to vastly improve the stability rate while achieving targeted material properties. It works by ensuring every design satisfies certain key rules of chemistry relating to the electrons around the materials’ atoms before the expensive generation step begins. The researchers call their approach “crystal generator with valence-constrained design, or CrysVCD.
In a paper published today in Nature Computational Science, the researchers show how CrysVCD allowed several commonly used material models to meet those valence shell rules more often, and used it to achieve high lattice-dynamics stability — a stringent stability test — in nearly 70 percent of computational material generations. They also showed the approach could support the creation of materials with specific desired properties, like high thermal conductivity or high dielectric constant, which is important for computer chips and data centers.
A hint of how the researchers envision people using their system is in the name.
“If material-generating models are like DVDs, we are like the DVD player,” says associate professor of nuclear science and engineering Mingda Li. “You can plug this into any kind of model, not only existing diffusion models but also future models, where people can’t generate enough stable materials, and it can improve stability.”
Joining Li on the paper are Mouyang Cheng SM ’26 and Weiliang Luo, MIT doctoral students in materials science and engineering and chemistry, respectively; Hao Tang PhD ’26, a recent graduate in materials science and engineering; Bowen Yu, a senior undergraduate in physics; Yongqiang Cheng, a staff scientist at the Oak Ridge National Laboratory; Weiwei Xie, an associate professor at Michigan State University; Ju Li, MIT’s Carl Richard Soderberg Professor in Power Engineering; and Heather Kulik, MIT’s Lammot du Pont Professor of Chemical Engineering.
More efficient materials
Computational approaches to materials design have been around for decades, but recent advances in artificial intelligence have increased excitement about their potential. Of particular interest are models that can start with a desired material property and work backward to deliver a material that achieves that goal.
Some of those models use an AI technique known as diffusion, which is commonly used to generate images, while others use large language models like the one powering ChatGPT and Claude, but both approaches struggle to ensure their material generations achieve chemical stability or follow fundamental principles about how chemicals interact and behave.
The solution has been to add another layer of computing on top of the generative process to filter out unstable materials.
“It’s becoming easy to generate the material structure,” Cheng says. “But the validation process, especially the part where you test the stability, has a huge computational cost. It’s something like 90 percent of the computational cost for creating usable materials, and it can take weeks or months.”
Big companies with huge computing budgets can afford to run those processes, but many small companies and research labs can’t, potentially limiting innovation in the field.
“In academia, where we have fewer resources, I think we can still achieve strong performance with smarter designs and other approaches,” Kulik explains. “Generating a model and then down-selecting for stability is inefficient. There’s a high computational cost. But if we put a language model in the beginning of the process to constrain the generation, you can significantly enhance the ratio of stable materials generated.”
The new study involved MIT researchers affiliated with the departments of Materials Science and Engineering, Chemistry, Chemical Engineering, Physics, and Nuclear Science and Engineering. Together the researchers combined AI diffusion models with a language model. In the first stage of their process, the language model produces chemically valid formulas. In the second stage, the diffusion model uses that formula to generate the corresponding atomic structure of the crystal material in coordination with the underlying material generation model.
“Diffusion for typical material generation is a slow process — you can think of it like 1,000 steps to create one material,” Luo says.
“In contrast, when our model is used in the beginning, you can think of it like five steps. It allows you to screen out the unstable materials to generate higher quality materials. And it works with any models generating materials,” Tang adds.
The researchers showed their approach created more stable materials an order of magnitude more efficiently than approaches that rely on screening materials after they’re generated. When fine-tuned on stability metrics, their approach produced crystalline materials that achieved 68 percent mechanical stability and 85 percent metastability, which measures if a material stays in a stable state when undisturbed.
The researchers then used their approach to generate material candidates with high thermal conductivity and easy polarization in an electric field.
“These are materials useful for the semiconductor industry and high thermal conductivity materials relevant to data center cooling,” Ju Li says. “In principle, you could also use this to create other properties, but thermal conductivity has become really important for cooling data centers. There’s been a huge increase in energy use in that industry, and 30 percent of that energy goes to cooling. The industry needs materials with high thermal conductivity to more efficiently remove the heat.”
Democratizing material design
The new approach doesn’t work with every kind of material — it works best with solid structures with highly ordered internal arrangements. Still, the approach could be used to generate stable new crystalline materials with a host of important properties.
“We are not just generating stable materials, we’re also prioritizing performance,” Cheng says. “Any time you have two goals, achieving those goals with anything over 50 percent is hard in this field. In the past, people might have a goal for specific properties and not stability, or vice-versa, and get a single-digit percentage of materials that fit their goal.”
Ultimately the approach will enable more researchers to develop novel materials for a range of next-generation applications.
“This will save huge computation costs and time by removing downstream selection requirements,” Li says. “That will help not only large efforts that generate hundreds of millions of materials, but also smaller research groups with targeted applications.”
The work was supported, in part, by the U.S. Department of Energy, a Mathworks Engineering Fellowship, the National Science Foundation, and the U.S. Defense Threat Reduction Agency.
Retooling to help democracy revive Deindustrialization didn’t only hurt some workers, Daron Acemoglu says in a new book; it shrank the coalition supporting democracy, which needs expanding.In the 20th century, the United States built the world’s dominant manufacturing powerhouse. A thriving middle class grew, well into the 1970s. The U.S. was a beacon of democracy, defeating fascism in World War II and beating back communism and other forms of authoritarianism during the Cold War.
To MIT economist Daron Acemoglu, there is a deep intertwining among these things. Democracy, his work has shown, helps economies grow. As the industrial economy expanded, in Britain, the U.S., and other countries in the 19th and 20th centuries, so did democratic participation, as people tried to stake out new rights, or make real the rights ascribed to them.
“The industrial age created the tools for shared prosperity around which democracy organized,” says Acemoglu, a Nobel Prize-winning economist and Institute Professor at MIT.
Today, though, income inequality has grown markedly in the U.S., starting around 1980. The U.S. has deindustrialized to a significant extent, offshoring production and hurting shop-floor workers and their families. As Acemoglu sees it, this economic realignment has had deep civic consequences: A stranded working class has become more alienated from the institutions and ideas traditionally buttressing democracy.
And for those around the world supporting democracy, he says, “You really need to have the working classes in your coalition for it to make any sense.”
Acemoglu explores these topics in a new book, “What Happened to Liberal Democracy? Remaking a Politics of Shared Prosperity,” published by Penguin Random House. In it, he looks broadly at the benefits of democracy, the tensions it faces in everyday life, and democracy’s trajectory in recent decades.
Broadly, Acemoglu favors rebuilding “working-class liberalism,” essentially seeking the largest coalition that favors self-government and the rule of law. “Working-class liberalism has strong communal roots, eschews social engineering, and prioritizes shared prosperity, jobs, and public services,” Acemoglu writes in the book.
After all, Acemoglu believes, democracy is the one form of rule that promotes rights and liberties, and allows the flexibility and “experimentation” we need to address all the challenges a complicated world throws at us.
“Democracy is the only way we can make progress in society,” Acemoglu says. “Trying to impose top-down solutions to all our problems will ultimately not work.”
Along the narrow corridor
Acemoglu has long studied the relationship between economic growth, rights, and democracy. With economist Simon Johnson of MIT and political scientist James Robinson, now of the University of Chicago, Acemoglu published a landmark series of studies in the early 2000s demonstrating that economic growth is helped by the development of stable democratic institutions, including property rights. For that work, Acemoglu, Johnson, and Robinson later shared the 2024 Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred Nobel.
Acemoglu’s 2012 bestseller “Why Nations Fail”— written before democracy’s current challenges seemed as acute — synthesized his research on these topics. His 2019 book “The Narrow Corridor,” co-authored with Robinson, casts democratic governments as essential to liberty because they protect people simultaneously from overreach by an authoritarian state, on the one hand, and from domination by other groups in society, on the other.
However, as Acemoglu has consistently emphasized, self-governance is an ongoing effort; this machine does not run on its own. Relatedly, in the new book, Acemoglu critiques some famous attempts to formulate governance as a neat “social contract,” including Jean-Jacques Rousseau’s conception of a “general will” in society.
Those ideas helped make the case for political rights, but actual governance in a pluralistic society will always be a messy process.
“You have to allow communities, and societies in aggregate, to build rules around shared values for anything to stick as institutions, norms, or aspirations,” Acemoglu says. “When you go down the social contractarian path, you sometimes fool yourself into thinking there are clear solutions to dilemmas that in reality don’t quite have such obvious ways of being resolved.”
For instance, Acemoglu notes, democracy itself “is built on tolerance and acceptance of plural perspectives, but how do you deal with people who are intolerant?” In the book, he largely regards interventions to stamp out seemingly intolerant thought as being unwise and politically counterproductive.
“You’re not going to have a clear-cut solution to all cases,” he says.
The economic realignment
Even with leaders backing a pragmatic, flexible approach to self-governance, democracy faces another challenge: supporting the material welfare of citizens. And here, “What Happened to Liberal Democracy?” takes an unflinching look at the postwar economy, finding fault lines that have shaken the political order.
The roughly three decades after World War II were fantastic for many workers in democracies, and certainly in the U.S., where middle-class incomes grew by 2.5 percent annually into the 1970s.
There were always going to be forces pushing back on this trend, and U.S. companies started offshoring and outsourcing production work to clamp down on wage growth. But one other technological and economic trend occurred just as the middle classes of the industrial economy were reaching new heights.
“Then computers happened,” writes Acemoglu in the book — referring to a complex set of economic and civic realignments involving technology-driven shifts in work.
Over time, computers started replacing significant numbers of clerical office workers, shop-floor industrial workers, and other types of employees who were earning middle-class wages without holding a college degree. In recent decades, middle-class incomes have only grown by about 0.5 percent annually.
To be sure, computers have produced plenty of benefits, and created many new forms of work. But as research shows, those jobs have tended to go mostly to college-educated employees, creating a significant split in society between well-educated, well-paid, white-collar workers, and less-educated, worse-paid workers in blue-collar and service jobs. That national share of income hauled in by the top 1 percent of earners has basically doubled in this time, from 10 percent to nearly 20 percent.
Crucially, in Acemoglu’s analysis, this material gap between more-educated and less-educated social cohorts has translated to U.S. politics, with political groupings reshuffling along educational lines, and cultural politics following suit. That’s the dynamic the U.S. faces now — even as one also accounts for the effects of social media and other polarizing features of contemporary society.
“We now live in a less-industrial world, and we also live in an age defined by social media, much greater levels of conflict, more polarization, and now AI, and all of that complicates things,” Acemoglu says.
Always a work in progress
This precise feature of contemporary society — deindustrialization fueling an earnings gap that has led to more political polarization — is what shapes Acemoglu’s prescription in response, the idea that “working-class liberalism” is needed to strengthen democracy.
There are many potential ingredients in this formula, from politicians determined to reach across class lines to workers regaining the impetus to organize in their workplaces.
“Trade union participation itself is a very important form of local governance that’s very difficult or unimaginable in an authoritarian society,” Acemoglu says, even while noting that he has not always agreed with the actions of particular unions in the past.
Still, Acemoglu adds, “I don’t think the economic aspect is the only one, in that you cannot just gain the trust of workers by ensuring there are wage gains. That is an important step but it is not sufficient.” Voters need asurances that politicians are thinking about them, at least share their concerns, and have a grounding in similar values. More candidates today need to seek a shared language about those things.
That’s not easy in a world characterized, in part, by global migrations, increasingly diverse national populations, and economic flux. But it is possible, Acemoglu thinks.
“There are deep dilemmas faced by liberal democracy that were sometimes going to come to boiling points, and this becomes more heightened when societies such as the U.S. and some European ones are simultaneously becoming more complex, more globalized, and more hetereogeneous,” Acemoglu says. On the other hand, he adds, “Multiracial tensions, I would say, were much worse for the U.S. in the 1950s and 1960s. We made democracy work then, in the face of much more difficult race problems, so why not today?”
None of this is a straightforward task, of course. “Forging working-class liberalism is a tall order in the best of times and much more challenging in today’s polarized environment,” Acemoglu writes in the new book. Still, he adds, even in frustrating moments, the stakes are too important for people to relent.
“Democracy is a success,” Acemoglu says. “It’s easy to fall into a trap of painting the democratic project as being doomed to failure, and I want to avoid that.” He adds: “It continues to be a work in progress.”
Cells use a little-known molecule to protect themselves from iron overloadThis discovery points toward new combination strategies against cancer, and may explain the iron buildup seen in disorders such as early-onset Parkinson’s disease.Iron is essential. Our cells need it to produce energy, carry oxygen throughout the body, and power countless chemical reactions that sustain life. But this metal has a dark side. When too much of it is left free inside cells, it can trigger destructive reactions that break down DNA, proteins, and even cell membranes.
Now, MIT associate professor of biology and Whitehead Institute for Biomedical Research member Ankur Jain; MIT assistant professor of biology and Koch Institute for Integrative Cancer Research member Whitney Henry; and Pushkal Sharma PhD '26 have discovered that cells rely on an unexpected protector against this threat: small molecules called polyamines.
The researchers’ detailed findings, published Aug. 14 in the journal Cell, reveal that polyamines act like storage lockers for iron, safely holding the metal in a non-reactive state until cells need it.
These findings solve a decades-old mystery about why cells maintain such extraordinarily high levels of polyamines and uncover a previously unknown defense mechanism that protects cells from toxic iron overload.
This work could also help scientists develop better cancer treatments, by allowing iron overload to trigger cancer cell death. It could also offer new clues about diseases like early-onset Parkinson’s disease, in which mutations affect polyamine levels within neurons.
The Jain Lab studies RNA, the intermediary between DNA and the tiny molecular machines called proteins that perform most of the essential tasks inside cells. The lab is particularly interested in how RNA folds, misfolds, and sometimes clumps inside cells.
Jain and Sharma first began studying polyamines because these molecules bind to RNA and help shape its structure. However, they suspected that polyamines must be playing other roles inside cells: they’re among the most abundant small molecules within cells, present at levels comparable to ATP, the molecule cells use as their energy currency.
“We’ve known that without polyamines, cells stop growing and dividing,” Jain says. “But their best-known function only requires a small fraction of the polyamine levels cells actually have.”
To uncover polyamines’ hidden function inside cells, the researchers used a large-scale genetic approach that allows them to screen the entire genome at once, rather than testing genes one-by-one, in order to find out which cellular processes are impacted when polyamine levels are changed within cells.
The screen revealed that when cells have reduced levels of polyamines, a protein called GPX4 becomes essential for survival. GPX4 is known to prevent harmful chemical reactions that damage the fatty molecules that make up cell membranes.
The team also found that cells with lower polyamine levels have higher amounts of another protein that acts as an iron sponge and keeps the metal in a mineralized form. Together, these findings led the researchers to hypothesize that polyamines might be helping keep iron in a safe, non-reactive state within cells.
To test this idea, they developed a new fluorescent sensor that would allow them to measure chemically reactive iron inside living cells. The new sensor causes living cells to glow based on the amount of chemically reactive iron they contain, allowing researchers to track any changes under a microscope in real-time.
The team paired the new iron sensor with another sensor they had previously developed that measures polyamine levels within cells. By employing them simultaneously, they observed a striking pattern: As polyamine levels dropped within cells, the amount of chemically reactive iron went up, offering new evidence that polyamines play a key role in preventing toxic iron build up inside cells.
Beyond answering a fundamental biological question, these findings could have implications for cancer treatment. Cancer cells often rely on high polyamine levels to support their rapid growth and division. However, cancer drugs designed to lower polyamine levels to stop cell division have had limited success.
“We saw that when polyamine levels fall, cells rely on GPX4 to protect themselves from iron toxicity,” says Sharma, who is also the first author of the study. “This could mean that combining drugs that lower polyamine levels with those that block GPX4 might be more effective for killing cancer cells than targeting either pathway alone.”
The discovery may also have implications beyond cancer. Mutations in genes that help move polyamines around cells are linked to a rare form of early-onset Parkinson’s disease, and scientists have long observed unusually high levels of iron in the brains of Parkinson’s patients.
While it is still unclear whether excess iron directly contributes to neuron death in Parkinson’s, the discovery that polyamines help buffer reactive iron inside cells offers a possible explanation for this link and opens new directions for future investigation.
In addition, the researchers expect the new iron sensor to be a valuable tool for other scientists. By allowing them to track chemically reactive iron inside living cells, it could power new discoveries in aging, cancer, and neurodegeneration.
“There are a lot of promising future directions for this work,” Jain says. “It’s exciting to think about how these tools and findings could help answer further questions about disease pathways and potentially help design better therapies.”
This work is supported by grants from the National Institutes of Health, Bumpus Foundation, and Pew Charitable Trusts. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH.
A new kind of aircraft departs an MIT classroom and arrives at an Ohio factoryElectra’s hybrid, fixed-wing aircraft, which grew out of a class project, could make travel easier for passengers taking shorter trips.A former MIT class project is becoming an $850 million effort to manufacture a new kind of aircraft in Ohio.
Electra began as an idea for a hybrid plane that could take off from shorter runways than traditional airplanes but have more range and speed than all-electric aircraft. Now, like other great MIT projects, it’s making an impact far beyond campus.
The company’s fixed-wing aircraft is designed to make travel easier, especially for people who don’t live in the immediate vicinity of a major airport. The plane features a smaller, more efficient engine than traditional planes, along with batteries to give it added power during takeoffs and landings.
With a range of around 1,200 miles and a cruising speed of around 200 miles per hour, the plane could improve the travel experience for many kinds of trips while cutting down on fuel use. And, given the much shorter runway needs and quieter operation than traditional planes, the plane can leverage unique access points such as barges, parking lots, and soccer fields to take off and land instead of traditional airports.
“Helping people travel between 50 and 250 miles is the sweet spot for this technology,” says Electra Director of Technology Development Chris Courtin SM ’19, PhD ’24. “This can be a better option than driving or commercial airlines for many kinds of trips. There’s a lot of people traveling in that range and a huge amount of friction in existing ground and air transport systems. This could be a big benefit to those people.”
Courtin has worked on the hybrid plane concept since its inception, first as part of a class project at MIT, then as a teacher’s assistant, and finally as part of his PhD thesis. The company was founded by another alumnus, John Langford ’79, SM ’83, SM ’85, PhD ’87, and counts two MIT professors — Mark Drela and John Hansman — as its founding technical advisors.
“The company has really benefited from a strong collaboration with MIT,” Courtin says. “One of the compelling things about MIT is it gives people space to marry the theoretical side with the practical side — to actually go build the airplane and see if people will buy it.”
Electra has already built and flown a two-seated version of its plane. Last month, the company announced an $850 million investment to scale production of its nine-passenger aircraft in Springfield and Clark County, Ohio. The investment, which is expected to create 1,975 new jobs, means Electra will be building the next chapter of aviation in the state where engine-powered human flight first began.
From concept to company
The origins of Electra date back to a 2017 project among graduate students in MIT class 16.886 (Air Transportation Systems Architecting). Electric vertical takeoff and landing (eVTOL) aircraft were garnering excitement at the time, and Courtin’s group wanted to compare that approach to alternative designs.
“It was an open-ended, project-based class where you look at developments in aerospace,” Courtin says. “My group realized short takeoff and landing aircraft had a lot of advantages over eVTOL for getting people where they wanted to go. We started exploring using the same technology — lightweight, electric motors suitable for aviation — to make a new aircraft, which we now call the ultra-short takeoff and landing aircraft.”
The idea was to use batteries and small electric motors to shorten the runway and landing space of a fixed-wing aircraft while leveraging blown wind to travel farther distances in the sky than would be possible with electric motors alone.
The concept was developed further in several senior design classes co-taught by Drela and Hansman, while Courtin served as a teacher’s assistant. In the classes, student collaborators built a subscale model of the aircraft to prove it would work, testing it in MIT’s Wright Brothers Wind Tunnel and in flight. Courtin went on to work on parts of the concept for his PhD.
In 2019, John Langford, who had been running the aircraft company Aurora Flight Sciences, which had recently been acquired by Boeing, got involved. Electra was officially formed that year.
As a first step, Electra’s team built the EL2, a two-seated version of its aircraft. That included designing and testing the hybrid propulsion system. The EL2 completed its first test flights in 2023 and has since completed over 200 flights.
The aircraft has a gas-powered generator located in its nose and two batteries under the floor, both of which feed the propellers during takeoff and landing. When cruising, the aircraft uses the generator, which can also charge the batteries.
“The gas generator is like a traditional turbine engine used in a conventional aircraft, only instead of driving a propeller or fan it drives an electric generator,” Courtin explains. “That feeds power to the eight motors on the wing. It allows you to have a smaller and more efficient engine because you can size it for cruising, not takeoff and landing conditions.”
The eight motors create a blown lift effect that allows the aircraft to take off and land in areas about the length of a soccer field, much shorter than the runways for conventional airplanes.
For travelers, “the big benefit is you can save a lot of time,” Courtin says. “You don’t need to go to an airport, and you don’t have to go to a train station.”
Operators could also maximize existing infrastructure at airports:
“If you’re three hours away from the nearest major airport, there’s a lot of friction in that,” Courtin says. “With Electra, we could fly you to the nearest major airport, and you don’t need to use a runway, so it doesn’t add to congestion at these very low-capacity places.”
Electra’s aircraft are also more affordable than traditional aircraft and far more quiet.
“The large number of propellers means you can make them much quieter than if you only had one or two,” Courtin explains. “That’s important because helicopters are restricted from operating in places they otherwise could because of the noise.”
Scaling up
Construction on Electra’s 96-acre Ohio manufacturing facility will begin next year. The facility’s initial phase will be capable of producing 400 of its nine-seat aircraft each year. The next phase will expand capacity to around 800 aircraft per year.
Electra’s team could see their aircraft shuttling people to major airports for longer trips or ultimately eliminating the need for conventional airports entirely.
“If you don’t have an existing airport, that’s a very difficult thing to build these days,” Courtin says. “But finding a soccer field-sized area is not hard, especially with our noise reductions.”
Electra’s team is also exploring applications around military logistics, cargo transport, and humanitarian missions.
For the passenger aircraft application, Electra’s team believes that as it scales production, it will be able to make the passenger aircraft accessible to a broad swath of travelers.
“If we can keep the fixed-wing design simplicity and make this large enough, then the per-seat cost could get to a range where a lot of people would have access to this,” Courtin says. “It wouldn’t just be a luxury product, so it could help a lot of people.”
The secret love life of the longfin squidMIT Sea Grant resident artist and acclaimed underwater photographer Keith Ellenbogen captures an intimate look at courtship and communication in a hidden spawning spectacle off Cape Cod.Squid have occupied New England’s maritime imagination for centuries, from fishermen’s tales of strange tentacled creatures to the widely publicized giant squid reports along North Atlantic coastlines in the 1800s. Today, we turn a curious eye toward the longfin inshore squid (Doryteuthis pealeii) — the “Boston squid” — which has long been an important part of regional commercial fisheries. These squid thrive in the emerald green depths off the coast of Massachusetts, where low visibility is characteristic of the turbid, nutrient-rich waters.
Keith Ellenbogen, MIT Sea Grant resident artist and acclaimed underwater photographer, knows these waters well. On a good day, he might have 20 feet of visibility beneath the surface. But even with the clearest conditions, these swift squid evaded Ellenbogen’s lens for months.
In 2023, over 2.85 million pounds of longfin squid — likely over 6 million individual squid — were landed commercially in Massachusetts, with a value exceeding $2.82 million. Consistently among the top 10 species landed commercially in Massachusetts, the longfin squid shares the ranks with the iconic American lobster, Atlantic surf clam, and sea scallop, underscoring its enduring significance in the state’s seafood industry.
In 2024, landings came in under 750,000 pounds, roughly a quarter of the previous year’s catch. Likewise, the spring 2024 trawl survey documented in the Massachusetts Division of Marine Fisheries Annual Report recorded a historic low in longfin squid biomass, following a record high in 2023.
But this drop, while significant, doesn’t necessarily spell trouble for the species. Longfin squid often show large fluctuations in abundance from year to year. Their short lifespan of about six to nine months, combined with their sensitivity to shifting ocean conditions, makes their population dynamics inherently unpredictable.
Kimberly Hyde, a biological oceanographer with the National Oceanic and Atmospheric Administration (NOAA)’s Northeast Fisheries Science Center (NEFSC), notes that NEFSC research scientists have expanded squid research over the past few years, including a two-year study on longfin squid to better understand their life history and track their maturity and readiness to spawn. Across the Northeast, scientists are also collaborating with the fishing industry through efforts including the Longfin Squid Biological Sampling Program (SQUIBS), Collaborative SQUid Size Monitoring (SQUISM), and the Squid-Squad, a highly interdisciplinary team of scientists, industry members, and managers with a common goal to improve squid science. Still, much of this cephalopod’s story remains hidden from sight.
After years of trying to find and photograph a squid spawning aggregation, Ellenbogen chartered a vessel and worked with a network of local fishermen to locate concentrations of squid beneath the surface. In New England’s emerald-green, nutrient-rich coastal waters, visibility was limited, and although he knew he was directly above the spawning grounds, finding a cluster of eggs and squid 30 to 40 feet below the surface was far from easy.
“As I descended through the emerald-green waters of Cape Cod, I couldn’t see anything at first,” Ellenbogen recalls. “I knew I was in the right area, but the seafloor seemed empty. Then I noticed a few faint shadows moving in the distance.”
As he swam closer, the scene slowly revealed itself.
“First came the squid, then the egg masses, and then hundreds more animals appearing out of the green water. Suddenly I found myself surrounded by squid flashing colors, courting, competing, and spawning,” Ellenbogen says. “It felt like being in a theater, watching a carefully choreographed performance unfold all around me.”
Dozens of squid hovered intently in a circle with arms and tentacles stretching toward the focus of attention: a large pale cluster of eggs fixed to a bed of slipper shells and fingerlike seaweed. Thousands of gelatinous, translucent egg capsules swayed softly in the current. Male and female pairs broke from the outer circle with ceremonial precision, darting inward to spawn. Their alienlike bodies pulsed and flickered with waves of color, from flares of rust-red, golden yellow, and iridescent pink to flashes of lightning white. Their brief lives had culminated here in this critical moment of coordination to give rise to the next generation.
Longfin squid live fast and die young, exhibiting incredible exponential growth throughout their lifespan of less than one year. They emerge from egg capsules as planktonic hatchlings — paralarvae — that already look like tiny 1.5 millimeter simplified versions of their adult form.
Still small but fast-growing, juveniles feast on planktonic prey in coastal, surface waters and move deeper in the water column as they grow larger, settling on a life closer to the seafloor. As natural-born ambush and pursuit predators, they begin hunting small crustaceans and other invertebrates — including other squid — with jet propulsion and 10 grasping arms and tentacles.
Like octopuses, squid have chromatophore organs, pigmented cells controlled by nerves and muscles through their central nervous system. Contraction or dilation of these sacs results in mesmerizing iridescence and color shifts. Their color-changing behavior serves several purposes, including camouflage, courtship, and communication through ancient visual language. And to add an extra layer of curiosity, squid themselves are effectively colorblind. Their eyes are well-adapted to detect contrast, brightness, movement, and even polarization, but not to perceive hues like we do.
According to a report from the NEFSC, longfin squid can reach sexual maturity at a mantle length of just 8 centimeters. Nearing adulthood, they migrate offshore to overwinter in deeper, warmer waters along the continental shelf. At night, they form large schools grouped by body size and move upward in the water column to feed. Growth remains rapid and temperature-dependent, with males growing faster and larger than females.
Longfin squid spawn year-round with seasonal and geographic peaks. In New England waters, spawning has been reported from May to August. Egg clusters, or mops, like the one Ellenbogen photographed, act like a hub. As reported by NOAA Fisheries, female squid lay fertilized egg capsules that contain about 150 to 200 eggs each in clusters attached to the ocean bottom. They return repeatedly to deposit multiple clutches of eggs over several weeks, with a typical female laying a total of 3,000 to 6,000 eggs.
Spawning typically occurs in seasonal pulses tied to water temperature and other conditions, sometimes triggering large spawning aggregations — dense gatherings of squid depositing and fertilizing eggs. Males and females gather in the spawning grounds, and density increases until individuals are constantly interacting.
But reproductive biology and behavior are complicated for longfin squid. The NEFSC report highlights unique behavior: Females can store sperm from spawning events for later use, and eggs in the same capsule from a single female may have multiple males from multiple spawning events.
Consort males, typically the larger males, pair up with a single female during spawning. They swim closely alongside her, often guarding her with their arms, and use their size to intimidate competition. Sneaker males, smaller unpaired squid, use stealth and speed to sneak into position with paired females. Males deposit bundles of spermatophores into the female’s mantle cavity or in a pouch located near her head.
The competition is guided by visual and chemical signals, including pheromones indicating reproductive readiness, rapid color and pattern changes, as well as strategic arm postures and whole-body displays. A 1999 paper published by the Marine Biological Laboratory catalogued 34 visual displays involving colors, brightness, spots, stripes, iridescence, and polarization signals, as well as 17 specific positions and movements used by squid on the spawning grounds.
Squid were seen flashing white as a signal to repel other squid. Squid displaying this component are almost always engaged in mate guarding, egg laying, or competitive confrontations. Like humans, female squid can blush, displaying a dark patch on one side of the mantle. But when a squid blushes, it functions as a repellent to courting males. And as captivating as these colorful displays can be, squid communication largely remains an encrypted secret to even the most curious scientists.
“Keith’s rare glimpse of squid in their natural environment beautifully bridges art and science, reminding us that we still have much to learn,” says Hyde, who has centered her research at NOAA on marine ecosystems and fisheries.
For most people, squid are known solely as seafood or as shadowy legends, chameleons of the sea. Yet each spring, beneath the cool waters of Cape Cod, millions of longfin squid gather in this remarkable reproductive event, a reminder of the rich biodiversity and productivity of Massachusetts marine ecosystems.
MIT Sea Grant works to support sustainable fisheries and to promote environmental education and stewardship of our coastal and ocean resources. As MIT Sea Grant’s resident artist, Keith Ellenbogen is working on a long-term project to document extraordinary species and ocean events that unfold just off our coast, revealing hidden moments that few have the opportunity to witness. The longfin squid is one of our region’s most valuable marine resources, and these images help reveal one of the most extraordinary events unfolding right off our coast.
Brain circuit keeps tabs on what just happened to aid judgment of what’s happening nowTo keep track of what’s going on in front of it, the brain relies not only on what it sees, but also a comparison with what it just saw. A new study pinpoints the circuit that provides that service.A brain must constantly cope with the highly variable, fast-paced nature of the world when trying to judge what’s going on around it. On one hand, it has to be open to whatever new sensory information may come its way, but on the other hand, just to keep up, it has to try to leverage prior experience to make predictions about what seems to be happening.
In a new study published in Science, MIT neuroscientists identify a circuit that links a sensory decision-making region with one that advises it on how much sensory information just changed.
“This circuit organizes a comparison between what has just happened versus what is happening now in the sensory world in a manner that can be used to act,” says study senior author Mriganka Sur, Newton Professor in The Picower Institute for Learning and Memory and MIT’s Department of Brain and Cognitive Sciences.
Study lead author Ning Leow Phd ’23, a former graduate student in Sur’s lab who is now a postdoc at A*STAR in Singapore, says the study in mice sheds light on closely analogous circuitry in humans, in which an area of the prefrontal cortex (the anterior cingulate cortex, or ACC) makes sensory decisions. The new study shows it bases those decisions on advice about immediate past history from an area of the thalamus called the pulvinar (though in mice, it’s called the lateral posterior thalamus, or LP).
“The brain does not evaluate each new event from scratch,” Leow says. “The pulvinar has traditionally been studied for its role in attention and filtering visual information, but we found that it was also important for comparing present information with the immediate past and highlighting meaningful changes to influence whether we maintain or update a decision.”
As part of Sur’s long-standing interest in how the brain’s cortex integrates sensory perception and learning to produce behavior, Leow and Sur began comprehensively mapping the copious inputs to the LP-ACC circuit, culminating in a paper in 2022. It was clear from that study how the circuit would seem well-positioned to help focus attention, which is what it was known for at the time.
But in thinking more deeply about what focused attention is for, and about how these well-connected regions seemed to sit at the center of not only attention but also perception and action, Sur and Leow hypothesized that they might also have a hand in guiding decisions based on sensory information. The new study presents multiple lines of evidence that it does.
The findings not only shed light on a fundamental function of the brain, Sur says, but could also be applicable to studies of autism, in which many patients show significant differences in the predictions they make about the sensory world. Often, this manifests as difficulty filtering out stimuli that neurotypical people are able to regard as recurring, and therefore mundane.
Which way?
To conduct the study, the researchers trained lab mice to play a video game in which dots on a screen would drift around, but at least some would move together in the same direction (left or right). In each trial, the mice had to discern that trend. From one trial to the next, then, the sensory cue could vary not only by the direction of movement, but also by how what proportion of dots were participating. For instance, on one trial maybe 64 percent of the dots would move left and on the next trial maybe 16 percent of the dots would move right. In this way, the researchers could measure a whole continuum of differences from one trial to the next.
Meanwhile, as mice played the game, the scientists used a two-photon microscope to record the activity of the LP-ACC circuit and the response of neurons in the ACC. In some experiments, they used a technique called optogenetics to artificially activate the circuit.
By tracking how mice performed the task trial after trial, the researchers were able to see that the mice indeed factored in not only what they were seeing in the moment, but also what they had just seen previously. For instance, when mice guessed right, they were very likely to repeat their guess if the new cue was very similar to the prior one, and very unlikely to if the cue was very different. But if they guessed wrong, then the opposite was true: They wouldn’t repeat that decision if the cue was similar to the last, but would if it looked very different.
Looking in the brain
Of course, behavioral observations only indicated that the mice indeed compared new cues to prior ones. Determining whether that was indeed because of the LP-ACC circuit required the researchers to use optogenetics to perturb it (by stimulating extra activity in the LP’s inputs into the ACC). For instance, optogenetic perturbation of the circuit in the left brain hemisphere made mice less likely to guess that dots were moving right, and perturbation in the right hemisphere made mice more likely to guess dots were moving to the right. But in both cases, the extent of these deviations from normal behavior was directly proportional to the difference between the current cue and the previous one. In other words, perturbing the circuit disrupted how mice used recent sensory history when evaluating new evidence, Leow says.
“That showed the pathway is causally involved in the comparison process that influences how current evidence is interpreted, rather than merely carrying the information,” Leow says.
Moreover, using the microscope imaging (which visualizes calcium levels in neurons, a close proxy of the electrical activity), the researchers extensively analyzed the activity patterns of the LP input into the ACC and how ACC neurons reacted to that input.
“The main takeaway is that the LP and ACC were performing different jobs,” Leow says. “The pulvinar doesn’t appear to be making the decision itself. Instead, it sends that history-referenced sensory comparison to the frontal cortex. The ACC then transforms that information into the neural activity that predicts the animal’s final choice.”
Essentially, the pulvinar advises the ACC on the degree of change so that the frontal cortex can consider whether it’s time to change a guess. After all, if a mouse is guessing right and little is changing, why not keep on trucking? But if there’s a big change, then it might make sense for the mouse to re-evaluate what it’s thinking.
It turns out, the brain has this dedicated circuit for doing so.
In addition to Leow and Sur, the paper’s other authors are Arundhati Natesan, Alexandria Barlowe, Sofie Ährlund-Richter, Tianyu (Cindy) Luo, and Mehrdad Jazayeri.
The National Institutes of Health, a MURI grant, the Simons Foundation Autism Research Initiative, A*STAR, and the Freedom Together Foundation funded the research.
Meteorite dust holds records of magnetism that may have helped form the sunThe discovery likely represents the earliest known evidence of a magnetic field in the infant solar system.Around 4.6 billion years ago, the solar system was little more than a giant ball of gas and dust. Over the next few million years, this “solar nebula” underwent a huge transformation, flattening into a disk of matter that then condensed to form the central sun and orbiting planets.
Scientists have assumed that the early solar system was shaped mainly through gravity. But a new study finds that magnetism also likely played a role.
MIT scientists have discovered records of ancient magnetism in the oldest samples of meteorites known today. The team analyzed microscopic grains embedded in a meteorite that was discovered in Antarctica in 2008. These grains, called calcium-aluminum-rich inclusions, or CAIs, originally formed during the solar system’s first 200,000 years, making the samples the oldest known solar system material.
The findings suggest that a magnetic field existed very early on, during the time of the solar nebula. The researchers estimate that this nebular magnetic field was stronger than Earth’s magnetic field today, and likely played a significant role in pulling together primordial matter to form the early sun.
“This transition, from a spherical cloud to a protoplanetary disk, is one of the most significant events in all of solar system history,” says Benjamin Weiss, the Robert R. Shrock Professor of Earth and Planetary Sciences at MIT. “It has long been theorized that gravity caused this, but our measurements show magnetism likely played a role.”
Weiss and his colleagues report their discovery in a paper appearing this week in the Proceedings of the National Academy of Sciences. The study’s MIT co-authors are first author Cauê Borlina PhD ’22, Elias Mansbach PhD ’24, and Nilanjan Chatterjee, along with Xue-Ning Bai of Tsinghua University, Po-Yen Tung and Richard Harrison of Cambridge University, François Tissot of Caltech, and Kevin McKeegan of the University of California at Los Angeles.
Spinning grains
Magnetic fields are generated by matter that is electrically charged and moving around. In the very early solar system, the collapsing cloud of gas and dust could have whipped up a plasma of charged particles. As these charges spun through the developing disk, they could have produced and sustained a magnetic field.
If this were the case, Weiss and his colleagues reasoned that such early magnetism would have affected material in the disk. As this material condensed, tiny magnetic minerals would have locked in the strength of the magnetic field, preserving its original intensity over billions of years. If these minerals somehow made it to Earth for scientists to measure, their “remanent magnetization” would be evidence that a magnetic field indeed existed and could have played a role in shaping the solar system.
In fact, the team has previously discovered evidence of a magnetic field, as early as 2 million years into the solar system’s formation. At that time, scientists believe that the sun was already in place, and that the planets were just starting to come together. Thus, the magnetic field Weiss measured likely played a part in the formation of the early planets.
“Nowadays people don’t debate whether magnetism is present when planets are forming. But the debate is around the very early solar system, before planets are forming, when there’s just a disk,” says Borlina, who led the new study as an MIT graduate student and is now an assistant professor at Purdue University. “That’s where the debate still resides, and that’s where we’re operating now.”
Magnetic records
For their new study, the team investigated whether a magnetic field could have existed even earlier in the solar system, when the sun was first coming together. They analyzed samples of DOM 08006, a meteorite that was discovered in 2008 in Dominion Range, a mountain range located along the East Antarctic Ice Sheet. Since it was first recovered, the meteorite has been studied extensively.
DOM 08006 is one of the most primitive meteorites discovered, and it contains mineral grains that date back to the earliest stages of solar system development, possibly even before the sun was formed. Surprisingly, the meteorite has managed to keep its original composition and minerals.
“Other meteorites went through many different processes over this 4.5 billion year history,” Weiss says. “They were formed in the solar nebula, then added to bodies with water, then got destroyed, moved to the asteroid belt, and then landed here. But somehow, DOM has experienced less alteration than any other meteorite.”
If the early solar system did harbor a magnetic field, records of that field could still be in place in some of DOM’s ancient mineral grains, including CAIs.
“We know they are the oldest things we have of the early solar system,” Borlina says. “But CAI’s are very complex and are not all the same, even within a 1-millimeter piece of the meteorite. So we have to carefully identify what types they are.”
From small samples of the parent meteorite, the team isolated tiny grains and identified a handful of CAIs that contained inherently magnetic minerals such as iron. They then put the grains through a series of tests to measure any magnetism they still carry.
The team identified traces of a magnetic field in the ancient grains. Based on their measurements, they estimate that a magnetic field, of about 150 to 600 microteslas, existed in the early solar system. This field strength is about three to 12 times greater than the Earth’s magnetic field today.
“We think these kinds of magnetic fields were helping to move gas from the protoplanetary disk, in toward this central star, the sun,” Borlina says. “Gravity is also playing a role. But we are now showing that, if you want to fully understand how the sun and planets formed, you should include magnetic fields in the ingredients that make them.”
This research was supported, in part, by NASA.
Generating scenarios for extreme events, without extreme dataA new algorithm learns to anticipate the unprecedented scenarios that critical infrastructure and global supply chains are least prepared for.Can a city’s seawall stand up to a blockbuster storm? Will a region’s power grid hold against record-breaking heat? And can a town’s fire-fighting resources contain a major wildfire?
To answer these questions, communities will first need to know how such extreme events could unfold. How far is a wildfire likely to spread? How much of a region might a storm impact? How long could a heat wave last?
But extreme events are notoriously difficult to anticipate. By their nature, they are outliers. In the history of record keeping, extreme events are sporadic and rare. Yet most methods that assess a region’s risk depend on extreme events of the past to characterize even more extreme, worst-case scenarios in the future.
Now, MIT engineers have developed a tool that generates plausible extreme events and worst-case scenarios, and maps their characteristics, such as an extreme storm’s likely duration, intensity, and area of impact. The key to their method is that it does not need to know about previous extreme events in order to generate plausible future extreme events.
Instead, the method, in the form of a machine-learning algorithm, learns from a dataset, such as a region’s daily weather records and maps. This record may or may not contain past extreme deviations, such as record-setting heat or rain. The team’s algorithm takes a statistical approach to learn from the available data, to exclude implausible weather scenarios. The method then generates plausible extreme events that are likely to occur in a region with a given frequency (such as once every 100 years), and projects how those extreme events might look in terms of their size, intensity, and duration.
“We are trying to model extreme, unprecedented events that no one has seen before, that are not in the dataset,” says Kai Chang, an MIT graduate student in mechanical engineering and affiliate of the MIT Center for Computational Science and Engineering.
“An event like Hurricane Katrina is something that happens every 30 to 40 years,” adds Themis Sapsis, the William I. Koch Professor of Mechanical and Ocean Engineering at MIT, a core member of the Center for Computational Science and Engineering, and an affiliate of the MIT Institute for Data, Systems, and Society. “What will be the Katrina that happens every 100 years? How bad will it be? That’s exactly what we’re trying to quantify, to help planners prepare for plausible extreme scenarios.”
Beyond weather events, the approach, which the team has dubbed Extreme Event Aware, or “η-learning,” can be applied to other fields, such as robotic navigation and financial markets.
“Financial market crashes are extreme events that are a complicated combination of things, involving many different sectors,” Chang says. “What is the interaction that leads to a market crash? That is something that this method could explore.”
Sapsis and Chang detail their new method in an open-access paper that appeared on Aug. 20 in the journal Nature Communications.
“Riskier than everything”
To estimate a region’s risk of an extreme weather event, planners, policymakers, and insurance companies typically ask questions such as “What does a once-every-100-year storm look like for New York City?” For answers, they use computer simulations that must be trained on data that includes extreme, once-in-a-century events, in order to learn the conditions leading up to those events and generate scenarios of how those events might look in the future.
“These methods assume there are very disastrous events that we have seen in the dataset, and they build a method to either estimate the risk of those events, or they try to predict exactly the events that have happened,” Chang says. “We are trying to see: What do unprecedented extreme events look like that are riskier than everything that has happened before and yet are still plausible?”
For example, if the most extreme rainfall measurement ever recorded in New York City is 200 millimeters, what kind of storm would produce an even more extreme measurement, of 300 millimeters? Such an event has never been recorded before and yet could still be plausible. City planners would want to know where such a storm would hit, how big an area it would cover, and how intense it would be. A simulation of the storm could help them assess infrastructure and plan reinforcements.
“We want to predict maps of these worst-case scenarios,” Sapsis says. “There is no method that does this efficiently to predict events that happen rarely.”
Extreme learning
The team’s new algorithm generates plausible, unprecedented extreme scenarios, without needing to train on previous extreme event data. To do so, the algorithm combines and learns statistics, or probabilities, about the relationships between two types of data: point statistics and spatial maps.
To demonstrate, the researchers applied the method to generate maps of future extreme precipitation events over the continental United States. The researchers began with 25 years of hourly precipitation maps, which they pooled into daily maps. From the full record, they computed point statistics describing how often the maximum rainfall across a map reached a given level. They then trained the algorithm on paired low- and high-resolution spatial maps from just the first six months of the record, which contained few or no examples of the most extreme rainfall levels.
From these data, the algorithm learned how patterns in low-resolution maps correspond to detailed, high-resolution precipitation maps. It then used the point statistics to constrain the rainfall extremes represented in those maps. This combination enables the algorithm to generate plausible spatial patterns for events more extreme than those represented in the training data — for instance, the possible locations, sizes, and intensities of a once-in-a-century rainfall event with a maximum of 300 millimeters.
A user can prompt the trained algorithm with a question such as, “What could a once-in-a-century storm look like in New York City?” The algorithm then generates maps of statistically plausible storms that are likely to occur with that frequency, including characteristics such as the storm’s size, area of coverage, and intensity of rainfall.
“Someone can say, ‘I’m interested in building things to withstand the risk of an event that happens every 100 years,’” Chang says. “What we can do then is produce thousands of possible realizations that will happen with this sort of rare frequency.”
As long as relevant point statistics and spatial data are available, the method could be applied to visualize other unprecedented events such as extreme floods and wildfires.
“Extreme events have become a strategic concern, not just an environmental one — we’ve optimized global systems for efficiency, and the price of that efficiency is that there’s very little slack left anywhere. A single extreme event propagates through supply chains, energy markets, and food systems in weeks,” Sapsis says. “Being able to put a probability on an event that hasn’t happened yet is now a question of national and economic resilience.”
This research was supported, in part, by a Vannevar Bush Faculty Fellowship and the U.S. Air Force Office of Scientific Research.
Language skills stay strong in older adults, even while other cognitive abilities declineMIT researchers find that activity in the brain’s language network is nearly identical in young and old people.As people age, many cognitive functions tend to decline. Brain scanning studies have revealed corresponding changes in the function of a brain network that is involved in many of these cognitive functions, including working memory and problem-solving.
When it comes to language skills, however, the picture is different. Unless impaired by a stroke or dementia, most older people retain their language skills and may even improve them as they steadily gain vocabulary throughout their lives.
A new brain imaging study from an MIT-Boston University collaboration now reveals the neural activity underlying this observation. The researchers found that in older adults, activity of the language processing network is nearly identical to that seen in the brains of younger adults during language tasks.
In contrast, the researchers found that activation patterns in the multiple demand network, a brain system involved in executive control tasks such as decision-making, were very different in older and younger adults.
“In the language network, we couldn’t find any differences between older and younger groups. In contrast, the executive system showed decline across almost all of the measures. The network synchronization declined in older adults, the extent of activation was reduced, and the magnitude of activation was reduced as well,” says Anne Billot, one of the lead authors of the new study, who carried out this work while doing her PhD at BU and is now a postdoc at Harvard University.
The findings suggest that parts of the brain that are specialized for specific functions, such as language processing, may be more resilient to aging than the multiple demand network, a more general-purpose network that has greater flexibility in its function, the researchers say.
Former MIT research assistant Niharika Jhingan is also a lead author of the study, which appears today in Nature Communications. Evelina Fedorenko, an MIT associate professor of brain and cognitive sciences and member of MIT’s McGovern Institute for Brain Research, and Swathi Kiran, the James and Cecilia Tse Ying Professor in Neurorehabilitation at BU, are the paper’s senior co-authors.
The resilience of language
To study the effects of aging on the brain, the researchers looked at two groups of people, ages 17-39 and 41-80. Based on previous studies, they expected that the multiple demand network, which includes several regions in the frontal and parietal lobes of the brain, would look different in the brains of older people.
“It’s well known that executive functions, such as attention, working memory, and cognitive control, tend to decline with age. And it’s also known that in opposition to that, language skills typically tend to remain quite stable or even improve with age,” Billot says. “These two types of functions really go in opposite directions in healthy aging. In terms of behavior, that’s quite well-established, and we wanted to see if that was also the case in the brain.”
In previous studies of the multiple demand network, scientists have found that as people age network activity becomes less synchronized. Some neuroscientists have hypothesized that this may also happen in the language network, but studies haven’t found definitive evidence for this.
The MIT researchers were able to look at both networks by designing tasks that elicit responses primarily in either the language network or the multiple demand network. This allowed them to identify, for each participant, the brain areas that belong to each network.
During a spatial memory task — remembering the location of squares in a grid — the researchers confirmed that the multiple demand network showed altered activity in older adults. Compared to the younger subjects, their networks were smaller and less well-synchronized, and the overall activation level was weaker.
To identify the language network, the researchers had participants listen to stories and read sentences. They found that in both groups, brain activity in response to language showed similar levels and spatial distribution across the network.
They also found that younger and older subjects showed similar brain responses when they encountered an unfamiliar word or an unusual grammatical construction.
“We have previously used similar kinds of materials to show that young adults show strong sensitivity to these points of linguistic difficulty: activity in the language areas goes up. Here we found that in older adults, you also see this sensitivity, which suggests that there’s nothing fundamentally different about how they process language,” Fedorenko says.
A language boost
The researchers also showed that in older people, the language network did not show any signs of becoming less synchronized. Additionally, the network did not show signs that it was blurring together with the multiple demand network, as some neuroscientists have hypothesized might happen.
While this study did not evaluate language ability, other studies have shown that not only do language skills not decline with age, for some people, their language processing improves in older age. This might be because vocabulary and reading skill can continually grow over time, the researchers say.
“Vocabulary keeps increasing as long as people have been measuring, which makes sense. People get exposed to more and more language, and older people sometimes start reading more, so they get an extra boost — it’s like a large language model trained on increasingly more data,” Fedorenko says.
Given these findings, one possible generalization is that parts of the brain that are specialized for particular functions such as language may be less susceptible to age-related decline than the multiple demand network. That network is unique in its ability to give the human brain the flexibility to learn new skills and adapt to new situations.
“The multiple demand network is a different system in the sense that it’s not accumulating knowledge over time. It’s more like a flexible resource that you can deploy in all sorts of ways. And somehow that’s the thing that is more vulnerable to aging,” Fedorenko says. “Why it’s so vulnerable — that is a very good question.”
The research was funded by the National Institute on Deafness and Other Communication Disorders, as well as MIT’s McGovern Institute, Simons Center for the Social Brain, Poitras Center for Psychiatric Disorders Research, and Quest for Intelligence.
The importance of indoor airflow patterns in spreading airborne diseaseResearchers explore how a key factor can mitigate or promote tuberculosis transmission.Tuberculosis (TB) is a leading cause of infectious disease deaths, claiming over 1 million lives every year. It spreads through the air when an infected person coughs, sneezes, or exhales, and drug-resistant strains and asymptomatic spreading are growing concerns. Curbing TB transmission is an urgent public health challenge, yet scientists still don’t understand how airflow and other environmental factors influence that spread.
One problem is that studies of infectious disease transmission have focused mainly on population-level assessments or individual immune responses. But understanding how airflow and mixing influence transmission in indoor spaces requires expertise in fluid physics and computational modeling.
An interdisciplinary team including researchers at MIT and the University of Texas Southwestern Medical Center has now combined animal transmission experiments with quantitative particle tracking and flow modeling to understand how some lab-based environments can promote the spread of respiratory infectious diseases such as TB, while others mitigate that spread.
A key factor in predicting infectious transmission was not just the total ventilation rate but, more importantly, the local pattern of airflow driven by the design — such as air leakage, inflow and outflow locations, and forces created by an infected individual.
“The local airflow patterns turn out to be pivotal,” says Lydia Bourouiba, the Japan Steel Industry Chair Professor at MIT and faculty lead of the Fluid Dynamics of Disease Transmission Laboratory, part of the Fluids and Health Network within the Institute for Medical Engineering and Science (IMES). “Our team’s findings provide some of the clearest evidence I’m aware of showing the importance of accounting for [airflow] inhomogeneity and its effects when designing for airflow detailed patterns. This insight is critical when building or retrofitting an indoor space to mitigate airborne transmission, or when designing an airborne transmission study.”
The research is an important step toward connecting laboratory infectious disease studies with how people spread such diseases in the real world. The team hopes their insights can extend beyond their model system and show the importance of flow physics in building designs to prevent the spread of airborne diseases indoors.
“Despite recent pandemics and epidemics, there is still resistance to incorporating airflow in routine infectious disease prevention tools,” Bourouiba says. “Infrastructure could be retrofitted at relatively low cost, but the paucity and difficulty of gathering direct evidence prevents broader adoption of flow physics as a tool for indoor health. This study helps provide such evidence.”
Joining Bourouiba on a paper about the work are Yash Kulkarni, a postdoc at IMES, who led the fluid and aerosol physics components; Kubra Naqvi, lead author and a postdoc at UT Southwestern; Michael Shiloh, a professor at UT Southwestern, who led the multiyear effort to reestablish a classic tuberculosis transmission model; Hui Ouyang, an assistant professor of aerosol engineering at UT Dallas; Yuhui Guo, Deepak Sapkota, and Arabella Martin, all UT Southwestern PhD students; Pei Lu and Victoria Ektnitphong, research associates at UT Southwestern; Shibo Wang, a University of Minnesota researcher; Beatriz Dias, a UT Southwestern instructor; Bret Evers, an associate professor at UT Southwestern; and Lenette Lu, assistant professor at UT Southwestern.
Opening the black box
When people exhale, talk, cough, or sneeze, tiny microdroplets and bioaerosols launch from their mouths, carried forward by a cloud. If infected by a respiratory disease, these bioaerosols can contain pathogens that can infect others. Disease transmission depends on pathogen survival in the air, which is influenced by temperature, humidity, and ventilation.
In 1882, German physician and microbiologist Robert Koch first established an animal model for the study of tuberculosis pathogenesis. Decades later, researchers demonstrated airborne transmission of tuberculosis between people and animals.
These early experiments have proven difficult to replicate in today’s modern, biosafety-grade facilities. This new study reveals the difficulty comes from stringent containment and ventilation requirements, which can dramatically influence airflow in experiments.
“Host-to-host transmission is an obligatory evolutionary phase of respiratory pathogens, yet it has been considered too intractable or complex to be amenable to systematic investigation, hence is commonly relegated to a black box. Our work opens that black box,” says Bourouiba, who is professor in MIT’s departments of Mechanical and Civil and Environmental Engineering, and an IMES core faculty member.
To quantify how local airflow patterns impact infectious disease transmission, the researchers redesigned and modelled the early studies for modern high-containment lab facilities — including their seal, inflow, outflow, and exhaust pathways — and quantified particle and bacteria-laden particle release and dispersal. They released tracer particles and bacteria into a compartment and modelled recovery from air sampled on the other side under differing airflow rates, designs, and leak configurations.
The MIT team carried out computations, benchmarked against particle release experiments. The results revealed how important seemingly small details such as leakage paths could be.
“Even a small leak could short-circuit the airflow by drawing fresh air directly toward the exhaust, rather than drawing contaminated air across the containment chambers,” says Kulkarni.
Advancing TB research
To date, uneven indoor airflow patterns have not been fully harnessed as part of a risk mitigation strategy.
“By systematically defining how airflow and design influence biological exposure, we were ultimately able to restore transmission and create a system that can now be used to ask fundamental questions about the bacterial, host, and environmental factors that determine tuberculosis spread,” says Naqvi.
“I began working to reestablish this seminal TB animal transmission model nearly 10 years ago, and it proved far more challenging than I anticipated,” says Shiloh. “I hope this work serves as a reminder that meaningful scientific advances often require patience and perseverance.”
“This work illustrates how crucial it is to support synergistic collaborations integrating complementary disciplines to tackle research bottlenecks — and to standardize reporting norms across laboratories,” Bourouiba says. “If different labs have varying airflow patterns from uncontrolled leaks or seal details, that physical variability can overwhelm the biological signals researchers seek. Beyond its foundational impact for TB transmission studies, our work shows that opening the black box of transmission provides mechanistic insights: Detailed airflow pattern control can enhance or mitigate airborne transmission — making it exploitable as a prevention measure in crowded gathering spaces.”
This work was supported, in part, by the National Institutes of Health, the National Science Foundation, the Burroughs Wellcome Fund, MathWorks, and the Translational Research Institute for Space Health.
MIT engineers design a better controller for operating construction diggersThe new, more intuitive system could speed up the training process for excavator operators.Anyone who’s ever wrestled with a claw machine at an arcade can appreciate the difficulty in pulling and pushing on joysticks, in just the right way, to get a mechanical arm to scoop up that one special toy. Coordinating the joysticks and connecting their movement to the claw’s motion is a type of “mental mapping” that is not immediately intuitive. (And it’s what arcade owners depend on to bring players back, again and again).
In fact, the mechanics of a claw machine are broadly similar to driving an excavator: An operator uses joysticks to control the digger’s boom, arm, and bucket, and the direction of its cab. But an excavator’s maneuvers are far more complex than anything an arcade claw can do. Operators must learn more complicated mental maps to direct a digger to move rocks, grade soil, clear debris, and dig foundations, among other essential on-site jobs. Indeed, it can often take years for operators to build up expertise in maneuvering the heavy machines.
MIT engineers are looking to shorten the learning curve for excavator operators with a new training interface. Instead of using joysticks, the team has designed a more intuitive controller, which itself resembles a miniature excavator’s arm and bucket. Trainees grasp the device and use their arm and hand to make it move the way an excavator does. A digital excavator projected on an immersive six-screen display mirrors the trainee’s movements in a virtual environment.
“This is a more intuitive way to command the machine,” says Hermano Krebs, principal research scientist in MIT’s Department of Mechanical Engineering. “With this new interface, we can eliminate a lot of the mental maps that an operator would need to build in order to operate an excavator.”
Krebs sees the interface as a faster way to train excavator operators, as well as a new way to physically operate the machines, both on-site and remotely.
“Instead of having joysticks, you might have this miniature arm on the side, where the operator would place their own arm, kind of like an exoskeleton, which would allow them to operate the excavator in the cab,” Krebs says. “If work has to be done in a difficult or unsafe environment, you could have an operator sitting off-site in a trailer and using this arm to remotely tele-operate the excavator.”
The team reports its open-access results this week in the Journal of Computing and Civil Engineering. MIT co-authors include Moises Alencastre-Miranda, Joao Buzzatto, and Eran Beeri Bamani, along with collaborators from Sumitomo Heavy Industries, an industrial machinery manufacturer based in Japan.
A machine mimic
At MIT, Krebs’ group works on human-robot interactions, with a longtime focus on physical rehabilitation. Through this work, the team has accumulated knowledge about the ways in which humans control their limbs and how they can most intuitively interact with machines.
In 2018, Krebs struck up a collaboration with researchers at Sumitomo Heavy Industries, who were looking for a faster way to train excavator operators. They noted that in Japan, the population of heavy machinery operators is aging rapidly; training their replacements takes time.
Operators typically learn by driving actual excavators on a controlled driving course. As they operate the machine, novices must learn to relate the actions of the excavator’s joysticks with the movements of the arm, bucket, and cab. Coordinating these actions to carry out actual tasks adds another level of complexity that can take months to years to master.
The team reasoned that if they could eliminate the need for this mental map, they might significantly shorten the training process. To do so, they looked for a more natural way to control the machine, as an alternative to the traditional joysticks. They soon landed on the mechanical arm design, reasoning that the physical resemblance to the digger’s own arm and bucket could enable operators to mimic and control the excavator’s movements directly, without much mental translation.
Over the next few years, the researchers worked to build the mechanical arm, along with the software to pair its movements with a virtual simulation of an excavator. The combination of the mechanical arm and the virtual simulator constitutes a new training and control platform for digger operators, which the team has named the “World-Space Interface.”
“‘World-space’ refers to everything in the world that is outside of yourself, or in this case, outside of the excavator’s cab,” Krebs explains. “Normally, operators have to build a mental map of how to manipulate things in the world-space. But now, we can just mime picking up rocks or dirt, and the computer will do that translation to the world-space for us.”
Construction on day one
For their new study, the team ran training experiments with volunteers who used the World-Space Interface (WSI) as well as a more traditional, joystick-based excavator simulator. The researchers developed virtual simulations of 15 realistic excavation environments, including construction sites, highways, forest roads, riverbanks, mining areas, and urban and rural settings. Each virtual environment was associated with various excavation tasks, such as scooping and dumping sand or gravel, digging and grading trenches, clearing debris from roads, removing tree branches from water edges, and breaking up rocks.
The team designed the experiment to resemble the tasks that an operator typically performs during a weeklong excavator driving course. For one hour each day for seven days, volunteers — both expert and novice — operated the WSI and the joystick counterpart, training on tasks with increasing difficulty.
The researchers then compared the volunteers’ performance before and after the training period. For the joystick simulator, they found that novices were consistently worse than experts, though they did improve over the training period. In comparison, the team found that with the new World-Space Interface, novices were just as good as experts from the start.
“In this case, joysticks are a non-intuitive way to control and coordinate the machine,” says study co-author and MIT postdoc Joao Buzzatto. “This is the first interface that does not require me to command the excavator with joysticks.”
The team is now working to add haptics, or feeling to the WSI’s physical arm. The idea is that, as an operator uses the arm to mime an action such as picking up a pile of rocks, the arm will generate a force in response, as if the operator can feel the heaviness of the rocks, as confirmation that the excavator is indeed picking them up.
“Haptics would make this an even more intuitive system,” says co-author and visiting engineer Solmon Jeong.
The team says the new training interface can be a more natural alternative to excavator simulators that the construction industry is currently exploring. Companies such as Caterpillar, Hyundai, and Komatsu are developing virtual simulators, both to help train operators before they go on-site, and to one day remotely control excavators from a distance. However, these simulators are largely based on traditional joystick controllers that still take time to learn.
If the team’s new arm-and-bucket controller were incorporated, as an appendage in an excavator cab, or in a virtual, teleoperational simulator, the researchers envision that even first-time operators could get to work, from day one.
This research was supported, in part, by Sumitomo Heavy Industries.
Securing wireless communication in next-generation devicesA new, scalable technique could enable powerful radars and sensors based on quantum technology that works at room temperature.MIT researchers have overcome a major challenge holding back the real-world deployment of microwave quantum technologies for advanced signal processing and secure communications.
The team developed a scalable platform that generates pairs of highly correlated radio frequency waves, without the need for bulky and expensive cooling equipment. In quantum technologies, these linked radio waves can be used for noise-resilient communication or high-precision radar and sensing. However, they’re usually only generated in research labs, under extremely cold conditions.
The MIT researchers fabricated a small, electronic device that can generate the same type of highly correlated signals at room temperature.
The device incorporates a magnetic film, which interacts with microwave energy inside a metal cavity to split an incoming signal into two linked output signals. The researchers used the device to demonstrate secure communications by encoding information in a signal that could only be recovered using its partner signal.
“We’ve shown how the quantum properties of magnets can be leveraged to realize new communication and detection technologies. I hope our demonstration of this platform will enable further development of room-temperature quantum simulators, which have huge potential to enable many future discoveries,” says Qiuyuan Wang, an electrical engineering and computer science (EECS) graduate student and lead author of a paper on this technique.
Wang is joined on the paper by Aravind Karthigeyan, a graduate student at the University of Illinois at Urbana-Champaign; Chung-Tao Chou, an MIT postdoc; and senior author Luqiao Liu, an associate professor in EECS and a member of the Research Laboratory of Electronics. The research appears today in Nature Electronics.
Synchronized signals
Microwave photons are fundamental particles that form the signals used for wireless communication and sensing.
Scientists can split one microwave photon into two tightly correlated photons using a device called a Josephson junction, which is an element of a superconducting circuit. These linked microwave photons can be used in applications like secure communications or high-performance radar systems that can detect extremely faint signals.
To enable secure communications using these correlated signals, engineers could design electronic devices that encode data in one signal by altering the signal’s properties, such that the information could only be decoded at the other end of the transmission using the matching signal. But to operate effectively, superconducting circuits must be kept at temperatures below 273 degrees Celsius, usually inside a bulky, expensive, and energy-intensive cryostat machine.
While pursuing a different line of research, the scientists in Liu’s group realized they could generate the same highly correlated microwave signals using magnets instead of cryogenically cooled superconducting circuits.
By putting a magnetic film into a microwave resonator, which is a metal cavity that traps electromagnetic energy, they could split one incoming microwave photon into a pair of perfectly synchronized signals with distinct frequencies, at room temperature.
“On its own, each signal looks random, but their phase relationship remains strongly correlated,” Wang explains.
Their device relies on magnons, which are tiny packets of magnetic energy. Typically, pumping microwave photons into a magnetic system generates a pair of correlated magnons with the same frequency.
Even though both magnons are correlated, because they have the same frequency, scientists can’t separate them. They would need to separate the magnons to use one signal for transmission and the other for detection in secure communications.
A hybrid system
By coupling a magnetic film with a microwave resonator and carefully controlling the energy they pump into the device, the researchers could form hybrid magnon-photon waves. These hybrid waves output a pair of synchronized signals with distinct microwave frequencies.
The signals remain strongly correlated, but since the frequencies are always different and random, an attacker can’t recover the information encoded in one signal without having the matching one to use as a key.
The researchers demonstrated this by encoding a small image in the frequency of one microwave signal. They successfully decoded the signal and extracted the image using its partner.
“Magnonic systems exhibit a remarkably rich range of nonlinear dynamics, but these nonlinearities have not yet been harnessed for practical applications as extensively as those in nonlinear optics and other dynamical systems. In this work, we address one important challenge: the spectral overlap between a pair of ‘twin’ magnons generated by the same pump photon. By using the level repulsion arising from coupling between magnons and microwave photons, we were able to separate the two magnons in frequency,” says Liu. “We believe this demonstration could provide a foundation for technologies such as quantum radar, secure communications, and quantum-limited sensing, all of which rely on correlated — and ultimately entangled — microwave sources.”
This hybrid magnon-microwave system could also be used in noise-resilient communication by enabling the receiver to decode a message that has been garbled by random data that interfere with the transmission.
Correlated microwave signals are also a key element of a quantum simulator, which is a device that can emulate the complex behavior and interactions of subatomic particles that classical computers can’t handle. Scientists are developing quantum simulators to discover new drugs and materials.
By generating correlated signals at room temperature, this new technique can improve the scalability and reduce the costs of quantum simulation. In the future, the researchers want to develop a scalable architecture for their platform, moving it one step closer to real-world deployment. They also want to explore additional applications for the process and use their platform to study the underlying physics of correlated microwave signals.
“The creation of a non-degenerate parametric magnon-polariton platform marks an important milestone for cavity magnonics, extending the field beyond coherent microwave generation to the production of multichannel correlated microwave photons,” says Can-Ming Hu, a distinguished profess or physics and astronomy at the University of Manitoba in Canada, who was not involved with this paper. “This breakthrough will broadly impact secure microwave communications, hardware random number generation, correlation-based signal processing, and intelligent microwave sensing — all operating within the classical regime at room temperature. Looking ahead, this platform could well be remembered as the starting point for realizing quantum-inspired microwave sensing and communication technologies based on nonlinear cavity magnonics.”
This research was supported, in part, by the National Science Foundation and the U.S. Department of Energy.
Cell-preservation technique could make CAR-T cell therapy more accessibleMIT researchers’ approach, which uses naturally occurring sugars as antifreeze, could make it easier for hospitals to deploy this type of cancer treatment.Immune cells that are engineered to attack cancer cells, known as CAR-T cells, are used to treat some types of blood cancer. However, only about 5 percent of hospitals in the United States have the ability to generate and deliver CAR-T cells to patients. For many patients, this means the cells need to be frozen and shipped long-distance.
To help make this type of therapy accessible to more people, researchers at MIT have developed a new way to protect the cells from damage that can occur when they are frozen for storage and shipment. Their technique significantly reduces the use of a chemical preservative that is now used to protect the cells, which should make it easier for more hospitals to provide this treatment option to patients.
Instead of treating the cells with a cryoprotective chemical that has to be removed before treatment, the researchers were able to preserve them using a nontoxic antifreeze sugar.
“With this approach, you could theoretically just thaw the cells and then inject them, without any extra processing steps. We think that could allow a lot more cancer treatment centers to be able to give CAR-T cell therapy,” says Ana Jaklenec, a principal investigator in MIT’s Koch Institute for Integrative Cancer Research and one of the lead authors of the study, which appears this week in Trends in Biotechnology.
In the study, the researchers showed that cells preserved using this process had higher survival rates and could be successfully used to treat lymphoma and glioblastoma in mice.
Robert Langer, the David H. Koch Institute Professor at MIT, is also a senior author of the paper. MIT postdocs Amy Lee and Khanh Tran are the paper’s lead authors.
Preserving cells
To make CAR-T cells, doctors isolate T cells from patient blood samples. These cells are then engineered to express a protein called chimeric antigen receptor (CAR), which can be designed to target specific proteins found on cancer cells.
Then, the cells spend several weeks proliferating until there are enough to transfuse back into the patient. A small number of hospitals are equipped to generate and administer these cells, but most CAR-T cells are generated at centralized lab facilities. Once ready, these cells are frozen and shipped to a hospital or cancer treatment center.
To protect the cells from ice crystals that can damage their membranes, the cells are treated with a chemical called dimethyl sulfoxide (DMSO), which prevents ice crystal formation. This compound must be removed before the cells are transfused, but most hospitals don’t have the expertise to do this, which limits their ability to provide CAR-T cell treatment.
The process of removing DMSO can also harm cells, reducing the number of CAR-T cells that are viable and effective. In the new study, the MIT team wanted to find a way to reduce or eliminate DMSO from the process, which could make it easier for these cells to reach more patients.
“We looked at this cell-manufacturing process to see if there are ways to improve it, to increase the efficacy and hopefully eventually get to the point where these cells can be easily distributed to treatment centers,” Jaklenec says. “Our goal was to eliminate adding this chemical and really focus on safe excipients like sugars.”
The researchers employed two sugars that scientists have previously used to help cells survive cold temperatures. These sugars — trehalose and sucrose — help cells to naturally combat cold by protecting proteins from denaturation and preventing the formation of ice crystals. This antifreeze mechanism is found in many Arctic organisms, such as North American wood frogs, and helps them to survive extreme subzero temperatures.
To get sugar molecules into the cells, the researchers used a technique called electroporation. By applying a small electrical current to the cells, they can briefly create holes in the cell membrane, allowing large molecules such as sugars to pass through. They found that they still needed to add a small amount of DMSO, but not enough that it had to be removed later.
“We believe that our cryopreservation strategy can truly improve the cell therapeutic accessibility because with our strategy, you don’t need to remove the cryoprotectants. You could use the cells upon thawing,” Lee says.
More effective therapy
The researchers tested this technique on CAR-T cells as well as mesenchymal stem cells, which can differentiate into many other cell types and hold potential for use in regenerative medicine. For both types of cells, a higher percentage of the cells survived the freezing and thawing process when sugars were used as the main cryoprotectant instead of DMSO.
They also used thawed CAR-T cells to treat non-Hodgkin’s lymphoma and glioblastoma, in mouse models. Mice treated with CAR-T cells preserved using the new strategy had higher survival rates than mice treated with cells preserved using the conventional DMSO approach.
“Preservation methods for living biotherapeutics have seen limited innovation, remain poorly characterized at scale, and often compromise cell viability and function after thawing,” Tran says. “We believe that our findings underscore the importance of thorough characterization and optimization of every stage of cell therapy manufacturing, which could have dramatic impacts on treatment efficacy.”
The researchers now hope to work with hospitals to explore whether their new technique could be easily integrated into the process of producing and thawing CAR-T cells.
“If that’s successful from a cell viability and functionality standpoint, perhaps we will do a small trial with patients,” Jaklenec says.
Vijay G. Sankaran, a professor of pediatrics at Boston Children’s Hospital and Harvard Medical School and a Howard Hughes Medical Institute Investigator, who was not involved in the study, says he is excited by the potential applications of the research.
“As a pediatric hematologist and oncologist, many of the cell therapies we use, including CAR-T cells and blood stem cells, require us to collect and freeze a substantial number of cells, so that enough healthy cells are available after thawing for when patients need treatment. This work suggests an innovative approach that could help more cells survive the freezing and thawing process, potentially making these powerful therapies more reliable and effective. Of course, further work will be needed to validate these results in settings where this approach can be clinically applied,” Sankaran says.
This work was supported by postdoctoral fellowships from the Ludwig Center at MIT’s Koch Institute and the Convergence Scholars Program at the MIT Marble Center for Cancer Nanomedicine.
Startup brings ancient Roman concrete technology to modern constructionDmat is commercializing findings from the lab of Associate Professor Admir Masic to make concrete longer-lasting and more sustainable.Concrete has served as the foundation of empires for thousands of years. Today, it’s one of the most common materials in the world. But one look at the ancient Roman concrete structures still standing suggests that ancient builders knew something about durability that we don’t.
MIT Associate Professor Admir Masic has spent his career studying ancient Roman concrete. His work has uncovered details about what gave Roman concrete its legendary durability, including the manufacturing process that endowed it with self-healing properties.
In 2021, Masic decided to apply those findings to improve the durability of modern concrete by co-founding Dmat. Today, the company has developed additional technology to create a concrete additive that increases the lifespan of concrete structures by 50 percent and reduces CO2 emissions to 40 percent of traditional concrete.
The company’s concrete has been used to make complex infrastructure across Europe including underground water tanks, road barriers, and pavement in Italy and Switzerland. The company plans to expand to the U.S. soon.
“We can now offer an extremely competitively priced, self-healing product that is easy to implement and available worldwide,” Masic says. “What’s exciting to me is that this material could become the industry standard without requiring companies to change how they operate. It doesn’t introduce any uncertainty, because it’s based on ancient Roman technology that has been tested for thousands of years. By applying lessons from the past, we’re enabling a better future for the modern concrete industry.”
Applying ancient insights
Masic’s research at MIT has involved using new characterization techniques to probe the chemical makeup of ancient concrete. It has also brought him to well-preserved ancient construction sites in Pompeii, where historical practices could be deconstructed.
In a 2023 study funded, in part, by the Concrete Sustainability Hub, Masic and collaborators showed that when ancient Roman concrete cracks, reservoirs of calcium inside it desolve and recrystallize to fill in the new openings. Using that insight, the team developed new concrete formulations based on the Ancient Roman technique that deliberately retain calcium-rich lime clasts throughout the mix. The researchers spent a year testing samples to show the technique improved the mechanical performance and durability of different forms of concrete.
Those findings served as the foundation of Dmat. Masic partnered with Italian entrepreneur Paolo Sabatini to commercialize the technology shortly after the paper was published.
Dmat has since developed a large portfolio of proprietary technology on top of what was licensed from MIT. As it developed its solution, Dmat worked with company laboratories to secure safety and performance certifications in the European Union and ensure it fit modern concrete-making practices.
“At Dmat, we like to view concrete as an ecosystem,” says Sabatini, who serves as Dmat’s CEO and co-founder. “How does a material become the biggest industry in the world? There are considerations around not just materials but also transportation, price, and certifications. In order to get adoption, you need to design something that fits within the current industry’s ecosystem.”
Today Dmat supplies additives that can be mixed with concrete and mortar to extend the lifespan and performance of the materials. Dmat sells its additives to developers as well as concrete manufacturers to incorporate when mixing the concrete. More recently, the company has also introduced a line of ready-mix bagged mortars for structural restoration.
“When we work with clients, we can customize the concrete mix for their project and then supply filler using our recipe,” Sabatini explains. “We provide recipes to concrete manufacturers and engineers that improve the performance of concrete. But we also work across the supply chain with developers, architects, construction companies, and others.”
The first few years of the company were spent developing the technology and establishing relationships with the industry while attaining the necessary certifications to deploy in Europe.
“What’s good about Dmat is that the company is truly embedded into the concrete industry,” Masic says. “The company isn’t selling an idea. They have gone slow and carefully chosen projects to ensure they are successful in providing self-healing concrete without significant added cost.”
Built for scale
Other self-healing concretes use bacteria or polymer substances as additives, which can be more expensive, not to mention less familiar to people in the industry. Dmat’s founders have spent years honing their recipes to achieve self-healing properties with materials more familiar to the industry.
As a result, they believe the company is now in a strong position to scale. And scalability is crucial to make an impact in the industry: Concrete today is the most produced material in the world. It’s responsible for approximately 5-8 percent of global CO2 emissions.
“There’s something profound about how ancient builders, without our modern chemistry, engineered self-healing material that still stands today,” Masic says. “My group research and work with Dmat is to make the modern built environment better by applying the best lessons from the past to today’s challenges.”
How 35 percent of US employees are left on the marginsIn a new book, Paul Osterman details his research finding more than one-third of the country’s workers are “disposable,” with little security or chance of job advancement.You’ve heard of gig workers, freelancers, and temporary employees. But do you know about marginal workers?
Accounting for about one in six U.S. jobs, it’s a huge category of people, who are going nowhere fast in the workplace — and don’t really have much say about that.
“Marginal workers are employees who have no career prospects at their organizations,” says MIT Professor Emeritus Paul Osterman, author of a new book on the subject. “They are employees of the organization for whom they work, but the organization does not intend to keep them, and these workers are much less attached to any career ladder.”
As such, marginal workers are part of a larger trend in U.S. employment. According to Osterman’s analysis, 35 percent of U.S. workers are either marginal employees, freelancers, contractors, or gig employees finding work on online platforms like ridesharing services.
“That’s a big number,” says Osterman, who is the Nanyang Technological University Professor Emeritus at the MIT Sloan School of Management, where he is also a professor emeritus of work and organization studies. “That’s over 55 million people in the American work force.”
Osterman scrutinizes this employment landscape in his new book, “Disposable Workers: The Transformation of Employment,” published this month by Harvard University Press. In it, he examines the different categories of “disposable” workers in the U.S., while making the case that they are all part of a still-growing movement by firms to control labor costs, leaving many workers in precarious positions.
“I wanted to present a unified way of thinking about these trends,” Osterman says.
Cutting costs
Osterman is a longtime labor economist and author of several previous books, whose work has often focused on job quality and labor-market fairness.
He was motivated to write “Disposable Workers,” he says, because of how significantly marginal workers have been overlooked. Indeed, the category and term “marginal workers” comes from Osterman.
In researching the book, Osterman conducted an original survey of over 6,000 workers, which helped shed light on the concept of marginal workers. They can fit a range of professions: staff attorneys at a law firm, adjunct faculty, and many kinds of part-time employees with few opportunities for advancement.
Overall, Osterman finds that about 17 percent of U.S. employees are marginal workers. Roughly 12 percent are contract workers, who are often employed by staffing agencies but then assigned to work at varying locations. Another 5 percent are organizational freelancers, working for firms without being part of the permanent staff. This includes gig workers, who account for a little more than 1 percent of the workforce and draw work from online platforms such as rideshare services. (Beyond this, there are also freelancers who work individually for multiple clients.)
The common denominator among these categories is that each has evolved as a result of firms trying to cut back on labor expenses while trying to gain flexibility and more managerial discretion. The result is fewer workers with promotion prospects, health benefits, and employment stability.
“I’m putting the discussion of freelancing, contracting, and marginal workers into a coherent story that shows they’re all of a piece, they’re all part of the same thing, in terms of how employers are thinking about it,” Osterman says.
Long term versus short term
How employers think about it, to be clear, revolves primarily around employee costs. By deploying employees in a variety of marginal, freelance, and contract roles, and making some of those positions part-time, businesses have constructed a system in which fewer employees have rising wages or additional benefits, and the portion of firm revenues plowed back into paying for workers can shrink.
“This is not a book that argues that there’s dishonesty or that anyone’s evil, but at the end of the day, firms only care about one thing, which is to maximize profits, period, end of story,” Osterman says.
He adds: “I’m very careful to say it’s a good thing that firms create jobs and develop new products — all good.” Still, he notes, for people who prioritize the plight of workers, the expansion of a disposable work force is a significant issue.
To be sure, many scholars have found that short-term labor cost reductions can be counterproductive. Many firms have appeared to benefit from having a more stable, committed, motivated work force, which seems to result in greater productivity. What Osterman finds is that firms are likely aware of this tradeoff, and still willing to have a less-committed, less-expensive staff.
“The firms are obviously making a decision that the costs outweigh the value of commitment,” Osterman says. He also notes that the evidence on the matter is not entirely clear-cut.
“There’s a debate on both sides of that question,” Osterman says. “I can’t prove that firms are being smart or stupid. But I can just tell you what they’re doing. And what they’re doing is making the decision that they benefit from having a large fraction of their workforce be disposable.”
Making the issue matter
“Disposable Workers” has drawn praise from other scholars. David Weil, a professor in the Heller School for Social Policy and Management and the Department of Economics at Brandeis University, has called it “a carefully researched and engaging book documenting the degradation of employment in recent decades.”
Indeed, as “Disposable Workers” makes clear, the workplace has been challenging for many employees for a while now. Add artificial intelligence into this setting, and the outlook would seem to get even tougher for employees. Indeed, Osterman thinks AI could increase the use of disposable workers, if only for indirect reasons.
“I think this trend is going to be exacerbated by AI, because AI introduces a lot of uncertainty to firms about what their staffing needs are, and if firms are uncertain, they’re going to want disposable workers,” Osterman says. However, he emphasizes, “Disposable Workers” is not a book about AI.
In any case, if jobs in the U.S. have become more precarious, what can be done to reverse that trend? One answer might be more expansive worker protections stemming from union negotiations. But these days, Osterman notes, only about 6 percent of U.S. employees are in a union, so that will only go so far.
Still, Osterman points out that nonunion organizations can help the situations of workers, such as the advocacy groups that lobbied for a $15/hour minimum wage in many places several years ago.
Then too, he observes, sometimes customer pressure gets firms, even large multinationals, to improve working conditions, either for the firm’s own workers, or along its supply chain.
“There is no magic solution,” Osterman says. “There is a set of tools.”
A key reason he wrote “Disposable Workers” is to bring attention to the topic in the first place, and the full extent to which the U.S. now has a workforce without much security or prospects of upward mobility. Without recognition of that point, no effort to change things will unfold, Osterman believes.
“The bigger policy point is: This issue has to become salient,” Osterman says. “If it does, then public and political pressure will come to bear on firms. If it doesn’t, then it won’t.”
Mathematical framework connects biological principles to manufacturable, adaptive materialsThe new framework could streamline the design process of robotic grippers or aerospace components that exhibit complex behaviors found in nature.The scales of a pine cone open in low humidity to scatter seeds, but close in damp conditions to protect seeds from moisture. An artificial material with the same behavior could be useful in applications like moisture-responsive shingles for passive cooling.
MIT researchers have now developed a system that simplifies the process of designing this type of bioinspired material.
Their framework captures how mechanisms across length scales in a natural system, like the cells, fibers, and tissues inside a pine cone, work together to achieve unique properties. It then formally translates that behavior in an engineered system.
The framework organizes biological behavior into building blocks that can be used to design synthetic structures that can be mathematically validated to perform the same way, and fabricated using a 3D printer.
By taking much of the guesswork out of this design process, the framework could help engineers more readily create new adaptive materials while cutting development time and eliminating costs from failed prototypes. This framework could one day be used to design soft robotic grippers that respond automatically to their environment without any complex electronics, or morphing structures for airplane wings that predictably change their shape in response to temperature shifts.
“I’ve always been fascinated with natural materials and how complex behavior emerges from very simple building blocks,” says Lee Marom, an MIT graduate student and lead author of a paper on this framework. “What really excites me about this work is going beyond bio-inspiration to what we could call ‘bio-derivation,’ where we move past observing a unique behavior to capturing the relationships and mechanisms that are actually producing that behavior, and then finding a systematic way to translate them into an engineered system.”
Marom is joined on the paper by corresponding author Markus Buehler, the Jerry McAfee Professor of Engineering in the departments of Civil and Environmental Engineering and Mechanical Engineering; Gioele Zardini, the Rudge and Nancy Allen Assistant Professor of Civil and Environmental Engineering, a principal investigator in the Laboratory for Information and Decision Systems, and an affiliate faculty with the Institute for Data, Systems, and Society; and Skylar Tibbits, an associate professor in the Department of Architecture. The research appears in the Journal of the Mechanics and Physics of Solids.
Biological building blocks
Pine cones can open and close their scales in response to humidity because of complex interactions within the organism’s structure.
Shifts in humidity cause changes in microscopic cellulose fibers, which then cause transformations in larger groupings of fibers called laminas, which impact tissue layers, and so on, all the way up to the pinecone we see hanging from a tree branch.
“We instantiated the framework on the pine cone because it gives us a relatively simple, well-understood mechanism to demonstrate how the framework works. But its value becomes even greater as we apply it to more complex systems,” Marom says.
For engineers, the challenge is not necessarily reproducing an individual behavior, but translating the mechanisms and relationships that produce it across length scales. Without an explicit framework, these relationships need to be reformulated for each new system.
To streamline the material design process, MIT researchers created a mathematical framework that captures how the components at each scale in a natural object work together to exhibit a certain behavior. The framework carries the design all the way to fabrication, translating the engineered behavior into verified manufacturing specifications and executable code that is used to 3D-print the object.
“What we were missing was a way to connect the mathematical description of a natural system all the way to its physical realization. The goal of this framework is to make that entire chain explicit so we can reason about what has to be preserved at each step,” Marom says.
The framework utilizes tools from category theory, which is a systematic method to compose larger systems from smaller ones in a way that is guaranteed to succeed.
Using category theory, the system maps out how a stimulus, such as humidity, causes a response at each level of the biological hierarchy within an organism like a pine cone. It models each level of the biological hierarchy as a separate building block that is independently validated.
Then the framework constructs a larger system from these building blocks by employing mathematical rules to ensure there is a valid transition between each step in the hierarchy.
It assigns each building block in the natural system to a synthetic counterpart. In this way, the engineered material preserves the stimulus-response interactions that cause the natural organism’s unique behavior.
The work extends a research program in Buehler’s laboratory spanning more than a decade.
Earlier studies used category theory to describe hierarchical materials and determine when building blocks could be replaced while preserving higher-level function. In subsequent work, Buehler and colleagues introduced “categorical prototyping,” using the same mathematics to preserve selected molecular-scale mechanics when translating computational models into large-scale 3D-printed prototypes.
The new framework takes the next step by closing the entire chain, from multiscale biological mechanics, through an engineered realization and fabrication specification, to an experimentally validated, machine-executable design.
“Biological materials derive their extraordinary functionality from relationships that span scales, from molecular and fiber-level mechanisms to whole structures. Category theory gives us a way to make those relationships explicit and transferable. Once that design logic is captured mathematically, nature becomes a library of composable mechanisms that can be translated, recombined, and realized in new material systems,” Buehler says.
Compositional structure
“Once we know that the relationships we mapped are valid, we can start recombining them in new ways. That means the framework isn’t only describing existing systems, it can also help us reason about ones we haven’t built before,” Marom explains.
For instance, the engineers mapped the humidity-driven bending behavior in a pine cone and the humidity-driven twisting behavior of a wheat awn as separate sets of building blocks.
Then they combined some building blocks from each to design and fabricate a new type of actuator that exhibits thermal twisting behavior, without the need to do any new design work. When tested, the twisting actuator performed as the researchers expected.
In the future, engineers could use this framework to reliably combine verified components into new, bio-inspired designs for adaptive materials in applications like robotics, biomedical devices, or wearable technology.
“The systematization of our framework allows you to reuse pieces without needing to start from scratch each time, saving a huge amount of computation. That’s the real-world payoff,” Zardini says.
Now that the researchers have laid the groundwork with this mathematical framework, they can apply it to objects with more complex mechanics. They also plan to incorporate artificial intelligence models into their pipeline to expedite the discovery of new adaptive materials.
“We have shown that the boundaries between disciplines do not matter as much as we think they do. Some of the principles from category theory can be used to guide and empower materials design. These mathematical structures seem to really have no boundaries,” Zardini says.
“The larger vision is physical AI: intelligence that can reason in terms of physical mechanisms and then turn those ideas into matter. Here we are beginning to build the infrastructure for that — composable physical knowledge, mathematical rules for determining what can be combined, and a path from a new design concept all the way to machine instructions and fabrication. Ultimately, this could allow AI not only to discover new materials and mechanisms, but to physically realize and test what it discovers,” Buehler says.
This research was supported, in part, by the MIT Lemelson Engineering Fellowship, Singapore DSO National Laboratories, and the MIT Generative AI Impact Consortium.
MIT engineers connect bacteria to create living transistorsBy wiring together colonies of these bacteria, the researchers built circuits that can perform complicated calculations.MIT researchers have engineered bacteria that can function as transistors, allowing the team to create living “circuit boards” that can be printed onto a growth medium in a Petri dish.
In electrical circuits, transistors function as switches that can turn current on or off. In the biological circuits that the researchers have created, bacterial switches control the flow of small molecules, which send signals to downstream circuit components.
The research team designed two different transistors, along with three bacterial strains that relay information between the transistors, giving them the building blocks they need to design nearly any type of circuit. In a new study, they used these cells to create circuits that can add two or three inputs, or send one input to a specific location in the circuit.
“We’ve built some initial computer architecture components that are commonly used, but any operation can be built with these five strains,” says Hamid Doosthosseini PhD ’25, an MIT postdoc and the lead author of the new study.
Using this approach, the researchers hope to develop circuits that one day could coat plant leaves or roots, where they could compute to sense and respond to environmental conditions such as drought or attack by pests.
Christopher Voigt, head of MIT’s Department of Biological Engineering, is the senior author of the paper, which was recently published in Nature Chemical Biology. Former MIT postdoc Haorong Chen is also an author of the paper.
Cells as transistors
When designing synthetic biology circuits, researchers typically engineer cells to express proteins and transcription factors that interact to perform a task such as sensing a target molecule, which then triggers production of a specific output.
These simple circuits can perform various logic functions, but they must use unique transcription factors to avoid crosstalk within the circuit. There is a limited number of transcription factors that can be used for these circuits, which limits the overall complexity that can be achieved in a single cell. Additionally, putting too many circuits in one cell can overburden the cell’s protein production machinery.
In the new paper, the researchers took a different approach: Instead of building an entire circuit into one cell, they designed cells that could act as transistors. These transistors can then be combined in different ways to create a variety of circuits.
To create the transistors, the researchers chose a bacterium called Pantoea agglomerans, which commonly grows on surfaces, including plants. Using these cells, they made two types of transistors that can be switched on or off by a molecule called OC-6. One of the transistors is switched on by this input, and the other is switched off. Each transistor also detects the presence of a target molecule, in this case, OC-12. Depending on whether that molecule is present, and whether the switch is active, the transistors produce an output molecule known as OHC-14.
The researchers also used three strains of Pantoea agglomerans to create relays, which translate the OHC-14 signal into an output that can be fed into another transistor. Using these relay strains, the researchers can “wire” the transistors together, just like an electronic circuit board.
For example, they could create a bidirectional switch with two transistors that sense OC-12, and then send that information to different relay strains based on a switch input, ultimately feeding into other transistors that further process the signal.
The researchers created their circuits by printing colonies of bacteria onto plates containing agar, a growth medium. Each colony is printed about 5 millimeters from the nearest one. This allows the signals to travel only to the nearest colony, which then relays them to the next one, so information flows only in one direction.
Complex calculations
In this paper, the researchers demonstrated a transistor that can perform several types of logic operations depending on its location in the circuit layout, including “multi-input,” “or,” and “imply” gates. They also combined the transistors to create more complex circuits that can add up two signals, process more signals simultaneously, or function as a demultiplexer — a circuit that takes one incoming signal and sends it to one of several possible destinations, depending on a control signal.
The largest of these circuits, which adds two inputs together, contains 24 bacterial colonies wired together.
“This work shows that we can get toward more complicated functions by linking up simpler functions in individual cells,” Voigt says. “Computationally, there’s nothing that your iPhone can do that these circuits couldn’t do.”
Circuits made from these cells take about eight hours to perform each calculation, much longer than a computer circuit. But, for biological applications, that is a reasonable amount of time, the researchers say.
“We’re not trying to replace computers, but rather put computational control into biology. If you have bacteria on the root of a plant, or the plant itself is doing the computing, running a simple calculation overnight is fast enough relative to a growth season,” Voigt says.
If developed for use in agriculture, this type of circuit could be applied to the roots of plants to detect different types of stress. Once a particular input is detected, it would trigger a response such as synthesizing a fungicide.
The research was funded, in part, by the U.S. Defense Advanced Research Projects Agency and by the U.S. Intelligence Advanced Research Projects Activity.
Flexible brain circuits can switch between different tasksNeuroscientists have discovered circuits in the prefrontal cortex that can be repurposed to store different types of information.As we move through everyday life, our brains engage in a huge variety of cognitive tasks. For example, during a grocery run, we might have to recall the items for a recipe, remember where the clerk said the flour was located, and count out money to pay.
Scientists have long theorized that the brain contains modules, or clusters of neurons, that perform the same computation across many different types of tasks. This type of modularity could help explain why our brains are able to take on so many functions, with little difficulty.
In a new study of mice, MIT neuroscientists have found the first evidence for the existence of these flexible modules. They identified neurons in the prefrontal cortex that can be used to store either a sensory input or an action plan in working memory.
“We found that the brain doesn’t dedicate a separate group of neurons for every type of information. Instead, it uses the same populations of neurons to perform the same computation on different kinds of information, which means the same subset of neurons can hold both an action and a sensory stimulus in working memory,” says Yuma Osako, an MIT postdoc and the lead author of the new study.
The discovery supports the theory that reusable circuits allow the brain to mix and match components to generate a rich variety of behavior, the researchers say.
Mriganka Sur, the Newton Professor of Neuroscience at MIT’s Picower Institute for Learning and Memory, and Timothy Buschman PhD ’08, a professor at the Princeton Neuroscience Institute, are the senior authors of the paper, which appears today in Nature Neuroscience. MIT graduate student Greggory Heller and postdoc Sofie Ahrlund-Richter are also authors of the study.
Cognitive building blocks
Dating back to his time as a graduate student at MIT, Buschman has been interested in understanding how the brain is able to perform so many different kinds of behavior.
“One of the solutions that’s always been proposed has been this idea of compositionality — that you can take pieces of cognition that perform part of a task and reuse them in another task,” he says.
In a study published last year, Buschman’s lab at Princeton showed that when animals perform a task such as categorizing objects based on their shape or color, they assemble neural circuits that perform different pieces of the task. Just like “cognitive Legos,” these building blocks can be flexibly combined to generate new behaviors.
Osako, who joined Sur’s lab several years ago, was also interested in studying cognitive flexibility. He and Sur teamed up with Buschman to explore a related question: whether individual neural circuits can be repurposed to perform different functions.
“Our everyday life requires us to temporarily hold many different kinds of information. One big question is how the brain can represent an unlimited variability of information using only a finite number of neurons,” Osako says.
To get at that question, the researchers trained mice on a task in which they have to determine whether two sensory stimuli (high or low pitched tones) are the same, and respond accordingly.
The researchers recorded electrical impulses from the brain while the mice performed this task, focusing on the prefrontal cortex, which is involved in executive functions such as planning and decision-making, and the parietal cortex, which processes sensory information and plans movement.
After measuring electrical activity from thousands of neurons, the researchers performed computational analyses that allowed them to identify groups of neurons that encode specific pieces of information.
They focused on two time periods — the time between the first and second tone, when the animals are holding a memory of the first tone, and the time between the second tone and the point where they have to decide on an action. During that second period, the animals are holding their decision and action plan in their working memory.
Within the parietal cortex, the researchers found that neurons appeared to exclusively store memory of the tone. But in the prefrontal cortex, they identified a cluster of neurons that could switch between the two types of memory. During the first period, they stored a memory of the first tone, but during the second, they were responsible for remembering the plan of action.
Re-using these clusters for different purposes allows the animals to flexibly store different types of information, the researchers say.
“When mice do tasks that test whether memory computations can be reused, the answer is they are. There are subspaces of functional activity in the prefrontal cortex that can be the substrate of mixing and matching toward flexible cognition,” Sur says.
Computational flexibility
The new findings offer support for the idea that the same computational circuits can be used for different purposes, Buschman says.
“The main result from this study is that there’s a circuit in the brain that maintains items in working memory, and you can put either sensory or motor information into it, and flexibly reuse it depending on what your current task is,” he says. “This means you do not have to build an entire new circuit for holding information in mind every time you want to learn a new task.”
The researchers now plan to study whether inhibiting these modules during different parts of the task affects the animals’ behavior, which could offer additional evidence that the flexible modules they identified participate in a variety of functions.
The research was funded by the National Institutes of Health, a MURI Grant, the Picower Institute Innovation Fund, the Japan Society for the Promotion of Science Overseas Research Fellowships, and the Uehara Memorial Foundation Postdoctoral Fellowship.
Professor Emeritus Chiang Chung Mei, pioneering scholar of ocean wave dynamics and fluid mechanics, dies at 91A towering figure in theoretical hydrodynamics is remembered for his intellectual rigor, generosity, and lifelong devotion to his students.Chiang Chung "C.C." Mei, professor emeritus in the MIT Department of Civil and Environmental Engineering (CEE), a renowned hydrodynamicist whose work shaped the field’s understanding of ocean waves and their interactions with coastal and offshore structures, passed away peacefully at home in Waltham, Massachusetts, on July 16. He was 91.
For more than four decades, Mei was a defining presence in CEE. Since joining the MIT faculty as an associate professor in 1965, he became one of the world's foremost authorities on theoretical hydrodynamics, fluid mechanics, and ocean and coastal wave phenomena, retiring in 2010 after 45 years on the faculty. Throughout his career, he earned a reputation among colleagues and students as a generous mentor and thoughtful leader.
An elegant, rigorous scholar
Mei's research advanced the science of ocean wave hydrodynamics, spanning nearly every aspect, including nearshore currents, sediment transport and resuspension, the formation of sand ripples and bars on beaches, wave-induced stresses and seabed deformation, and the removal of contaminants from soils. In later years, he extended his mathematical approach to biofluid dynamics, publishing on flow problems in blood vessels and the inner ear, including a paper on "Streaming and diffusion in the cochlea" that appeared in the Journal of Fluid Mechanics in July 2025.
He authored over 300 publications, was cited more than 14,000 times, and coauthored the landmark books "Theory and Applications of Ocean Surface Waves" and "Homogenization Methods for Multiscale Mechanics." Mei published decades of influential research on wave power extraction, harbor oscillations, waves over muddy seabeds, coastal vegetation, landslide-generated waves, tsunamis, and hydrodynamic resonance. His work combined mathematical elegance with practical engineering application and continues to guide solutions to some of the world's most complex ocean-based environmental challenges, including coastal defenses against storms and oil spill response strategies.
"C.C. tackled deep, diverse, difficult, and important fluid dynamics questions with utmost finesse and elegance," says Lydia Bourouiba, the Japan Steel Industry Professor. "He was an inspiring scholar, an intellectual leader, and a wonderful mentor, whose rigor set the standard we should continue to uphold. We lost a true giant in our field."
His excellence and leadership in research and teaching earned numerous prestigious recognitions, including a Guggenheim Fellowship in 1972, election to the National Academy of Engineering in 1986, fellowship in the American Physical Society, the Theodore von Kármán Medal in 2007, and appointment as a Ford Professor of Engineering at MIT.
Beyond his scientific achievements, Mei devoted himself to the MIT community, serving as interim head of CEE from 2001 to 2002 and helping guide the department through a period of transition with the same humility and steadiness that characterized his scholarly contributions. In 2015, the department established the C.C. Mei Distinguished Speaker Series in his honor — an idea that grew out of the initiative of Bourouiba to revive CEE's environmental seminar series and honor its strong historical legacy in fluid dynamics. "Discussing the idea with C.C., he thought it was an excellent idea and was so generously supportive. He embodied the excellence I wanted the new series to reflect; naturally, we named it in his honor," she says. The series continues to bring internationally renowned scholars to MIT.
A mentor whose students became family
Mei's influence was equally profound in the lives of his students. Over more than 45 years at MIT, Mei advised and mentored generations of engineers, many of whom became leaders in academia, industry, and government. Even in his final days, those relationships endured.
One of his first doctoral students, Professor Emertius Ole Madsen, visited him just hours before his passing. Former student Yile Li SM '01, PhD '06, who continued collaborating with Mei on biofluid dynamics research in his later years, remained in close conversation with him throughout his final days. Li recalls the highlight of his discussions with Mei. "He told me there are three stages of doing research: solving problems using mathematical methods, modeling problems by capturing core physics, and ultimately discovering entirely new problems," Li says. "His own work proved he was a master of all three."
For Mei's family, MIT was never simply his workplace. "CEE was truly the center of my father's life," says his daughter Deborah Mei. "For more than 50 years, it shaped not just his career, but our whole family's world. His students, colleagues, and collaborators weren't separate from our home life — they were part of it, for as long as I can remember."
Colleagues consistently remember not only Mei's intellectual brilliance, but also his extraordinary generosity. Mei was known for the warmth he extended to junior colleagues finding their footing at MIT.
"He was so respectful and kind to me when I was hired in 1976, and feeling like a fish out of water," says Institute Professor Sallie “Penny” Chisholm. "I will never forget that. A great gentleman, indeed."
Heidi Nepf, the Donald and Martha Harleman Professor, recalls Mei as "an exceptional scholar and a wonderful colleague."
Rafael L. Bras, professor emeritus, remembers Mei as the model of the gentleman scholar. "He cared deeply about people, loved his profession, and touched countless lives, both directly and indirectly. Everybody loved him."
A full and joyful life
Mei was born on April 4, 1935, in Wuchang, Hubei Province, China, the only son and first child of Ju-Long Mei and Wu Yu-Ling. He earned his BS from National Taiwan University in 1955, his MS from Stanford University in 1958, and his PhD from Caltech in 1963.
Those who knew him describe a man who was passionate, playful, endlessly curious, and quick with both words and affection. The home he shared with his wife, Caroline, became a gathering place for generations of the Mei family, his MIT colleagues and students alike with animated conversation, humor, and his familiar loving banter with his wife and siblings, as those close to him remember it.
To generations of students and colleagues, Mei was known as much for his patience, kindness, intellectual curiosity, and quiet encouragement as for his scientific accomplishments. He was always willing to discuss an idea, help a student work through a difficult problem, or offer thoughtful guidance to a young colleague beginning an academic career. His legacy lives on not only in the theories that continue to shape coastal and ocean engineering, but also in the worldwide community of scholars he mentored, inspired, and welcomed over more than half a century at MIT.
Mei is survived by his wife, Caroline (Schmitt) Mei of Waltham; his daughter, Deborah Yupin Mei, and her husband, Juan Ignacio Garcia De Motiloa Ubis of Singapore; his sisters Helen Chiang-Hua Mei Chao of Potomac, Maryland; Teresa Chiang-Ming Mei Wu of Bethesda, Maryland; Heidi Chiang-Kuo Mei Hsia and her husband, Jack, of Potomac, Maryland; and Christine Chiang Ying Mei and her husband, Paul Tung, of Rancho Palos Verdes, California; his grandchildren, Juan Ignacio Jr. and Lauren; and many nieces, nephews, grand-nieces, and grand-nephews.
Gifts may be made in Mei's memory to the Chiang and Caroline Mei Fund
Drug that targets an inflammatory enzyme could help prevent lung cancerA new study by MIT researchers shows that inhibiting caspase-1 can reduce the risk of tumor growth.Every year, lung cancer kills more than 100,000 people in the United States. Smoking is the leading risk factor for lung cancer, but other environmental exposures can also contribute to the disease.
In an advance that could help prevent some of those lung cancer deaths, MIT researchers have shown that blocking an enzyme involved in lung inflammation appears to reduce the risk of developing tumors.
The researchers found that this enzyme, caspase-1, is active in developing tumors in mice. When they treated the mice with a small-molecule drug that inhibits caspase-1, the mice were much less likely to develop lung tumors.
That drug has already gone into clinical trials for other diseases, and the researchers now hope to test it as a preventative drug in people with elevated risk for lung cancer.
“If you look at global cancer deaths, lung cancer causes most of them, and most of that is driven by tobacco smoking. Additionally, people who are ‘never smokers’ are showing up with lung cancer. You can imagine a future where you get a test and if you’re deemed high-risk, you go on a preventative medicine. This concept is called cancer interception, and it could help millions of people,” says Sangeeta Bhatia, the John and Dorothy Wilson Professor of Health Sciences and Technology and of Electrical Engineering and Computer Science at MIT, and a member of MIT’s Koch Institute for Integrative Cancer Research and the Institute for Medical Engineering and Science (IMES).
Bhatia is the senior author of the new study, which appears today in Science Advances. Cathy Wang PhD ’26 is the lead author of the paper.
Blocking inflammation
Preventing lung cancer in patients who are at high risk could significantly reduce the death toll of the disease. In 2017, a clinical trial run by Novartis yielded a tantalizing hint that targeting lung inflammation could prevent some lung cancer cases. That trial, known as CANTOS, was designed to examine whether an anti-inflammatory drug — an antibody that blocks the cytokine IL-1 beta — could reduce the risk of strokes and heart attacks. Unexpectedly, the researchers found that this treatment led to lower rates of lung cancer in a subset of people.
Later trials showed that the antibody had little effect in patients who had established lung cancer, but researchers are still exploring the possibility of using it to prevent progression of lung cancer in high-risk patients. A recent study by the Swanton lab at the Francis Crick Institute identified a set of proteins, across several biological pathways and cell types, that could be used to predict which patients would respond to treatment with an IL-1 beta antibody.
IL-1 beta requires protease cleavage to be converted to its mature, active form. Thus, Bhatia and her team wondered if enzymes called proteases, which cleave other proteins, might be involved in driving the inflammatory pathway that includes IL-1 beta.
For several years, Bhatia’s lab has been developing tools to track and visualize proteases, since the activity of these enzymes can contribute to cancer development. Proteases can help tumor cells escape their original locations by cutting through proteins of the extracellular matrix, and they also play essential roles in guiding inflammatory cell migration, which can influence tumor growth and immune system targeting.
By coming up with ways to detect these enzymes, Bhatia’s lab has created diagnostic nanosensors for cancer and other diseases. The sensors consist of nanoparticles decorated with peptides that can be cleaved by certain proteases, revealing when proteases are active in a particular tissue or disease state.
In addition to their role in cancer, proteases are known to be involved in the regulation of inflammation. In their new study, Bhatia and her colleagues adapted their nanosensors to identify proteases that may participate in IL-1 beta-mediated inflammatory pathways.
“We know that proteases are very important in inflammation, and we wanted to pinpoint which ones might be the most active during early lung cancer development,” Wang says.
For this study, the researchers used a mouse model developed by Tyler Jacks, the David H. Koch Professor of Biology at MIT and a member of the Koch Institute. This model, known as KPS, is engineered to turn on cancer-causing mutations in the p53 and Kras genes. The mice also express a peptide called SIINFEKL, which helps to activate T cells and stimulate inflammation in the lung.
The researchers designed their experiments to allow them to model increased cancer risk, beginning before tumor formation was detectable. Five weeks after they induced the cancer-causing mutations, the researchers injected some of the mice with an antibody that blocks IL-1 beta, while others were untreated. Three weeks later, the researchers used their nanosensors to detect proteases that were active in the lungs.
Those experiments showed that in untreated mice, which all developed lung tumors, caspase-1 was very active. However, in the treated mice, which had fewer tumors, caspase-1 activity was significantly reduced. The researchers also found that in untreated mice, the active caspase-1 was found primarily in lung tumors, not in nearby healthy tissue.
Working with Lecia Sequist, a professor of medicine at Havard Medical School and physician at Mass General Brigham, the researchers also analyzed a small number of human lung fluid samples. In these samples, they also found higher levels of caspase-1 activity from patients with lung cancer compared to healthy donors, despite a common smoking history.
A repurposed drug
The observation that caspase-1 activity is interrelated with the IL-1 beta inflammation pathway was not completely surprising, given IL-1 beta itself required protease cleavage to be converted to its mature, active form. The MIT team then investigated whether inhibitors of caspase-1 might also provide the same protective effects as inhibitors of IL-1 beta, or even improve them.
Before tumors developed, the researchers began treating the at-risk KPS mice with either a caspase-1 inhibitor, an IL-1 beta antibody, or both. In mice that received both drugs, nearly 20 percent never developed tumors at all. In the mice that received either the caspase-1 inhibitor or the IL-1 beta antibody alone, tumors were much smaller and less numerous than in untreated mice.
Unlike antibodies, which need to be given intravenously, caspase-1 inhibitors can be taken orally, which could make them more appealing as a preventative treatment. Another opportunity provided by these drugs is that they have previously been tested in clinical trials for treatment of rheumatoid arthritis and other diseases.
“What’s so attractive about using this caspase-1 inhibitor is that it has actually been tested in humans. It’s already been through safety studies, and we think it could potentially be repurposed for cancer prevention,” Bhatia says.
The researchers hope to test the drug in a clinical trial, potentially using the biomarkers that were identified by the Swanton team to identify subjects who are likely responsive to IL-1 beta antibody treatment.
The authors of the study also include MIT researchers Qian Zhong, Shih-Ting Wang, Carmen Martin-Alonso, Sofia Neaher, Sahil Patel, Tiziana Parisi, Jesse Kirkpatrick, and Tyler Jacks.
The study was funded by Johnson & Johnson, Upstage Lung Cancer through the Koch Institute Frontier Research Program, the Virginia and D.K. Ludwig Fund for Cancer Research, the Koch Institute’s Marble Center for Cancer Nanomedicine, the Koch Institute Support (core) Grant from the National Cancer Institute, and a core center grant from the National Institute of Environmental Health Sciences.
Cells pulse together as they grow — and malignant cells pulse the longestMIT researchers discovered a cellular dance that may offer clues to the development of cancer, asthma, and other diseases.Epithelial cells are the tiny shields that line and protect our body. In a developing embryo, epithelial cells grow, divide, and move into positions to form the outer layers of our skin and the surfaces of our organs and blood vessels. When we scrape our skin, suffer an internal tear, or undergo surgery, epithelial cells will migrate to the site of injury to heal a wound. And when epithelial cells go haywire, they can turn malignant and spread through the body as cancer.
MIT engineers have now discovered that as they migrate, epithelial cells can synchronize and collectively pulse. In a study appearing today in the journal Newton, the researchers report observing groups of epithelial cells repeatedly moving in, then out, like a circle of dancers coming together and pulling apart.
The team measured this collective rhythmic pulsing in different types of epithelial cells, including healthy cells, cells from benign tumors, and cancerous cells.
Surprisingly, they discovered that malignant epithelial cells were more persistent in their synchronization, pulsing together for twice as long as healthier cells. It’s unclear why the cells sync up in this way. But the researchers suspect that this cellular dance can serve as a clinical signal.
“More aggressive cancer cells tend to have a steadier and more persistent rhythm as compared to healthy ones,” says study author Ming Guo, professor of mechanical engineering at MIT. “We think this coordination could serve as an early warning sign of how likely a tumor is to spread. The same coordinated waves may help shape embryos during development and close wounds upon injury.”
The study includes first author and former MIT graduate student Wenhui Tang SM ’20, PhD ’24; Mehrana Nejad and L. Mahadevan of Harvard University; and Adrian Pegoraro of the Metrology Research Centre of the National Research Council Canada.
Cells got rhythm
When studying how epithelial cells organize and develop into whole organs and tissues, scientists have focused mainly on how the cells coordinate in space. Where cells move, where they are in relation to the growing tissue, and where they end up, are questions of spatial coordination that scientists including Guo have looked to investigate. How the movement of cells relate over time is less well-understood.
Guo’s group at MIT studies cell interactions to identify patterns that relate to healthy versus diseased states. As part of this work, the team takes microscopic snapshots of cells that they grow in the lab, to identify interesting behaviors among cells. Recently, Tang, then a member of Guo’s lab, was looking at a series of movies of epithelial cells when she started to see a rhythm, or pattern over time.
“I was studying collective cell migration, and I observed cells were swelling, then squeezing together, then swelling, again and again, forming local patterns,” Tang recalls. “That’s when I realized there might be something more interesting happening with these cells over time.”
Taking a pulse
In their new study, the researchers focused on the timing of cellular movements. They started by studying healthy, live epithelial cells that they cultured in the lab. They stained the cells with fluorescent dye to illuminate each cell’s nucleus. This way, they could easily identify one cell from another. They kept the cells in dishes with nutrients to help them naturally grow, divide, and move about.
“We’re looking at their natural migration process, related to how they would migrate during different processes in the body, such as when forming skin and organs, and healing wounds,” Guo explains.
Using a confocal microscope, the team took snapshots of the cells every few minutes, for up to 30 hours. When they strung the images together as a sort of movie, a distinct pattern emerged.
“If you just stare at any one location, you can see those dots are coming together, and then going further away, then coming together again, and going further away, like waves,” Tang says.
They observed that a single pulse occurred over about an hour. This pulsing persisted in healthy cells, as a slow and steady rhythm over the 30-hour period.
Curious as to whether other types of epithelial cells would sync up in similar fashion, the team tried the same experiment with several different lines of human breast cancer epithelial cells. They studied the movement of cells from benign tumors and cells of increasing malignancy. They observed similar pockets of synchronized pulsing in every cell type, especially in the most cancerous cells.
“We found the really dangerous cancer cells team up over time, and do this persistent oscillation, twice as long as healthy cells,” Guo says. “This is unexpected. We see they really team up, synchronize, and oscillate together, which potentially facilitates their invasion.”
The researchers also observed a correlation between cell synchronization, and cell density: In each dish of cells, regardless of type, the cells continued to grow, divide, and pulse. As their numbers grew, more cells pulsed together, and their synchronization increased, up to a point. Once the cells reached a certain density, their pulsing began to die down.
“There’s a peak of synchrony before it decreases as cell density continues to increase,” Tang says.
This connection is especially interesting in the context of certain conditions such as asthma. Epithelial cells line the inside of many organs and tissues, including the airways. In healthy people, these cells pack together and “jam” up to form a solid, stable lining that protects the airways. In asthmatic airways, however, epithelial cells are less able to jam together. This results in airways that are loose and fragile, easily irritated, and difficult to heal.
Guo and Tang suspect that, as there appears to be a connection between cell density and cell synchronization, there may be a way to target asthma treatments, by watching how potential drugs affect asthma cell synchronization. A similar approach could be taken for the screening of cancer drugs.
“More malignant cells would be better synchronized. After treating them with a drug, if their synchronization is disrupted, then it might be an efficient drug where we can consider the next step,” Guo envisions.
This research was supported, in part, by the National Institutes of Health.
High-speed microscopy reveals electrical activity across the brainThe new technique could help scientists learn how the entire brain works to generate decisions and emotions.Within the brain, neurons compute by generating electrical impulses. These signals travel throughout neurons, which are in turn connected in vast networks that control brain functions such as sensory perception, memory formation, and control of movement.
In an advance that could help neuroscientists map those neural networks, leading to a better understanding of how neural activity underlies behavior and other brain functions, MIT engineers have invented a new microscope that can image electrical activity in neurons distributed across the brain of an entire organism, the experimental model Danio rerio (zebrafish).
Using a microscope that they adapted for fast, high-volumetric rate imaging, the researchers were able to track electrical activity across the brain on the scale of milliseconds. This method revealed patterns of neural activity from neurons throughout the brain that were activated in response to ultraviolet light.
“All of the parts of the brain are connected together, so if you want to truly understand the brain, you have to understand how all the neurons work together as an emergent whole,” says Ed Boyden, the Y. Eva Tan Professor in Neurotechnology at MIT; a professor of biological engineering, media arts and sciences, and brain and cognitive sciences; and a member of MIT’s McGovern Institute for Brain Research, Yang Tan Collective, and the Koch Institute for Integrative Cancer Research.
Boyden is the senior author of the study, which appears today in Nature Methods. Former J. Douglas Tan Postdoctoral Fellow Zeguan Wang PhD ’24 and former MIT research scientist Jie Zhang are the lead authors of the paper. Other authors include former MIT postdoc Panagiotis Symvoulidis, Picower Institute research scientist Wei Guo, graduate students Davy Deng and Lige Zhang, Koch Institute research scientist Adam Amsterdam, Picower Institute research scientist Takato Honda, Boston College undergraduate Steven Roche, and Matthew Wilson, the Sherman Fairchild Professor of Neuroscience at MIT and a member of the Picower Institute.
High-speed imaging
One technique often used to measure neuron activity in the brain is calcium imaging. Calcium flows into neurons after they fire an electrical impulse, so measuring calcium levels in the cells can serve as a proxy for neural activity. However, this type of imaging isn’t fast enough to capture single spikes of activity.
“Calcium imaging inherently is very slow, so you’re talking about imaging activity on the order of seconds or even minutes. Typically that is too slow for us to be able to see a lot of these high-speed neural activities,” Zhang says. “Neurons compute using electrical activity, so with voltage imaging, you can get direct observation of that.”
To enable direct imaging of voltage, researchers have developed proteins called genetically encoded voltage indicators — fluorescent proteins that can be genetically expressed in neurons. When a neuron fires an impulse, the protein fluoresces, which can be detected with a fluorescence microscope.
In previous work, researchers have used these proteins to image small populations of neurons, usually focusing on one localized part of the brain. Until now, there hasn’t been a way to image a large volume, such as the entire brain, with the millisecond-scale resolution needed to see electrical impulses from individual neurons.
To achieve that, the MIT team decided to modify a commonly used microscope known as a light sheet microscope. This type of microscope uses a sheet of laser light to illuminate a thin slice of a sample. By imaging many layers in sequence, this technique can generate 3D images of a large volume. However, with previous microscopes, the scanning of an entire volume would take too long to be able to capture neuronal impulses across the volume at single cell resolution.
“Different groups of neurons that are distributed across the brain coordinate together at millisecond timescales to generate a lot of behaviors and brain computations,” Wang says. “To understand the principles, we need the technology to observe their activity at the same time, across the whole brain, so we are not missing any important participant neurons.”
To make the imaging process fast enough to image millisecond-scale activity, the researchers increased the image acquisition speed of the microscope’s camera, and they also boosted the scanning speed of the microscope using a technique called remote refocusing.
Using this approach, the researchers showed that they could scan the entire zebrafish brain 200 times per second, or once every five milliseconds.
Mapping brain activity
To test the new microscope, the researchers engineered neurons in larval zebrafish to express a voltage indicator called Positron2-Kv. Although they had hoped that the indicator would end up in every neuron, it produced signals in neurons distributed throughout the brain, with about one quarter of the neurons exhibiting acceptable signals. This was enough, however, to observe patterns of activity across the brain. The researchers imaged the brain as the fish were resting, and they were able to observe single voltage spikes from neurons, as well as rapid bursts of spikes.
Additionally, this technique revealed patterns in how the brain is activated following a stimulus such as ultraviolet light. Immediately following the stimulus, activity was seen in the optic tectum, which receives and processes visual input from the retina. This activity propagated from one side of a part of the brain called the tectum to the other. Stimulus-independent activity also occurred in sequences across sets of neurons in the cerebellum and hindbrain.
The researchers now hope to increase the percentage of neurons that they can image across the brain, as well as the microscope’s speed and resolution. They are also working on expanding the use of this technique to other experimental models, including mice.
This approach, they say, could offer neuroscientists a new way to generate hypotheses about what happens in the brain when it engages in specific behaviors, or about how brain activity is linked to states of mind such as daydreaming.
“A big question is simply to understand how neurons work together as a network. And this might be the first time that you could do that, because you can image the voltage of neurons distributed throughout the network,” Boyden says.
The research was funded by the National Institutes of Health, the BRAIN Initiative, the Picower Institute Innovation Fund, K. Lisa Yang, Ashar Aziz, the K. Lisa Yang and Hock E. Tan Center for Molecular Therapeutics in Neuroscience at MIT, the Hock E. Tan and K. Lisa Yang Center for Autism Research, the Alana Down Syndrome Center, John Doerr, Jed McCaleb, James Fickel, and the Howard Hughes Medical Institute.
Researchers uncover hidden pore network within nuclear fuelNew understanding of how nuclear fuel breaks down and changes in an operating nuclear reactor could help keep some reactors running longer, will inform the next generation of nuclear reactor fuel systems.The moment a nuclear reactor begins operation, a complex chain of events is initiated within the fuel: Heavy atoms split into fission products, knocking other atoms out of place and creating defects that can change how the fuel swells, transfers heat, and reacts chemically over time.
Understanding those processes is key to understanding how safe and efficient a nuclear reactor will be. But even for some of the most-studied fuel types, the mechanisms controlling those processes are unclear.
Such is the case with a particular kind of metallic fuel, uranium alloyed with 10 percent zirconium by weight, also known as U-10Zr. This fuel was extensively tested in historic sodium-cooled fast reactors such as the Experimental Breeder Reactor-II (EBR-II) in Idaho and the Fast Flux Testing Facility (FFTF) in Washington state, helping establish the foundation for metallic fuel development in the U.S. Today, U-10Zr is again attracting attention for use in next-generation advanced reactors.
But most studies of U-10Zr took place decades ago, leaving unanswered questions about exactly how the fuel changes when it undergoes nuclear fission in a reactor and how it interacts with the protective fuel cladding surrounding it.
Now, together with Idaho National Laboratory (INL), MIT researchers have led one of the most detailed three-dimensional studies of irradiated U-10Zr to date. The researchers used a technique known as high energy synchrotron X-ray computed tomography at Brookhaven National Laboratory (BNL) in New York to analyze the pore networks and chemical changes that formed under irradiation during use inside the FFTF reactor, providing new insights into how the material swells, transfers heat, and interacts with the fuel cladding.
The findings could help keep some nuclear reactors running for longer, while also informing the next generation of nuclear reactor fuel systems.
“This study helps us model the pore distribution in the fuel more accurately,” says senior author Ericmoore Jossou, MIT’s John Clark Hardwick (1986) Professor of Nuclear Science and Engineering. “It also helps us design for the safe operation of metallic fuels in reactors by giving us a better understanding of the role of pores and their importance.”
Joining Jossou on the paper are first author and MIT postdoc Anthony Harrup; Riley Moeykens ’25, SM ’25; BNL researchers Michael Drakopoulos and Nghia Vo; and INL researchers Jana Howard, Colby Jensen, and Tiankai Yao.
Understanding nuclear fuel
A class of nuclear reactors known as sodium-cooled fast reactors generate energy from rods of metallic fuels that are sealed inside metal tubes called cladding. In each rod, heat generally moves outward from the center to the edge and then to the cladding, where liquid sodium carries heat away to be harvested into power.
“As you operate the reactor, the contact between the fuel and the cladding material creates chemical interactions that can be problematic,” explains Jossou. “There is a migration of materials from the fuel to the cladding, like fission gases and rare earth elements called lanthanides, which can react with the cladding, cause embrittlement, and damage the fuel system.”
Studies of previously irradiated fuel and its cladding have captured mostly two-dimensional snapshots, preventing scientists from seeing the full scale of the pore networks that influence heat transfer and transport materials like lanthanides. Previous studies also mainly focused on specific sections of the fuel system, such as the fuel center or the fuel cladding interface.
For their study, the MIT researchers used fuel samples from the Fast Flux Testing Facility reactor, a sodium-cooled fast neutron reactor located in Washington state that operated from 1982 to 1992.
The Idaho National Lab managed the samples and prepared the samples. The team studied the prepared samples using high-energy synchrotron X-ray tomography at the Brookhaven National Laboratory. The synchrotron generated high-energy X-rays that allowed the researchers to reconstruct the fuel’s internal pore networks in three dimensions, revealing how porosity, chemistry, and fuel-cladding interactions evolve across the fuel radius.
The researchers found porosity increased modestly from the center of the fuel toward the fuel edge, but pore density jumped by over two orders of magnitude at the fuel’s edge by the cladding. The researchers also characterized the size and shape of pores, finding small pores at the center that turn into larger pore networks pointing outward toward the edge.
“The pores are currently modeled as spheres; however, in reality they are more complex, especially when many pores merged together,” Harrup says. “That’s true from the center all the way to the cladding. It explains why the cladding reacts the way it does, and why we see cladding chemicals in the fuel.”
The pore networks toward the edge allow fission products and lanthanides to move but slow down heat transport, impacting the fuel’s performance and lifetime. The researchers also mapped their microstructural findings with changes in the chemistry of the fuel in different areas.
“With this study, we’ve conducted an in-depth analysis enabled by advanced computational imaging methods that has never been done before, with correlations between local chemical environments and the formation of pores,” Harrup says. “It turns out that whether the environment is uranium rich or zirconium rich impacts the morphology and the channels of the pores. That has never been reported before.”
“The ability to directly visualize pore connectivity and fuel cladding interaction in three dimensions gives us important insight for improving fuel performance for advanced metallic fuel for sodium fast reactors,” says Tiankai Yao of INL.
Informing reactor designs
The experimental findings differed from some models of how pores form and how the fuel system swells, which could improve simulations to help keep reactors running for longer. They also give a more nuanced picture of how pores influence reactor performance and safety.
“This helps optimize the current metallic fuel proposed for sodium fast reactors,” Jossou says. “Now, together with INL, we better understand how pores are influencing the thermal performance of metallic fuel in reactors. At high temperature, the pores are not all bad, because we found they act as pathways for liquid sodium metal to flow through the fuel and sustain thermal conductivity. Connected pores could also serve as releasing channels for fission gases which reduce the internal fuel matrix stress.”
The findings could also be used to design better fuel systems for next generation of sodium fast reactors.
“This excellent piece of work generated by Professor Jossou’s group in collaboration with INL and BNL has elegantly combined the strength of attenuation-based X-ray tomography and focused ion beam lift-outs and produced valuable insights to the location-specific 3D porosity distribution in neutron-irradiated U-10Zr fuel,” says Dong Liu, a professor at Oxford University who was not associated with this work. “What is also impressive is that they correlated 3D porosity to the thermal properties of the fuels: The total volume fraction is not the only parameter that is important, the 3D topology also matters. This is extremely informative for the study of other types of porous nuclear materials.”
The work was supported by the U.S. Department of Energy Office of Nuclear Energy and utilized resources at BNL and INL. The sample preparation was carried out at INL, which is part of the Nuclear Science User Facilities, through a Rapid Turnaround Award.
Featured video: An “MIT story” about an iconic professorA new short film from MIT Open Learning explores the influential career of Institute Professor and School of Engineering Dean Paula Hammond.A new short film spotlights the life and career of MIT Institute Professor and School of Engineering Dean Paula Hammond ’84, PhD ’93.
The documentary, “Full Circle: Paula Hammond at MIT,” traces Hammond’s path from childhood in Detroit, Michigan, to her arrival at MIT at 16 years old, to her evolution into a pioneering researcher in nanotechnology and ovarian cancer, as well as a leader at the Institute and around the globe.
The film is one of the debut offerings within “MIT Stories,” a new documentary series on MIT Learn that spotlights the innovators and changemakers whose work extends far beyond campus walls. Produced through intimate storytelling by MIT Open Learning’s Emmy Award-winning video team, the series aims to explore the passions that spark global impact and the human stories behind innovation.
“Everything Paula Hammond does is grounded in a deeply personal sense of purpose,” says Lana Scott, assistant media development director at MIT Open Learning who produced the film with Nick Vandenberg. “As a pioneering researcher and the first woman to lead MIT’s School of Engineering, she didn’t just break barriers, she changed what leadership can look like in a field that hasn’t always made space for people like her. Her story blends curiosity, care, and conviction, turning complex science into something human, relatable, and genuinely cinematic.”
The film’s original score was composed by Vandenberg, who was inspired by a musician Hammond has long cherished.
“Before our second interview, Paula and I spoke about our shared love of jazz, including artists like Charlie Parker and Miles Davis,” says Vandenberg, a videographer and senior editor at MIT Open Learning. “She mentioned Ramsey Lewis as a particular favorite of hers. So, as a little Easter egg for her, I wrote and recorded a composition with upright bass, drums, and organ based loosely on the sound of his early trio recordings.”
Video by Lana Scott and Nick Vandenberg / MIT Open Learning | 8 minutes, 40 seconds
Astronomers discover a brand-new type of astrophysical object: A black hole starThe mashup of a black hole and an enormous star has never been seen before and could explain the mysterious little red dots often found in deep-space images.Astronomers at MIT and elsewhere have spotted an extremely bright red spot in the early universe. The object resembles an enormous star, spanning the size of our solar system. But it also is putting out 100 billion times more energy than any known star can physically produce. In fact, such energies are closer to what a black hole might generate.
The curious combination suggests that the red spot is an entirely new type of astrophysical source. The astronomers are calling it a “black hole star.”
In a paper appearing today in the journal Nature, the team presents their analysis of the new object, which they discovered using NASA’s James Webb Space Telescope (JWST). The telescope spotted the bright red dot in the very early universe, just a few hundred million years after the Big Bang.
The scientists conclude that the most likely explanation for the strange red dot is that it is a mashup of a black hole and a star — a combination that has never been observed until now. The object is likely a hugely dense cloud of gas, powered not by standard nuclear fusion, but by a central black hole.
“Our picture of this object is evolving very rapidly,” says lead author Rohan Naidu, a NASA Hubble Fellow and Pappalardo Fellow at MIT’s Kavli Institute for Astrophysics and Space Research (MKI). “We think there is a central black hole that is 100,000 times as massive as the sun. And around this black hole, there would be this very extended envelope of gas that looks like a star the size of the solar system. It’s huge.”
If the bright red dot is indeed a black hole star, it would help to solve the identity of other mysterious “little red dots” that have appeared in nearly every deep space image JWST has taken to date.
“These little red dots seem to be everywhere in the early universe but essentially disappear by the present day,” Naidu says. “What exactly these objects are has been one of the most debated topics of the JWST era.”
The study’s MIT co-authors are MKI Director Robert Simcoe, the Bruno B. Rossi Professor of Experimental Physics; and Wendy Sun ’26, along with collaborators from multiple other institutions.
A singular source
Naidu and his colleagues didn’t intend to find a black hole star. They were looking for the most distant, earliest galaxies, as part of a survey that they named “Mirage or Miracle” (MoM). The team used the JWST to look into deep space, back when the universe was a few hundred million years old. Their goal was to look for galaxies that actually formed at those early times.
“There’s been this puzzle of many bright galaxies showing up at extremely early times,” Naidu says. “What we found was that what looks like an extremely bright early galaxy, aka a ‘miracle,’ in some cases actually could be a ‘mirage.’”
As they looked through JWST’s images for intriguing sources to target with their survey, they noticed a feature that stood out from the rest: a dot that was very red, and very bright.
“When we see something very red in the universe, we often assume that it is surrounded by dust, like soot or ash,” Simcoe explains. “The same way that the wildfire smoke from Canada recently made the sky in Boston look bright red, astronomical objects can also appear redder than their intrinsic color when you see them through a veil of dust.”
But there were other signatures in the light that didn’t quite match up with what physicists expect from dust. The team also observed another strange pattern: The dot’s light was extremely bright, except below certain wavelengths, where the light completely disappeared.
This spectral drop-off is known as a “Balmer break” — a signature traditionally associated with dense gas soaking up photons in the atmospheres of stars that are a few hundred millions of years old. Vega, one of the brightest stars in the night sky shows exactly this pattern.
“The break we observed in this object is the deepest break we have ever observed in any object, ruling out ‘ordinary’ stars as the source,” Naidu says. “But it made us wonder if we were seeing a new kind of ‘stellar atmosphere,’ but on a spectacular scale.”
What’s more, the red dot’s light contained almost no signature of metals or any elements other than hydrogen and helium. “It was truly singular in so many ways,” Naidu says.
Pure light
To puzzle out what the source of the red dot could be, the team ran simulations of different scenarios to see what combination of astrophysical features could produce the red dot’s distinctive color.
“We started to ask: Could you make something that red using just hydrogen, without any dust?” Simcoe says. “To our surprise, it turns out you can, if you have an extremely dense screen of hydrogen, so dense that it looks more like the surface of an enormous star than a wispy interstellar nebula.”
Their simulations pointed to the red dot possibly being some powerful enshrouded energy source, surrounded by an extremely dense cocoon of hydrogen. If this were the case, it would explain the light-blocking Balmer break and the lack of anything other than hydrogen and helium that the astronomers observed. But it still wouldn’t explain the object’s extreme brightness.
“You have something that looks a bit like a star but is 100 billion times brighter,” Naidu says. “That means you can’t be powering this by nuclear fusion, which is the energy source that sits at the heart of all the stars we have.”
Black holes, however, routinely produce energy at the scales the team observed. Naidu and his colleagues incorporated an active, accreting black hole into their simulations of the hydrogen-cocooned star and varied the black hole’s mass, along with other parameters. They then compared the resulting brightness of the simulated “black hole star” with the brightness that JWST observed from the red dot.
From these simulations, they found the closest match, and concluded that the most likely scenario to explain the red dot, is a black hole star. Specifically, the object likely contains a central black hole that is about 100,000 times as massive as the sun. This powerful core is surrounded by a dense, star-like cocoon of hydrogen that is roughly the size of the solar system.
The team has named the object MoM-BH*-1, after the survey that detected it, as well as the moniker “black hole star – one,” which implies that the object is the first of others. The researchers suspect that black hole stars could explain many of the other little red dots that appear in JWST images. Those objects are not as bright as MoM-BH*-1.
“Every little red dot is consistent with being a black hole star, embedded in a generic early galaxy,” Naidu says. “But what is special about MoM-BH*-1 is, the black hole star is essentially completely outshining its surrounding host galaxy, such that we’re seeing pure black hole star light.”
This research was supported, in part, by the MIT Department of Physics, NASA, and the Space Telescope Science Institute.
Met Warehouse opens as the new home of MIT’s School of Architecture and PlanningIn a feat of adaptive reuse, a massive, century-old brick storage facility has been turned into a contemporary hub for collaboration and creative work.It is a transformation for the ages: The Metropolitan Storage Warehouse in Cambridge, Massachusetts, is opening as the new home of MIT’s School of Architecture and Planning, after a makeover turning the century-old storage facility into a light-infused center for teaching, research, and public engagement.
The massive structure is a unique addition to daily life at the Institute. A hulking brick building and local landmark over 500 feet long and five stories high, the Met Warehouse now stands as a remarkable feat of architecture, engineering, and “adaptive reuse.” It includes four segments of glass walls, double-height studio spaces, copious common areas, and building-long walkways overlooking the work areas on all five floors — a 21st-century variation on the Infinite Corridor in MIT’s main group buildings.
Designed by the architecture studio Diller Scofidio + Renfro (DS+R), the Met Warehouse is intended to serve as a new campus hub. Beyond work studios, offices, and classrooms, there is an auditorium, galleries, and common spaces where MIT scholars and students can learn and design together, and the public can engage in lectures, exhibitions, and other programming.
“Walking through the Met Warehouse, everywhere you look you see the artful melding of the original architecture with the new design. It’s a perfect expression of the historical importance of architecture at MIT and of the creative promise of this new hub,” says MIT President Sally Kornbluth. “The new Met Warehouse will create a central home for design at MIT, and together with the new Linde Music Building, the presence of the Met will create a magnetic new west campus district for arts and design.”
Faculty, staff, and students have started moving into the Met Warehouse this month. The School of Architecture and Planning will stage a ceremonial procession into the building on Sept. 8, with a formal dedication event on Oct. 1, and a day welcoming the general public on Oct. 3 as part of MIT Future Fest.
The Met Warehouse’s conversion began in the late 2010s, championed by Hashim Sarkis, the dean of MIT’s School of Architecture and Planning, and his collaborators. They envisioned a new and dedicated space for architecture, design, and planning at MIT — while reusing an existing structure for that purpose.
“I think it sends a very good message that this vanguard school of architecture, at the Massachusetts Institute of Technology, is moving into a historic building and adapting it for the future,” says Sarkis, the Elizabeth and James Killian 1926 Professor. “This is a big statement on the part of MIT.”
Sarkis adds: “We’re expecting the Met to facilitate a very vibrant in-person culture. The vitality of interpersonal connection will be highlighted in the building. The faculty and the students wanted more research space, more space for exhibitions and galleries, and more spaces that enable what we do best, which is to work together. Design is about collaboration, and planning is about community.”
From fortress to studio
Built in stages starting in 1894 and completed in 1923, the building known as the Metropolitan Storage Warehouse long stood as a forbidding, fortress-like facility, with some tiny window slits. Only a few people had reason to venture inside. Visible from across the river in Boston, the Met Warehouse was a landmark, an advertisement of services, and a curiosity. It had about 1,500 storage spaces inside, and few other uses.
MIT acquired the building in 1962, and by 2015 it was no longer used for storage. That raised a question: What comes next? Over time, the idea of moving the School of Architecture and Planning into the Met Warehouse took hold. That left the hard work of designing and transforming the building into a place that people could inhabit, while respecting the historically designated façade’s monolithic qualities.
To create such a thoroughgoing transformation, MIT engaged DS+R, known for the design of high-profile cultural and institutional projects, including the Broad Museum in Los Angeles; the Institute of Contemporary Art in Boston; the Shed, a nonprofit cultural and performing-arts space in New York City; and, not least, the transformation of a postindustrial rail line into New York City’s High Line. Shawmut Design and Construction managed the renovation, and the entire endeavor was made possible by the generous philanthropic support of MIT alumni, volunteers, and friends.
Significantly, some of the signature projects of DS+R, including the High Line and the renovation of Alice Tully Hall at Lincoln Center in New York, involved updating and adaptively reusing existing structures. For the Met Warehouse, this meant a revamping of the interior, creating new workspaces, new ways to help people circulate through the massive building, and new ways to bring light inside the structure. In addition to the glass wall segments, the architects expanded the building’s windows, added a connective staircase, and found additional ways to let light and air permeate throughout.
“Our thinking was always around trying to bring communities on campus together, knowing there would be a convergence of labs, classrooms, resource spaces, and disciplines,” says Elizabeth Diller, founding partner at DS+R. “The big challenge from the start of the project was the building itself. The building is stubborn and big and heavy, and it was conceived to hold furniture and suitcases and pianos, not humans.”
When thinking through the project, Diller adds, “The first thing was assessing the building itself and its potential, and our ability to perforate it [allowing light] and to create new spaces inside of it. … We saw the potential, because of the structure, that it could endure some surgery.”
“The choice by MIT and Hashim Sarkis to adaptively reuse a building as a center for design represents a bold vision,” says Benjamin Gilmartin, partner at DS+R. “It’s a courageous idea: that the future of design and architecture very much lives in the reuse of structures we already have.”
MIT campus leaders say they are delighted with the outcome.
“The way the building is structured, the architects, Liz Diller, Ben Gilmartin, and their team, have been unbelievably shrewd in understanding our culture and respecting it while transforming the building,” Sarkis says. “That transformation enables the things we want, which include collaborative work, while also combining instruction and research.”
The makeover of the building also represents a collaboration between the City of Cambridge and MIT. Because the Metropolitan Storage Warehouse is a historically listed building, the city had to approve the substantial exterior renovations — such as on the north side, where several glass walls now cascade from the top of the Met to ground level. On the south side, the architects preserved many of the small storage units, redesigning them as offices with an innovative “skin” of new windows.
“That was one of the big decisions, based on light and the sensitivities of the history, that the large studios would be facing the north, and extracted from the north side of the building,” Diller explains. “Which left a lot of peripheral areas to act as small-scale and more intimate spaces, offices, and other types of spaces as needed.”
Indeed, the architects emphasize, the redesign of the Met Warehouse is not simply an overhaul; the plan significantly reflects the longtime interior structure of the building, too.
“It wasn’t just about converting the shell,” Gilmartin says. “It was about trying to find a balance and determining how much was already there [structurally] that we could use as a fabric.”
That historical fabric is evident through one of the building’s signature features: The old brick structure in key places is exposed to view, next to many places where the architects made dramatic cuts to create platforms for light-filled studio spaces. Students, designers, and visitors can see both how the old Met Warehouse was built and how the new version of it was created.
“The building itself can be a teaching tool,” Diller says. “When we did those extractions from the building, we left our intervention exposed, so there’s a kind of conversation between a contemporary strategy and the historical building. The traces are all there; they’re all revealed.”
Educators at the Institute view the building in a similar manner as they think about architectural teaching broadly.
“Our move to the Met is an exciting physical transition for the school, and an occasion for us to articulate the shifts in architectural education we have been undertaking,” says Ana Miljački, the Francis White Davis Professor at MIT and head of the Department of Architecture. “Making our home in the building will be part of our rethinking of the discipline, the profession, and our pedagogical tasks.”
Five stories, five blocks, one vision
As originally constructed, the Met Warehouse had five contiguous segments. Given that it is also five stories high, the building has 25 natural segments, in a sense. A wide range of activity will be housed inside it, including several core parts of the School of Architecture and Planning: the Department of Architecture, the Department of Urban Studies and Planning (DUSP), and the Norman B. Leventhal Center for Advanced Urbanism. (The MIT Media Lab, the Art, Culture, and Technology Program, and the Center for Real Estate, all part of the School of Architecture and Planning, will remain in their existing locations on campus.)
The MIT Morningside Academy for Design (MAD), a campus-wide center promoting interdisciplinary design work, will also be located in the Met Warehouse, helping to further establish the building as the essential hub of design and planning work on campus.
Many MIT scholars say they welcome the opportunity to bring so many related programs into greater proximity with each other, along with all the physical assets the Met Warehouse will provide.
“At MIT we have fewer boundaries, less conventions, and we bump into each other on campus,” says Jinhua Zhao, the Class of 1941 Professor and head of DUSP. “I have always appreciated this spirit since I first came here as a student and walked along the Infinite Corridor. A lot of places value interdisciplinary research. At MIT, you can’t help it happening. I believe the new Met Warehouse will expand that custom.”
Those who saw the inside of the building in its old days as a storage space, and are moving into it now, are deeply impressed by the complete readaptation of the Met Warehouse and the provision of new “commons” spaces for the campus.
“It’s almost inconceivable that this brick box, which was not designed for human habitation but to store objects, has been opened up, through the work of Diller Scofidio + Renfro,” says John Ochsendorf, the Class of 1942 Professor and director of MAD. “Our hope is you will find vibrant cross-fertilization across disciplines, across the School of Architecture and Planning, but also across all of MIT. That’s really important.”
Indeed, as Ochsendorf and others have noted, the building figures to produce its own urban dynamics within its monumental walls.
“As you go up into the building, you will find different neighborhoods concerned with different aspects of design,” Ochsendorf says. “These are all areas pushing frontiers in research and education and design of the built environment, which interact with so many of the pressing issues facing humanity. We’re excited to create new neighborhoods of inquiry with the building.”
That is certainly part of the intention, the architects say.
“There are a lot of opportunities for smaller groupings of people to be organized in ways that are visible and connected to the larger shared spaces but also offer the prospect of retreat in different places to work,” Gilmartin observes.
“The challenges facing cities cannot be addressed by any one discipline,” says Sarah Williams, director of the Norman B. Leventhal Center for Advanced Urbanism. “Innovation comes from bringing together all the fields that shape — and are shaped by — the built environment. The Met Warehouse gives us a place to work across those boundaries, inspiring new ways to imagine and build the future of our cities.”
Sarkis, for his part, professes some happy relief that the long-held conception of the Met Warehouse is finally becoming reality. The building, he thinks, will influence the flow of people through MIT’s campus, bringing a transformative multiuse space into the daily lives of students, faculty, staff, and the public.
“It is going to be a new center of gravity for the campus,” Sarkis says.
MIT News will offer a further look at the Met Warehouse’s transformative architecture in concert with the Sept. 8 procession, as well as coverage of events from the formal dedication weekend in October.