MIT researchers have developed a new method for designing 3D structures that can be transformed from a flat configuration into their curved, fully formed shape with only a single pull of a string.
This technique could enable the rapid deployment of a temporary field hospital at the site of a disaster such as a devastating tsunami — a situation where quick medical action is essential to save lives.
The researchers’ approach converts a user-specified 3D structure into a flat shape composed of interconnected tiles. The algorithm uses a two-step method to find the path with minimal friction for a string that can be tightened to smoothly actuate the structure.
The actuation mechanism is easily reversible, and if the string is released, the structure quickly returns to its flat configuration. This could enable complex, 3D structures to be stored and transported more efficiently and with less cost.
In addition, the designs generated by their system are agnostic to the fabrication method, so complete structures can be produced using 3D printing, CNC milling, molding, or other techniques.
This method could enable the creation of transportable medical devices, foldable robots that can flatten to enter hard-to-reach spaces, or even modular space habitats that can be actuated by robots working on the surface of Mars.
“The simplicity of the whole actuation mechanism is a real benefit of our approach. The user just needs to provide their intended design, and then our method optimizes it in such a way that it holds the shape after just one pull on the string, so the structure can be deployed very easily. I hope people will be able to use this method to create a wide variety of different, deployable structures,” says Akib Zaman, an electrical engineering and computer science (EECS) graduate student and lead author of a paper on this new method.
He is joined on the paper by MIT graduate student Jacqueline Aslarus; postdoc Jiaji Li; Associate Professor Stefanie Mueller, leader of the Human-Computer Interaction (HCI) Engineering Group in the Computer Science and Artificial Intelligence Laboratory (CSAIL); and senior author Mina Konaković Luković, an assistant professor and leader of the Algorithmic Design Group in CSAIL. The research was presented at the Association for Computing Machinery’s SIGGRAPH Conference and Exhibition on Computer Graphics and Interactive Techniques in Asia.
From ancient art to an algorithm
Creating deployable structures from flat pieces simplifies on-site assembly and could be especially useful in constructing emergency shelters after natural disasters. On a smaller scale, items like foldable bike helmets could improve the safety of riders who would otherwise be unable to carry a bulky helmet.
But converting flat, deployable objects into their 3D shape often requires specialized equipment or multiple steps, and the actuation mechanism is typically difficult to reverse.
“Because of these challenges, deployable structures tend to be manually designed and quite simple, geometrically. But if we can create more complex geometries, while simplifying the actuation mechanism, we could enhance the capabilities of these deployables,” Zaman says.
To do this, the researchers created a method that automatically converts a user’s 3D design into a flat structure comprised of tiles, connected by rotating hinges at the corners, which can be fully actuated by pulling a single string one time.
Their method breaks a user design into a grid of quadrilateral tiles inspired by kirigami, the ancient Japanese art of paper cutting. With kirigami, by cutting a material in certain ways, they can encode it with unique properties. In this case, they use kirigami to create an auxetic mechanism, which is a structure that gets thicker when stretched and thinner when compressed.
After encoding the 3D geometry into a flat set of auxetic tiles, the algorithm computes the minimum number of points that the tightening string must lift to fully deploy the 3D structure. Then, it finds the shortest path that connects those lift points, while including all areas of the object’s boundary that must be connected to guide the structure into its 3D configuration. It does these calculations in such a way that the optimal string path minimizes friction, enabling the structure to be smoothly actuated with just one pull.
“Our method makes it easy for the user. All they have to do is input their design, and our algorithm automatically takes care of the rest. Then all the user needs to do is to fabricate the tiles exactly the way it has been computed by the algorithm,” Zaman says.
For instance, one could fabricate a structure using a multi-material 3D printer that prints the hinges of the tiles with a flexible material and the other surfaces with a hard material.
A scale independent method
One of the biggest challenges the researchers faced was figuring out how the string route and the friction within the string channel can be effectively modeled as close to physical reality.
“While playing with a few fabricated models, we observed that closing boundary tiles is a must to enable a successful deployment and the string must be routed through them. Later, we proved this observation mathematically. Then, we looked back at an age-old physics equation and used it to formulate the optimization problem for friction minimization,” he says.
They built their automatic algorithm into an interactive user interface that allows one to design and optimize configurations to generate manufacturable objects.
The researchers used their method to design several objects of different sizes, from personalized medical items including a splint and a posture corrector to an igloo-like portable structure. They also fabricated a deployable, human-scale chair they designed using their method.
This method is scale independent, so it could be used to create tiny deployable objects that are injected and actuated inside the body, or architectural structures, like the frame of a building, that are deployed and actuated on-site using cranes.
In the future, the researchers want to further explore the design of tiny structures, while also tackling the engineering challenges involved in creating architectural installations, such as determining the ideal cable thickness and the necessary strength of the hinges. In addition, they want to create a self-deploying mechanism, so the structures do not need to be actuated by a human or robot.
This research is funded, in part, by an MIT Research Support Committee Award.
MIT in the media: 2025 in review MIT community members made headlines with key research advances and their efforts to tackle pressing challenges.“At MIT, innovation ranges from awe-inspiring technology to down-to-Earth creativity,” noted Chronicle, during a campus visit this year for an episode of the program. In 2025, MIT researchers made headlines across print publications, podcasts, and video platforms for key scientific advances, from breakthroughs in quantum and artificial intelligence to new efforts aimed at improving pediatric health care and cancer diagnosis.
MIT faculty, researchers, students, alumni and staff helped demystify new technologies, highlighted the practical hands-on learning the Institute is known for, and shared what inspires their research with viewers, readers and listeners around the world. Below is a sampling of news moments to revisit.
Let’s take a closer look at MIT: It’s alarming to see such a complex, important institution subject to the whims of today’s politics
Washington Post columnist George F. Will reflects on MIT and his view of “the damage that can be done to America’s meritocracy by policies motivated by hostility toward institutions vital to it.” Will notes that MIT has an “astonishing economic multiplier effect: MIT graduates have founded companies that have generated almost $1.9 trillion in annual revenue (a sum almost equal to Russia’s GDP) and 4.6 million jobs.”
Full story via The Washington Post
At MIT, groundbreaking ideas blend science and breast cancer detection innovation
Chronicle visited MIT this spring to learn more about how the Institute “nurtures groundbreaking efforts, reminding us that creativity and science thrive together, inspiring future advancements in engineering, medicine, and beyond.”
Full story via Chronicle
New MIT provost looks to build more bridges with CEOs
Provost Anantha Chandrakasan shares his energy and enthusiasm for MIT, and his goals for the Institute.
Full story via The Boston Globe
Five things New England researchers helped develop with federal funding
Professors John Guttag and David Mindell discuss MIT’s long history of developing foundational technologies — including the internet and the first widely used electronic navigation system — with the support of federal funding.
Full story via The Boston Globe
Bostonians of the Year 2025: First responders, university presidents, and others who exemplified courage
President Sally Kornbluth is honored by The Boston Globe as one of the Bostonians of the Year, a list that spotlights individuals across the region who, in choosing the difficult path, “showed us what strength looks like.” Kornbluth was recognized for her work being of the “most prominent voices rallying to protect academic freedom.”
Full story via The Boston Globe
Practical education and workforce preparation
College students flock to a new major: AI
MIT’s new Artificial Intelligence and Decision Making major is aimed at teaching students to “develop AI systems and study how technologies like robots interact with humans and the environment.”
Full story via New York Times
50 colleges with the best ROI
MIT has been named among the top colleges in the country for return on investment. MIT “is need-blind and full-need for undergraduate students. Six out of 10 students receive financial aid, and almost 88% of the Class of 2025 graduated debt-free.”
Full story via Boston 25
Desirée Plata: Chemist, oceanographer, engineer, entrepreneur
Professor Desirée Plata explains that she is most proud of her work as an educator. “The faculty of the world are training the next generation of researchers,” says Plata. “We need a trained workforce. We need patient chemists who want to solve important problems.”
Full story via Chemical & Engineering News
Taking a quantum leap
MIT launches quantum initiative to tackle challenges in science, health care, national security
MIT is “taking a quantum leap with the launch of the new MIT Quantum Initiative (QMIT). “There isn't a more important technological field right now than quantum with its enormous potential for impact on both fundamental research and practical problems,” said President Sally Kornbluth.
Full story via State House News Service
Peter Shor on how quantum tech can help climate
Professor Peter Shor helps disentangle quantum technologies.
Full story via The Quantum Kid
MIT researchers develop device to enable direct communication between multiple quantum processors
MIT researchers made a key advance in the creation of a practical quantum computer.
Full story via Military & Aerospace Electronics
Fortifying national security and aiding disaster response
Nano-material breakthrough could revolutionize night vision
MIT researchers developed “a new way to make large ultrathin infrared sensors that don’t need cryogenic cooling and could radically change night vision for the military.”
Full story via Defense One
MIT researchers develop robot designed to help first-responders in disaster situations
Researchers at MIT engineered SPROUT (Soft Pathfinding Robotic Observation Unit), a robot aimed at assisting first-responders.
Full story via WHDH
MIT scientists make “smart” clothes that warn you when you’re sick
As part of an effort to help keep service members safe, MIT scientists created a programmable fiber that can be stitched into clothing to help monitor the wearer’s health.
Full story via FOX 28
MIT Lincoln Lab develops ocean-mapping technology
MIT Lincoln Laboratory researchers are developing “automated electric vessels to map the ocean floor and improve search and rescue missions.”
Full story via Chronicle
Transformative tech
This MIT scientist is rewiring robots to keep the humanity in tech
Professor Daniela Rus, director of the Computer Science and Artificial Intelligence Lab, discusses her work revolutionizing the field of robotics by bringing “empathy into engineering and proving that responsibility is as radical and as commercially attractive as unguarded innovation.”
Full story via Forbes
Watch this tiny robot somersault through the air like an insect
Professor Kevin Chen designed a tiny, insect-sized aerial microrobot.
Full story via Science
It's actually really hard to make a robot, guys
Professor Pulkit Agrawal delves into his work engineering a simulator that can be used to train robots.
Full story via NPR
Shape-shifting fabrics and programmable materials redefine design at MIT
Associate Professor Skylar Tibbits is embedding intelligence into the materials around us, while Professor Caitlin Mueller and Sandy Curth PhD ’25 are digging into eco-friendly construction.
Full story via Chronicle
Building a healthier future
MIT launches pediatric research hub to address access gaps
The Hood Pediatric Innovation Hub is addressing “underinvestment in pediatric healthcare innovations.”
Full story via Boston Business Journal
Bionic knee helps amputees walk naturally again
Professor Hugh Herr developed a prosthetic that could increase mobility for above-the-knee amputees. “The bionic knee developed by MIT doesn’t just restore function, it redefines it.”
Full story via Fox News
MIT drug hunters are using AI to design completely new antibiotics
Professor James Collins is using AI to develop new compounds to combat antibiotic resistance.
Full story via Fast Company
Innovative once-weekly capsule helps quell schizophrenia symptoms
A new pill from the lab of Associate Professor Giovanni Traverso “can greatly simplify the drug schedule faced by schizophrenia patients.”
Full story via Newsmax
Renewing American manufacturing
US manufacturing is in “pretty bad shape.” MIT hopes to change that.
MIT launched the Initiative for New Manufacturing to help “build the tools and talent to shape a more productive and sustainable future for manufacturing.”
Full story via Manufacturing Dive
Giving US manufacturing a boost
Ben Armstrong of the MIT Industrial Performance Center discusses how to reinvigorate manufacturing in America.
Full story via Marketplace
New England companies are sparking an industrial revolution. Here’s how to harness it.
Professor David Mindell spotlights how “a new wave of industrial companies, many in New England, are leveraging new technologies to create jobs and empower workers.”
Full story via The Boston Globe
Improving aging
My day as an 80-year-old. What an age-simulation suit taught me.
To get a better sense of the experience of aging, Wall Street Journal reporter Amy Dockser Marcus donned the MIT AgeLab’s age-simulation suit and embarked on multiple activities.
Full story via The Wall Street Journal
New mobile robot helps seniors walk safely and prevent falls
A mobile robot created by MIT engineers is designed to help prevent falls. “It's easy to see how something like this could make a big difference for seniors wanting to stay independent.”
Full story via Fox News
The senior population is booming. Caregiving is struggling to keep up
Professor Jonathan Gruber discusses the labor shortages impacting senior care.
Full story via CNBC
Upping our energy resilience
New MIT collaboration with GE Vernova aims to accelerate energy transition
“A great amount of innovation happens in academia. We have a longer view into the future,” says Provost Anantha Chandrakasan of the MIT-GE Vernova Energy and Climate Alliance.
Full story via The Boston Globe
The environmental impacts of generative AI
Noman Bashir, a fellow with MIT’s Climate and Sustainability Consortium, explores the environmental impacts of generative AI.
Full story via Fox 13
Is the clean energy economy doomed?
Professor Christopher Knittel discusses how the U.S. can be in the best position for global energy dominance.
Full story via Marketplace
Advancing American workers
WTH can we do to prevent a second China shock? Professor David Autor explains
Professor David Autor shares his research examining the long-term impact of China entering the World Trade Organization, how the U.S. can protect vital industries from unfair trade practices, and the potential impacts of AI on workers.
Full story via American Enterprise Institute
The fight over robots threatening American jobs
Professor Daron Acemoglu highlights the economic and societal implications of integrating automation in the workforce, advocating for policies aimed at assisting workers.
Full story via Financial Times
Moving toward automation
Research Scientist Eva Ponce of the MIT Center for Transportation and Logistics notes that robotics and AI technologies are “replacing some jobs — particularly more manual tasks including heavy lifting — but have also offered new opportunities within warehouse operations.”
Full story via Financial Times
Planetary defense and out-of-this world exploration
MIT researchers create new asteroid detection methods to help protect Earth
Associate Professor Julien de Wit and Research Scientist Artem Burdanov discuss their work developing a new method to track asteroids that could impact Earth.
Full story via WBZ Radio
What happens to the bodies of NASA astronauts returning to Earth?
Professor Dava Newman speaks about how long-duration stays in space can affect the human body.
Full story via News Nation
Lunar lander Athena is packed and ready to explore the moon. Here’s what on board
MIT engineers sent three payloads into space on a course set for the moon’s south polar region.
Full story via USA Today
Scanning the heavens at the Vatican Observatory
Br. Guy Consolmagno '74, SM '75, director of the Vatican Observatory, and graduate student Isabella Macias share their experiences studying astronomy and planetary formation at the Vatican Observatory. “The Vatican has such a deep, rich history of working with astronomers,” says Macias. “It shows that science is not only for global superpowers around the world, but it's for students, it's for humanity.”
Full story via CBS News Sunday Morning
The story of real-life rocket scientists
Professor Kerri Cahoy takes viewers on an out-of-this-world journey into how a college internship inspired her research on space and satellites.
Full story via Bloomberg Television
On the air
While digital currency initiatives expand, we ask: What’s the future of cash?
Neha Narula, director of the MIT Digital Currency Initiative, examines the future of cash as the use of digital currencies expands.
Full story via USA Today
The high stakes of the AI economy
Professor Asu Ozdaglar, head of the Department of Electrical Engineering and Computer Science and deputy dean of the MIT Schwarzman College of Computing, explores AI’s opportunities and risks — and whether it can be regulated without stifling progress.
Full story via Is Business Broken?
The LIGO Lab is pushing the boundaries of gravitational-wave research
Associate Professor Matt Evans explores the future of gravitational wave research and how Cosmic Explorer, the next-generation gravitational wave observatory, will help unearth secrets of the early universe.
Full story via Scientific American
Space junk: The impact of global warming on satellites
Graduate student Will Parker discusses his research examining the impact of climate change on satellites.
Full story via USA Today
Endometriosis is common. Why is getting diagnosed so hard?
Professor Linda Griffith shares her work studying endometriosis and her efforts to improve healthcare for women.
Full story via Science Friday
There’s nothing small about this nanoscale research
Professor Vladimir Bulović takes listeners on a tour of MIT.nano, MIT’s “clean laboratory facility that is critical to nanoscale research, from microelectronics to medical nanotechnology.”
Full story via Scientific American
Marrying science and athletics
The MIT scientist behind the “torpedo bats” that are blowing up baseball
Aaron Leanhardt PhD ’03 went from an MIT graduate student who was part of a research team that “cooled sodium gas to the lowest temperature ever recorded in human history” to inventor of the torpedo baseball bat, “perhaps the most significant development in bat technology in decades.”
Full story via The Wall Street Journal
Engineering athletes redefine routine
After suffering a concussion during her sophomore year, Emiko Pope ’25 was inspired to explore the effectiveness of concussion headbands.
Full story via American Society of Mechanical Engineers
“I missed talking math with people”: why John Urschel left the NFL for MIT
Assistant Professor John Urschel shares his decision to call an audible and leave his NFL career to focus on his love for math at MIT.
Full story via The Guardian
Making a statement, MIT’s football team dons extra head padding for safety
It’s a piece of equipment that may become more widely used as research continues into its effectiveness — including from at least one of the players on the current team.
Full story via GBH Morning Edition
Agricultural efficiency
New MIT breakthrough could save farmers billions on pesticides
MIT engineers developed a system that helps pesticides adhere more effectively to plant leaves, allowing farmers to use fewer chemicals.
Full story via Michigan Farm News
Bug-sized robots could help pollination on future farms
Insect-sized robots crafted by MIT researchers could one day be used to help with farming practices like artificial pollination.
Full story via Reuters
See how MIT researchers harvest water from the air
An ultrasonic device created by MIT engineers can extract clean drinking water from atmospheric moisture.
Full story via CNN
Appreciating art
Meet the engineer using deep learning to restore Renaissance art
Graduate student Alex Kachkine talks about his work applying AI to develop a restoration method for damaged artwork.
Full story via Nature
MIT’s Linde Music Building opens with a free festival
“The extent of art-making on the MIT campus is equal to that of a major city,” says Institute Professor Marcus Thompson. “It’s a miracle that it’s all right here, by people in science and technology who are absorbed in creating a new world and who also value the past, present and future of music and the arts.”
Full story via Cambridge Day
“Remembering the Future” on display at the MIT Museum
The “Remembering the Future” exhibit at the MIT Museum features a sculptural installation that uses “climate data from the last ice age to the present, as well as projected future environments, to create a geometric design.”
Full story via The New York Times
In 2025, MIT maintained its standard of community and research excellence amidst a shift in national priorities regarding the federal funding of higher education. Notably, QS ranked MIT No. 1 in the world for the 14th straight year, while U.S. News ranked MIT No. 2 in the nation for the 5th straight year.
This year, President Sally Kornbluth also added to the Institute’s slate of community-wide strategic initiatives, with new collaborative efforts focused on manufacturing, generative artificial intelligence, and quantum science and engineering. In addition, MIT opened several new buildings and spaces, hosted a campuswide art festival, and continued its tradition of bringing the latest in science and technology to the local community and to the world. Here are some of the top stories from around MIT over the past 12 months.
MIT collaboratives
President Kornbluth announced three new Institute-wide collaborative efforts designed to foster and support alliances that will take on global problems. The Initiative for New Manufacturing (INM) will work toward bolstering industry and creating jobs by driving innovation across vital manufacturing sectors. The MIT Generative AI Impact Consortium (MGAIC), a group of industry leaders and MIT researchers, aims to harness the power of generative artificial intelligence for the good of society. And the MIT Quantum Initiative (QMIT) will leverage quantum breakthroughs to drive the future of scientific and technological progress.
These missions join three announced last year — the Climate Project at MIT, the MIT Human Insight Collaborative (MITHIC), and the MIT Health and Life Sciences Collaborative (MIT HEALS).
Sharing the wonders of science and technology
This year saw the launch of MIT Learn, a dynamic AI-enabled website that hosts nearly 13,000 non-degree learning opportunities, making it easier for learners around the world to discover the courses and resources available on MIT’s various learning platforms.
The Institute also hosted the Cambridge Science Carnival, a hands-on event managed by the MIT Museum that drew approximately 20,000 attendees and featured more than 140 activities, demonstrations, and installations tied to the topics of science, technology, engineering, arts, and mathematics (STEAM).
Commencement
At Commencement, Hank Green urged MIT’s newest graduates to focus their work on the “everyday solvable problems of normal people,” even if it is not always the easiest or most obvious course of action. Green is a popular content creator and YouTuber whose work often focuses on science and STEAM issues, and who co-created the educational media company Complexly.
President Kornbluth challenged graduates to be “ambassadors” for the open-minded inquiry and collaborative work that marks everyday life at MIT.
Top accolades
In January, the White House bestowed national medals of science and technology — the country’s highest awards for scientists and engineers — on four MIT professors and an additional alumnus. Moderna, with deep MIT roots, was also recognized.
As in past years, MIT faculty, staff, and alumni were honored with election to the various national academies: the National Academy of Sciences, the National Academy of Engineering, the National Academy of Medicine, and the National Academy of Inventors.
Faculty member Carlo Ratti served as curator of the Venice Biennale’s 19th International Architecture Exhibition.
Members of MIT Video Productions won a New England Emmy Award for their short film on the art and science of hand-forged knives with master bladesmith Bob Kramer.
And at MIT, Dimitris Bertsimas, vice provost for open learning and a professor of operations research, won this year’s Killian Award, the Institute’s highest faculty honor.
New and refreshed spaces
In the heart of campus, the Edward and Joyce Linde Music Building became fully operational to start off the year. In celebration, the Institute hosted Artfinity, a vibrant multiweek exploration of art and ideas, with more than 80 free performing and visual arts events including a film festival, interactive augmented-reality art installations, a simulated lunar landing, and concerts by both student groups and internationally renowned musicians.
Over the summer, the “Outfinite” — the open space connecting Hockfield Court with Massachusetts Avenue — was officially named the L. Rafael Reif Innovation Corridor in honor of President Emeritus L. Rafael Reif, MIT’s 17th president.
And in October, the Undergraduate Advising Center’s bright new home opened in Building 11 along the Infinite Corridor, bringing a welcoming and functional destination for MIT undergraduate students within the Institute’s Main Group.
Student honors and awards
MIT undergraduates earned an impressive number of prestigious awards in 2025. Exceptional students were honored with Rhodes, Gates Cambridge, and Schwarzman scholarships, among others.
A number of MIT student-athletes also helped to secure their team’s first NCAA national championship in Institute history: Women’s track and field won both the indoor national championship and outdoor national championship, while women’s swimming and diving won their national title as well.
Also for the fifth year in a row, MIT students earned all five top spots at the Putnam Mathematical Competition.
Leadership transitions
Several senior administrative leaders took on new roles in 2025. Anantha Chandrakasan was named provost; Paula Hammond was named dean of the School of Engineering; Richard Locke was named dean of the MIT Sloan School of Management; Gaspare LoDuca was named vice president for information systems and technology and CIO; Evelyn Wang was named vice president for energy and climate; and David Darmofal was named vice chancellor for undergraduate and graduate education.
Additional new leadership transitions include: Ana Bakshi was named executive director of the Martin Trust Center for MIT Entrepreneurship; Fikile Brushett was named director of the David H. Koch School of Chemical Engineering Practice; Laurent Demanet was named co-director of the Center for Computational Science and Engineering; Rohit Karnik was named director of the Abdul Latif Jameel Water and Food Systems Lab; Usha Lee McFarling was named director of the Knight Science Journalism Program; C. Cem Tasan was named director of the Materials Research Laboratory; and Jessika Trancik was named director of the Sociotechnical Systems Research Center.
Remembering those we lost
Among MIT community members who died this year were David Baltimore, Juanita Battle, Harvey Kent Bowen, Stanley Fischer, Frederick Greene, Lee Grodzins, John Joannopoulos, Keith Johnson, Daniel Kleppner, Earle Lomon, Nuno Loureiro, Victor K. McElheny, David Schmittlein, Anthony Sinskey, Peter Temin, Barry Vercoe, Rainer Weiss, Alan Whitney, and Ioannis Yannas.
In case you missed it…
Additional top stories from around the Institute in 2025 include a description of the environmental and sustainability implications of generative AI tech and applications; the story of how an MIT professor introduced hundreds of thousands of students to neuroscience with his classic textbook; a look at how MIT entrepreneurs are using AI; a roundup of new books by MIT faculty and staff; and behind the scenes with MIT students who cracked a longstanding egg dilemma.
MIT’s top research stories of 2025Concrete batteries, AI-developed antibiotics, the ozone’s recovery, and a more natural bionic knee were some of the most popular topics on MIT News.In 2025, MIT’s research community had another prolific year filled with exciting scientific and technological advances. To celebrate the achievements of the past 12 months, MIT News highlights some of our most-read stories from this year.
In 2013, Martin Trust Center for MIT Entrepreneurship Managing Director Bill Aulet published “Disciplined Entrepreneurship: 24 Steps to a Successful Startup,” which has since sold hundreds of thousands of copies and been used to teach entrepreneurship at universities around the world. One MIT course where it’s used is 15.366 (Climate and Energy Ventures), where instructors have tweaked the framework over the years. In a new book, “Disciplined Entrepreneurship for Climate and Energy Ventures,” they codify those changes and provide a new blueprint for entrepreneurs working in the climate and energy spaces.
MIT News spoke with lead author and Trust Center Entrepreneur-in-Residence Ben Soltoff, who wrote the book with Aulet, Senior Lecturer Tod Hynes, Senior Lecturer Francis O’Sullivan, and Lecturer Libby Wayman. Soltoff explains why climate and energy entrepreneurship is so challenging and talks about some of the new steps in the book.
Q: What are climate and energy ventures?
A: It’s a broad umbrella. These ventures aren’t all in a specific industry or structured in the same way. They could be software, they could be hardware, or they could be deep tech coming out of labs. This book is also written for people working in government, large corporations, or nonprofits. Each of those folks can benefit from the entrepreneurial framework in this book. We very intentionally refer to them as climate and energy ventures in the book, not just climate and energy startups.
One common theme is meeting the challenge of providing enough energy for current and future needs without exacerbating, or even while reducing, the impact we have on our planet. Generally, climate and energy ventures are less likely to be only software. Many of the solutions we need are around molecules, not bits. A lot of it is breakthrough technology and science from research labs. You could be making a useful fuel, removing CO2 from the atmosphere, or delivering something in a novel way. Your venture might produce a chemical or molecule that’s already being provided and is a commodity. It needs to be not only more sustainable, but better for your customers — either cheaper, more reliable, or more securely delivered. Ultimately, all of these ventures have to provide value. They also often involve physical infrastructure that you have to scale up — not just 10 times or 100 times, but 1,000 times or more — from original lab demonstrations.
Q: How should climate and energy entrepreneurs be thinking about navigating financing and working with the government?
A: One of the major themes of the book is the importance of figuring out if policy is in your favor and constantly applying a policy lens to what you’re building. Finance is another major theme. In climate and energy, these things are fundamental, and we need to consider them from the beginning. We talk about different “valleys of death” — the idea that going from one stage to the next stage requires this jump in time and resources that presents a big challenge. That also relates to the jump in scale of the technology, from a lab scale to something you can produce and sell in a quantity and at a cost the market is interested in. All of that requires financing.
At an early stage, a lot of these ventures are funded through grants and research funding. Later, they start getting early-stage capital — often venture capital. Eventually, as folks are scaling, they move to debt and project financing. Companies need to be very intentional about the type of financing they’re going to pursue and at what stage. We have an entire step on creating a long-term capital plan. Entrepreneurs need to be very clear about the story they’re going to tell investors at different stages. Otherwise, they can paint themselves into a corner and fail to build a company for the next stage of capital they need.
In terms of policy, entrepreneurs should use the policy environment as a filter for selecting a market. We have a story in the book about a startup that switched from working in sub-Saharan Africa to the U.S. after the Inflation Reduction Act passed. As those incentives began disappearing, they still had the option to return to their original market. It’s not ideal for them, but they are still able to build profitable projects. You shouldn’t build a company based on the incentives alone, but you should understand which way the wind is blowing and take advantage of policy when it’s in your favor. That said, policy can always change.
Q: How should climate and energy entrepreneurs select the right market “stepping stones”?
A: Each of the “Disciplined Entrepreneurship” books talks about the importance of selecting customers and listening to your customers. When thinking about their beachhead market, or where to initially focus, climate and energy entrepreneurs need to look for the easiest near-term opportunity to plug in their technology. Subsequent market selection is also driven by technology. Instead of just picking a beachhead market and figuring everything else out later, there often needs to be an intentional choice of what we call market stepping stones. You start by focusing on an initial market in the early days — land and expand — but there needs to be a long-term strategy, so you don’t go down a dead end. These ventures don’t have a lot of flexibility as they build out potentially expensive technologies. Being intentional means having a pathway planned from the beachhead market up to the big prize that makes the entire enterprise worthwhile. The prize means having a big impact but also targeting a big market opportunity.
We have an example in the book of a company that can turn CO2 into useful products. They knew the big prize was turning it into fuel, most likely aviation fuel, but they couldn’t produce at the right volume or cost early on, so they looked at other applications. They started with making vodka from CO2 because it was low-volume and high-margin. Then the pandemic happened, so they made hand sanitizer. Then they made perfume, which had the highest margins of all. By that point, they were ready to start moving into the fuel market. The stepping stones are about figuring out who is willing to buy the simple version of your technology or product and pay a premium. Initially, looking at that company, you might say, “They’re not going to save the planet by selling vodka.” But it was a critical stepping stone to get to the big prize. Long-term thinking is essential for ventures in this space.
Study: High-fat diets make liver cells more likely to become cancerousNew research suggests liver cells exposed to too much fat revert to an immature state that is more susceptible to cancer-causing mutations.One of the biggest risk factors for developing liver cancer is a high-fat diet. A new study from MIT reveals how a fatty diet rewires liver cells and makes them more prone to becoming cancerous.
The researchers found that in response to a high-fat diet, mature hepatocytes in the liver revert to an immature, stem-cell-like state. This helps them to survive the stressful conditions created by the high-fat diet, but in the long term, it makes them more likely to become cancerous.
“If cells are forced to deal with a stressor, such as a high-fat diet, over and over again, they will do things that will help them survive, but at the risk of increased susceptibility to tumorigenesis,” says Alex K. Shalek, director of the Institute for Medical Engineering and Sciences (IMES), the J. W. Kieckhefer Professor in IMES and the Department of Chemistry, and a member of the Koch Institute for Integrative Cancer Research at MIT, the Ragon Institute of MGH, MIT, and Harvard, and the Broad Institute of MIT and Harvard.
The researchers also identified several transcription factors that appear to control this reversion, which they believe could make good targets for drugs to help prevent tumor development in high-risk patients.
Shalek; Ömer Yilmaz, an MIT associate professor of biology and a member of the Koch Institute; and Wolfram Goessling, co-director of the Harvard-MIT Program in Health Sciences and Technology, are the senior authors of the study, which appears today in Cell. MIT graduate student Constantine Tzouanas, former MIT postdoc Jessica Shay, and Massachusetts General Brigham postdoc Marc Sherman are the co-first authors of the paper.
Cell reversion
A high-fat diet can lead to inflammation and buildup of fat in the liver, a condition known as steatotic liver disease. This disease, which can also be caused by a wide variety of long-term metabolic stresses such as high alcohol consumption, may lead to liver cirrhosis, liver failure, and eventually cancer.
In the new study, the researchers wanted to figure out just what happens in cells of the liver when exposed to a high-fat diet — in particular, which genes get turned on or off as the liver responds to this long-term stress.
To do that, the researchers fed mice a high-fat diet and performed single-cell RNA-sequencing of their liver cells at key timepoints as liver disease progressed. This allowed them to monitor gene expression changes that occurred as the mice advanced through liver inflammation, to tissue scarring and eventually cancer.
In the early stages of this progression, the researchers found that the high-fat diet prompted hepatocytes, the most abundant cell type in the liver, to turn on genes that help them survive the stressful environment. These include genes that make them more resistant to apoptosis and more likely to proliferate.
At the same time, those cells began to turn off some of the genes that are critical for normal hepatocyte function, including metabolic enzymes and secreted proteins.
“This really looks like a trade-off, prioritizing what’s good for the individual cell to stay alive in a stressful environment, at the expense of what the collective tissue should be doing,” Tzouanas says.
Some of these changes happened right away, while others, including a decline in metabolic enzyme production, shifted more gradually over a longer period. Nearly all of the mice on a high-fat diet ended up developing liver cancer by the end of the study.
When cells are in a more immature state, it appears that they are more likely to become cancerous if a mutation occurs later on, the researchers say.
“These cells have already turned on the same genes that they’re going to need to become cancerous. They’ve already shifted away from the mature identity that would otherwise drag down their ability to proliferate,” Tzouanas says. “Once a cell picks up the wrong mutation, then it’s really off to the races and they’ve already gotten a head start on some of those hallmarks of cancer.”
The researchers also identified several genes that appear to orchestrate the changes that revert hepatocytes to an immature state. While this study was going on, a drug targeting one of these genes (thyroid hormone receptor) was approved to treat a severe form of steatotic liver disease called MASH fibrosis. And, a drug activating an enzyme that they identified (HMGCS2) is now in clinical trials to treat steatotic liver disease.
Another possible target that the new study revealed is a transcription factor called SOX4, which is normally only active during fetal development and in a small number of adult tissues (but not the liver).
Cancer progression
After the researchers identified these changes in mice, they sought to discover if something similar might be happening in human patients with liver disease. To do that, they analyzed data from liver tissue samples removed from patients at different stages of the disease. They also looked at tissue from people who had liver disease but had not yet developed cancer.
Those studies revealed a similar pattern to what the researchers had seen in mice: The expression of genes needed for normal liver function decreased over time, while genes associated with immature states went up. Additionally, the researchers found that they could accurately predict patients’ survival outcomes based on an analysis of their gene expression patterns.
“Patients who had higher expression of these pro-cell-survival genes that are turned on with high-fat diet survived for less time after tumors developed,” Tzouanas says. “And if a patient has lower expression of genes that support the functions that the liver normally performs, they also survive for less time.”
While the mice in this study developed cancer within a year or so, the researchers estimate that in humans, the process likely extends over a longer span, possibly around 20 years. That will vary between individuals depending on their diet and other risk factors such as alcohol consumption or viral infections, which can also promote liver cells’ reversion to an immature state.
The researchers now plan to investigate whether any of the changes that occur in response to a high-fat diet can be reversed by going back to a normal diet, or by taking weight-loss drugs such as GLP-1 agonists. They also hope to study whether any of the transcription factors they identified could make good targets for drugs that could help prevent diseased liver tissue from becoming cancerous.
“We now have all these new molecular targets and a better understanding of what is underlying the biology, which could give us new angles to improve outcomes for patients,” Shalek says.
The research was funded, in part, by a Fannie and John Hertz Foundation Fellowship, a National Science Foundation Graduate Research Fellowship, the National Institutes of Health, and the MIT Stem Cell Initiative through Foundation MIT.
Study: More eyes on the skies will help planes reduce climate-warming contrailsImages from geostationary satellites alone aren’t enough to help planes avoid contrail-prone regions, MIT researchers report.Aviation’s climate impact is partly due to contrails — condensation that a plane streaks across the sky when it flies through icy and humid layers of the atmosphere. Contrails trap heat that radiates from the planet’s surface, and while the magnitude of this impact is uncertain, several studies suggest contrails may be responsible for about half of aviation’s climate impact.
Pilots could conceivably reduce their planes’ climate impact by avoiding contrail-prone regions, similarly to making altitude adjustments to avoid turbulence. But to do so requires knowing where in the sky contrails are likely to form.
To make these predictions, scientists are studying images of contrails that have formed in the past. Images taken by geostationary satellites are one of the main tools scientists use to develop contrail identification and avoidance systems.
But a new study shows there are limits to what geostationary satellites can see. MIT engineers analyzed contrail images taken with geostationary satellites, and compared them with images of the same areas taken by low-Earth-orbiting (LEO) satellites. LEO satellites orbit the Earth at lower altitudes and therefore can capture more detail. However, since LEO satellites only snap an image as they fly by, they capture images of the same area far less frequently than geostationary (GEO) satellites, which continuously image the same region of the Earth every few minutes.
The researchers found that geostationary satellites miss about 80 percent of the contrails that appear in LEO imagery. Geostationary satellites mainly see larger contrails that have had time to grow and spread across the atmosphere. The many more contrails that LEO satellites can pick up are often shorter and thinner. These finer threads likely formed immediately from a plane’s engines and are still too small or otherwise not distinct enough for geostationary satellites to discern.
The study highlights the need for a multiobservational approach in developing contrail identification and avoidance systems. The researchers emphasize that both GEO and LEO satellite images have their strengths and limitations. Observations from both sources, as well as images taken from the ground, could provide a more complete picture of contrails and how they evolve.
“With more ‘eyes’ on the sky, we could start to see what a contrail’s life looks like,” says Prakash Prashanth, a research scientist in MIT’s Department of Aeronautics and Astronautics (AeroAstro). “Then you can understand what are its radiative properties over its entire life, and when and why a contrail is climatically important.”
The new study appears today in the journal Geophysical Research Letters. The study’s MIT co-authors include first author Marlene Euchenhofer, a graduate student in AeroAstro; Sydney Parke, an undergraduate student; Ian Waitz, the Jerome C. Hunsaker Professor of Aeronautics and Astronautics and MIT’s vice president of research; and Sebastian Eastham of Imperial College London.
Imaging backbone
Contrails form when the exhaust from planes meets icy, humid air, and the particles from the exhaust act as seeds on which water vapor collects and freezes into ice crystals. As a plane moves forward, it leaves a trail of condensation in its wake that starts as a thin thread that can grow and spread over large distances, lasting for several hours before dissipating.
When it persists, a contrail acts similar to an ice cloud and, as such, can have two competing effects: one in which the contrail is a sort of heat shield, reflecting some incoming radiation from the sun. On the other hand, a contrail can also act as a blanket, absorbing and reflecting back some of the heat from the surface. During the daytime, when the sun is shining, contrails can have both heat shielding and trapping effects. At night, the cloud-like threads have only a trapping, warming effect. On balance, studies have shown that contrails as a whole contribute to warming the planet.
There are multiple efforts underway to develop and test aircraft contrail-avoidance systems to reduce aviation’s climate-warming impact. And scientists are using images of contrails from space to help inform those systems.
“Geostationary satellite images are the workhorse of observations for detecting contrails,” says Euchenhofer. “Because they are at 36,000 kilometers above the surface, they can cover a wide area, and they look at the same point day and night so you can get new images of the same location every five minutes.”
But what they bring in rate and coverage, geostationary satellites lack in clarity. The images they take are about one-fifth the resolution of those taken by LEO satellites. This wouldn’t be a surprise to most scientists. But Euchenhofer wondered how different the geostationary and LEO contrail pictures would look, and what opportunities there might be to improve the picture if both sources could be combined.
“We still think geostationary satellites are the backbone of observation-based avoidance because of the spatial coverage and the high frequency at which we get an image,” she says. “We think that the data could be enhanced if we include observations from LEO and other data sources like ground-based cameras.”
Catching the trail
In their new study, the researchers analyzed contrail images from two satellite imagers: the Advanced Baseline Imager (ABI) aboard a geostationary satellite that is typically used to observe contrails and the higher-resolution Visible Infrared Radiometer Suite (VIIRS), an instrument onboard several LEO satellites.
For each month from December 2023 to November 2024, the team picked out an image of the contiguous United States taken by VIIRS during its flyby. They found corresponding images of the same location, taken at about the same time of day by the geostationary ABI. The images were taken in the infrared spectrum and represented in false color, which enabled the researchers to more easily identify contrails that formed during both the day and night. The researchers then worked by eye, zooming in on each image to identify, outline, and label each contrail they could see.
When they compared the images, they found that GEO images missed about 80 percent of the contrails observed in the LEO images. They also assessed the length and width of contrails in each image and found that GEO images mostly captured larger and longer contrails, while LEO images could also discern shorter, smaller contrails.
“We found 80 percent of the contrails we could see with LEO satellites, we couldn’t see with GEO imagers,” says Prashanth, who is the executive officer of MIT’s Laboratory for Aviation and the Environment. “That does not mean that 80 percent of the climate impact wasn’t captured. Because the contrails we see with GEO imagers are the bigger ones that likely have a bigger climate effect.”
Still, the study highlights an opportunity.
“We want to make sure this message gets across: Geostationary imagers are extremely powerful in terms of the spatial extent they cover and the number of images we can get,” Euchenhofer says. “But solely relying on one instrument, especially when policymaking comes into play, is probably too incomplete a picture to inform science and also airlines regarding contrail avoidance. We really need to fill this gap with other sensors.”
The team says other sensors could include networks of cameras on the ground that under ideal conditions can spot contrails as planes form them in real time. These smaller, “younger” contrails are typically missed by geostationary satellites. Once scientists have these ground-based data, they can match the contrail to the plane and use the plane’s flight data to identify the exact altitude at which the contrail appears. They could then track the contrail as it grows and spreads through the atmosphere, using geostationary images. Eventually, with enough data, scientists could develop an accurate forecasting model, in real time, to predict whether a plane is heading toward a region where contrails might form and persist, and how it could change its altitude to avoid the region.
“People see contrail avoidance as a near-term and cheap opportunity to attack one of the hardest-to-abate sectors in transportation,” Prashanth says. “We don’t have a lot of easy solutions in aviation to reduce our climate impact. But it is premature to do so until we have better tools to determine where in the atmosphere contrails will form, to understand their relative impacts and to verify avoidance outcomes. We have to do this in a careful and rigorous manner, and this is where a lot of these pieces come in.”
This work was supported, in part, by the U.S. Federal Aviation Administration Office of Environment and Energy.
Anything-goes “anyons” may be at the root of surprising quantum experimentsMIT physicists say these quasiparticles may explain how superconductivity and magnetism can coexist in certain materials.In the past year, two separate experiments in two different materials captured the same confounding scenario: the coexistence of superconductivity and magnetism. Scientists had assumed that these two quantum states are mutually exclusive; the presence of one should inherently destroy the other.
Now, theoretical physicists at MIT have an explanation for how this Jekyll-and-Hyde duality could emerge. In a paper appearing today in the Proceedings of the National Academy of Sciences, the team proposes that under certain conditions, a magnetic material’s electrons could splinter into fractions of themselves to form quasiparticles known as “anyons.” In certain fractions, the quasiparticles should flow together without friction, similar to how regular electrons can pair up to flow in conventional superconductors.
If the team’s scenario is correct, it would introduce an entirely new form of superconductivity — one that persists in the presence of magnetism and involves a supercurrent of exotic anyons rather than everyday electrons.
“Many more experiments are needed before one can declare victory,” says study lead author Senthil Todadri, the William and Emma Rogers Professor of Physics at MIT. “But this theory is very promising and shows that there can be new ways in which the phenomenon of superconductivity can arise.”
What’s more, if the idea of superconducting anyons can be confirmed and controlled in other materials, it could provide a new way to design stable qubits — atomic-scale “bits” that interact quantum mechanically to process information and carry out complex computations far more efficiently than conventional computer bits.
“These theoretical ideas, if they pan out, could make this dream one tiny step within reach,” Todadri says.
The study’s co-author is MIT physics graduate student Zhengyan Darius Shi.
“Anything goes”
Superconductivity and magnetism are macroscopic states that arise from the behavior of electrons. A material is a magnet when electrons in its atomic structure have roughly the same spin, or orbital motion, creating a collective pull in the form of a magnetic field within the material as a whole. A material is a superconductor when electrons passing through, in the form of voltage, can couple up in “Cooper pairs.” In this teamed-up state, electrons can glide through a material without friction, rather than randomly knocking against its atomic latticework.
For decades, it was thought that superconductivity and magnetism should not co-exist; superconductivity is a delicate state, and any magnetic field can easily sever the bonds between Cooper pairs. But earlier this year, two separate experiments proved otherwise. In the first experiment, MIT’s Long Ju and his colleagues discovered superconductivity and magnetism in rhombohedral graphene — a synthesized material made from four or five graphene layers.
“It was electrifying,” says Todadri, who recalls hearing Ju present the results at a conference. “It set the place alive. And it introduced more questions as to how this could be possible.”
Shortly after, a second team reported similar dual states in the semiconducting crystal molybdenium ditelluride (MoTe2). Interestingly, the conditions in which MoTe2 becomes superconductive happen to be the same conditions in which the material exhibits an exotic “fractional quantum anomalous Hall effect,” or FQAH — a phenomenon in which any electron passing through the material should split into fractions of itself. These fractional quasiparticles are known as “anyons.”
Anyons are entirely different from the two main types of particles that make up the universe: bosons and fermions. Bosons are the extroverted particle type, as they prefer to be together and travel in packs. The photon is the classic example of a boson. In contrast, fermions prefer to keep to themselves, and repel each other if they are too near. Electrons, protons, and neutrons are examples of fermions. Together, bosons and fermions are the two major kingdoms of particles that make up matter in the three-dimensional universe.
Anyons, in contrast, exist only in two-dimensional space. This third type of particle was first predicted in the 1980s, and its name was coined by MIT’s Frank Wilczek, who meant it as a tongue-in-cheek reference to the idea that, in terms of the particle’s behavior, “anything goes.”
A few years after anyons were first predicted, physicists such as Robert Laughlin PhD ’79, Wilczek, and others also theorized that, in the presence of magnetism, the quasiparticles should be able to superconduct.
“People knew that magnetism was usually needed to get anyons to superconduct, and they looked for magnetism in many superconducting materials,” Todadri says. “But superconductivity and magnetism typically do not occur together. So then they discarded the idea.”
But with the recent discovery that the two states can, in fact, peacefully coexist in certain materials, and in MoTe2 in particular, Todadri wondered: Could the old theory, and superconducting anyons, be at play?
Moving past frustration
Todadri and Shi set out to answer that question theoretically, building on their own recent work. In their new study, the team worked out the conditions under which superconducting anyons could emerge in a two-dimensional material. To do so, they applied equations of quantum field theory, which describes how interactions at the quantum scale, such as the level of individual anyons, can give rise to macroscopic quantum states, such as superconductivity. The exercise was not an intuitive one, since anyons are known to stubbornly resist moving, let alone superconducting, together.
“When you have anyons in the system, what happens is each anyon may try to move, but it’s frustrated by the presence of other anyons,” Todadri explains. “This frustration happens even if the anyons are extremely far away from each other. And that’s a purely quantum mechanical effect.”
Even so, the team looked for conditions in which anyons might break out of this frustration and move as one macroscopic fluid. Anyons are formed when electrons splinter into fractions of themselves under certain conditions in two-dimensional, single-atom-thin materials, such as MoTe2. Scientists had previously observed that MoTe2 exhibits the FQAH, in which electrons fractionalize, without the help of an external magnetic field.
Todadri and Shi took MoTe2 as a starting point for their theoretical work. They modeled the conditions in which the FQAH phenomenon emerged in MoTe2, and then looked to see how electrons would splinter, and what types of anyons would be produced, as they theoretically increased the number of electrons in the material.
They noted that, depending on the material’s electron density, two types of anyons can form: anyons with either 1/3 or 2/3 the charge of an electron. They then applied equations of quantum field theory to work out how either of the two anyon types would interact, and found that when the anyons are mostly of the 1/3 flavor, they are predictably frustrated, and their movement leads to ordinary metallic conduction. But when anyons are mostly of the 2/3 flavor, this particular fraction encourages the normally stodgy anyons to instead move collectively to form a superconductor, similar to how electrons can pair up and flow in conventional superconductors.
“These anyons break out of their frustration and can move without friction,” Todadri says. “The amazing thing is, this is an entirely different mechanism by which a superconductor can form, but in a way that can be described as Cooper pairs in any other system.”
Their work revealed that superconducting anyons can emerge at certain electron densities. What’s more, they found that when superconducting anyons first emerge, they do so in a totally new pattern of swirling supercurrents that spontaneously appear in random locations throughout the material. This behavior is distinct from conventional superconductors and is an exotic state that experimentalists can look for as a way to confirm the team’s theory. If their theory is correct, it would introduce a new form of superconductivity, through the quantum interactions of anyons.
“If our anyon-based explanation is what is happening in MoTe2, it opens the door to the study of a new kind of quantum matter which may be called ‘anyonic quantum matter,’” Todadri says. “This will be a new chapter in quantum physics.”
This research was supported, in part, by the National Science Foundation.
Statement on Professor Nuno Loureiro"We are grateful to all who played a part in identifying and tracking down the suspect in the killing of Prof. Loureiro. Our community continues to mourn and remember Nuno — an incredible scientist, colleague, mentor, and friend. Our thoughts are also with the Brown University community, which suffered so much loss this week.As the authorities work to answer remaining questions, our continuing position is to refer to the law enforcement agencies and the U.S. Attorney of Massachusetts for information.
For now, our focus is on our community, on Nuno’s family, and all those who knew him.”
Remembering Nuno
Students can take many possible routes through MIT’s curriculum, which can zigag through different departments, linking classes and disciplines in unexpected ways. With so many options, charting an academic path can be overwhelming, but a new tool called NerdXing is here to help.
The brainchild of senior Julianna Schneider and other students in the MIT Schwarzman College of Computing Undergraduate Advisory Group (UAG), NerdXing lets students search for a class and see all the other classes students have gone on to take in the past, including options that are off the beaten track.
“I hope that NerdXing will democratize course knowledge for everyone,” Schneider says. “I hope that for anyone who's a freshman and maybe hasn't picked their major yet, that they can go to NerdXing and start with a class that they would maybe never consider — and then discover that, ‘Oh wait, this is perfect for this really particular thing I want to study.’”
As a student double-majoring in artificial intelligence and decision-making and in mathematics, and doing research in the Biomimetic Robotics Laboratory in the Department of Mechanical Engineering, Schneider knows the benefits of interdisciplinary studies. It’s a part of the reason why she joined the UAG, which advises the MIT Schwarzman College of Computing’s leadership as it advances education and research at the intersections between computing, engineering, the arts, and more.
Through all of her activities, Schneider seeks to make people’s lives better through technology.
“This process of finding a problem in my community and then finding the right technology to solve that — that sort of approach and that framework is what guides all the things I do,” Schneider says. “And even in robotics, the things that I care about are guided by the sort of skills that I think we need to develop to be able to have meaningful applications.”
From Albania to MIT
Before she ever touched a robot or wrote code, Schneider was an accomplished young classical pianist in Albania. When she discovered her passion for robotics at age 13, she applied some of the skills she had learned while playing piano.
“I think on some fundamental level, when I was a pianist, I thought constantly about my motor dynamics as a human being, and how I execute really complex skills but do it over and over again at the top of my ability,” Schneider says. “When it came to robotics, I was building these robotic arms that also had to operate at the top of their ability every time and do really complex tasks. It felt kind of similar to me, like a fun crossover.”
Schneider joined her high school’s robotics team as a middle schooler, and she was so immediately enamored that she ended up taking over most of the coding and building of the team’s robot. She went on to win 14 regional and national awards across the three teams she led throughout middle and high school. It was clear to her that she’d found her calling.
NerdXing wasn’t Schneider’s first experience building new technology. At just 16, she built an app meant to connect English-speaking volunteers from her international school in Tirana, Albania, to local charities that only posted jobs in Albanian. By last year, the platform, called VoluntYOU, had 18 ambassadors across four continents. It has enabled volunteers to give out more than 2,000 burritos in Reno, Nevada; register hundreds of signatures to support women’s rights legislation in Albania; and help with administering Covid-19 vaccines to more than 1,200 individuals a day in Italy.
Schneider says her experience at an international school encouraged her to recognize problems and solutions all around her.
“When I enter a new community and I can immediately be like, ‘Oh wait, if we had this tool, that would be so cool and that would help all these people,’ I think that’s just a derivative of having grown up in a place where you hear about everyone’s super different life experiences,” she says.
Schneider describes NerdXing as a continuation of many of the skills she picked up while building VoluntYOU.
“They were both motivated by seeing a challenge where I thought, ‘Wait, we have the tech skills to build that. This is something that I can envision the solution to.’ And then I wanted to actually go and make that a reality,” Schneider says.
Robotics with a positive impact
At MIT, Schneider started working in the Biomimetic Robotics Laboratory of Professor Sangbae Kim, where she has now participated in three research projects, one of which she’s co-authoring a paper on. She’s part of a team that tests how robots, including the famous back-flipping mini cheetah, move, in order to see how they could complement humans in high-stakes scenarios.
Most of her work has revolved around crafting controllers, including one hybrid-learning and model-based controller that is well-suited to robots with limited onboard computing capacity. It would allow the robot to be used in regions with less access to technology.
“It’s not just doing technology for technology's sake, but because it will bridge out into the world and make a positive difference. I think legged robotics have some of the best potential to actually be a robotic partner to human beings in the scenarios that are most high-stakes,” Schneider says.
Schneider hopes to further robotic capabilities so she can find applications that will service communities around the world. One of her goals is to help create tools that allow a surgeon to operate on a patient a long distance away.
To take a break from academics, Schneider has channeled her love of the arts into MIT’s vibrant social dancing scene. This year, she’s especially excited about country line dancing events where the music comes on and students have to guess the choreography.
“I think it's a really fun way to make friends and to connect with the community,” she says.
Q&A: The secret sauce behind successful collegiate diningAndrew Mankus, MIT’s award-winning director of dining, describes why leading with a “students-first mentality” leads to better food offerings for the entire community.MIT Director of Dining Andrew Mankus has been serving the Institute community since his arrival on campus in June. He brings a wealth of energy and experience — and a problem-solver’s sensibilities — to food service at MIT. Most recently, he led dining at the University of Massachusetts at Amherst, which has won the top prize in student dining nine years in a row. Prior to that, Mankus worked in civic centers and large commissaries, among other dining environments. In this Q&A, Mankus speaks about what makes a standout dining environment on a college campus, his tenure so far at MIT, and some dining plans for the near future.
Q: What’s the secret sauce to success in academic dining?
A: You start with the obvious thing: The food’s got to be good. You can’t just serve pizza and chicken tenders, but you also can’t leave them out — students want and need their comfort food.
Students also want food that’s authentic. The dining hall is like their home away from home on campus. So if you’re calling something “Northern Indian,” it can’t taste like Southern Indian, because the student from Northern India knows exactly how it’s supposed to taste. And if someone tells me it doesn’t taste like what they had at home, I need to ask, “How should it taste? Let’s talk to our chefs.” Students should see that we’re willing to do that, willing to go there for them.
Collegiate dining is not like anything else in the food industry, because we are an integral part of the whole campus-life experience. We look at how dining can help build community around food and how to elevate cultural aspects and authenticity through food.
Q: How do you manage authenticity at a large scale?
A: It sounds silly, but it’s really one meal at a time. But as somebody who comes from an operations background, it’s also about standard operating procedures. We follow recipes, we know how many people are coming through the door, we know how much to prep — a whole bunch of things. You need to know how many students like certain things and how to be ready for them — so when you’re cooking things like stir fries, students can customize their own ingredients. It turns out you can cook something hot and fresh and make it authentic at the same time.
I like to tell people I didn’t go to school for culinary. I went to school for management. So basically, I’m a professional problem-solver. I just found my passion in food service. I like to solve problems, and MIT likes to solve problems. What better place to have this skill set?
Q: What were your first impressions of dining at MIT?
A: The thing about MIT is: The product is here. We just need to do the things we should be doing here — like integrating technology, providing service, updating meal plans, and the like — and do them better. There’s nothing Earth-shattering about it. We just need to elevate our program to new levels.
I will say, the geography of MIT’s campus is a real challenge. Many colleges have dining programs that are built around concentrated residential housing. This lets them serve a lot of meals in fewer locations. MIT has 11 dorms spread across campus. There are six dining halls and a dozen retail locations. Students who live on the west side of campus are often on east campus, away from their dining halls and meal plans, for most of the day. It’s a complicated landscape, and none of it is easy to change.
Q: What are your biggest lessons so far?
A: To start with: Every college student has limited time, and MIT students are certainly busy. In addition to course work, pretty much everybody is involved in an extracurricular activity or athletics for a couple of hours.
This is where campus dining can help. When students only have a 30-minute window between classes, we need to figure out how to feed them. If we can figure this out, it’s a win — and if we can do that with their meal plan, they’ll be more likely to eat on campus.
I’m also starting to understand MIT students’ value equation. That’s always the No. 1 thing — and I’m not just talking about the price of a meal plan. Value could mean a lot of different things. It definitely could be the cash, but it could also be quality, access, nutrition, convenience, operating hours, using swipes — whatever. I want to know how to make their meal plan as valuable to them as possible.
I don’t have the data for MIT just because I haven’t been here long enough, but it’s broadly true that college students eat a little more often than four times a day. They snack. They graze. Here, students don’t have the same options because of their schedules, the meal plans, and geography. We need to figure out where MIT students are and try to meet them there.
Basically, I want campus dining to lead with a students-first mentality. Does this or that idea bring value? Does it contribute to campus life and the student experience? If the answer is yes, then we move on to the next step. Let’s put all the ideas on the table, and let’s be transparent and tell the students: There are going to be things we try that work, and some things we try that might not.
Q: What’s an example of something you’ve tried since you got here?
A: I’ll give you three. First, we started a new grab-and-go lunch program in Baker. That’s very popular.
Second, we ran a promotion to give away MIT Dining Dollars to students on the meal plan and to students in cook-for-yourself locations. It was basically to provide more value in the meal plan and raise awareness about Dining Dollars, which students can use at any dining hall or retail location on campus and the Concord Market. When I met with students about it, they asked me: “What's the catch?” I told them, “It’s pretty simple. I want you to eat with us. I don’t want you to go across the street.” Also, it helps build morale with dining staff. People get into dining to make food for people to eat. They don’t make food so people can throw it away.
Third, we’re starting a student ambassador program. They will be an extension of our management team and will help us tell the story of campus dining through the lenses of students — how things are going on campus or in their houses.
Q: Do you have plans for working with graduate students at MIT?
A: This is a huge area of opportunity for dining at MIT. Graduate students are not on meal plans, because the plans don’t fit their needs, but many of them live on or near campus. What if there was some kind of pilot program that was more Dining Dollar-based, where it suits a graduate student and their family, or it doesn’t expire and can be very portable? I’m pretty sure we can come up with something that fits their needs better than grocery shopping and cooking for yourself in Cambridge.
Q: What’s your favorite thing to cook?
A: Lately, it’s been a chicken fricassee. It’s my wife’s father’s recipe. It’s Hungarian, like a paprikash chicken. You boil onions and water for a really long time and load it up with paprika. It takes hours to make. But when you do it right, it’s really, really good.
This is an edited version of an article first published by the MIT Division of Student Life.
Building reuse into the materials around us At MIT, metallurgist Diran Apelian ScD ’73 urges engineers and researchers to rethink design, recycling, and the life cycle of modern materials.In a field defined by discovering, designing, and processing the materials that underpin modern technology, Diran Apelian ScD ’73 has a resounding message: Reuse can’t remain just the focus of a PhD thesis or a startup. It needs to be engineered from the beginning.
Apelian, a metallurgist and MIT alumnus known for his pioneering work in molten metal processing, framed his plea with a look at society’s growing needs for materials like copper, nickel, iron, and manganese — and how demand for them has surged alongside population growth over the past 150 years.
“We’re using more and more stuff — that’s the takeaway,” said Apelian, the speaker for the MIT Department of Materials Science and Engineering (DMSE)’s Wulff Lecture on Nov. 19. “Now, where’s all this stuff coming from? It doesn’t come from Home Depot. It comes from the Earth — planet Earth — where we take the ores out of the Earth, and we have to extract them out.”
And more and more everyday goods depend on those ores, depleting the planet’s supplies while expending massive amounts of energy to do it, Apelian said. As one example, Apelian pointed out that computer chips, which incorporated 11 elements in 1980, now contain 52.
Instead of simply taking, processing, and eventually discarding materials — often after passing them through inefficient recycling systems — Apelian proposes another approach: designing materials and products so that the value inside them can be recovered.
Examples include aerospace-grade materials made from scrap aluminum alloys, optimized using AI-driven alloy blending, and shredding lithium-ion batteries to produce “black mass,” a mixture rich in cobalt, nickel, and lithium that can be refined into new cathode materials for the next generation of batteries.
“Sustainable growth, sustainability, the development of the planet Earth is a challenge,” said Apelian — one that materials scientists and engineers are in a prime position to tackle. “It’s a profound change, but it requires material issues and challenges that are also an opportunity for us.”
Reshaping materials design
The Wulff Lecture is no stranger to sustainability and climate issues — past speakers have discussed green iron and steel production and hydrogen-powered fuel cells. But what marked Apelian’s talk was a call for an overhaul of how materials are produced, used, and — crucially — used again. The key, he said, is “materials circularity,” which keeps Earth-derived minerals moving through the economy as long as possible, instead of being extracted, processed, used, and thrown away.
Apelian referenced the “materials tetrahedron,” the classic framework connecting processing, structure, properties, and performance — the foundation underlying the development of most materials around us. Highlighting what’s missing, he asked DMSE students about materials at the end of their life cycle: “You don’t really spend too much time on it, right?”
He proposed a new framework of concentric circles that reimagines the materials life cycle — from mining, extraction, processing, and design, to new phases focused on repair, reuse, remanufacturing, and recycling — “all the R’s,” he said.
One pathway to more sustainable materials use, Apelian said, is tackling post-consumer waste — the everyday products people throw away once they’re done using them.
“How can we take the waste and recover it and reuse it?” Apelian asked.
One example is aluminum scrap processing, which has seen several advances in recent years. Traditionally, end-of-life vehicles were stripped of valuable parts and fed through giant shredders; the resulting mix of metals were melted together, forfeiting much of its engineered value, and “downcycled” into cast alloys used for products like engine blocks or patio furniture.
Today, advancements in automated sensor-based sorting, machine learning and robotics, and improved melting practices mean aluminum scrap can now be directed into higher-value applications, including aerospace components and structural automotive parts — beams and supports that form a vehicle’s frame.
“So that’s the aim, that’s the motivation: creating value out of waste,” Apelian said.
He highlighted ongoing efforts to modernize scrap processing. He is a co-founder of Solvus Global Inc., which develops systems to convert metal scrap into high-value products, and Valis Insights, a Solvus spinout that uses sensor-based systems to identify and sort metal scraps with high precision.
At the University of California at Irvine — where Apelian serves as distinguished professor of materials science and engineering — his group is “studying the DNA” of mixed scrap, analyzing and testing blends to prepare them for high-value applications. He has also done significant work in lithium-ion battery recycling, including co-inventing the process, commercialized by Ascend Elements, that shreds batteries and produces as a byproduct the black mass used as feedstock for new cathode materials.
Believing in circularity
Apelian also pointed to ways of extracting value from industrial waste: recovering metals from red mud — the highly alkaline byproduct of aluminum production — and reclaiming rare-earth elements from mine tailings. And he spotlighted the work of Shaolou Wei ScD ’22, a DMSE alum joining the faculty in 2026, who has developed ways to bypass the long, energy-intensive sequences traditionally used to make many alloys — reducing energy consumption and eliminating processing steps.
Stressing that business models and policy play a critical role in enabling a circular economy, Apelian offered a scenario: “Right now, in America, when you buy a car, it’s yours. At the end of life, it’s your problem.” Owners can trade it in or sell it, but ultimately, they need to dispose of it, he said. He then mused about reversing this responsibility — requiring manufacturers to take cars back at end of life. “I’ve got to tell you, when that happens, things are going to be designed very differently.”
Audience member Evia Rodriguez, a senior in materials science and engineering, was struck by Apelian’s emphasis on circularity. She pointed to Patagonia — one of Apelian’s examples — as a company weaving circularity into its business model by encouraging customers to repair clothing instead of replacing it.
“That definitely represents an optimistic idea of what could happen,” Rodriguez said. “I tend to be more skeptical, but I like to think that we could get there someday, and that we could have all companies operating on a more sustainable front.”
First-year undergraduate Brandon Mata shared a similar outlook — balancing doubt with hope. “I think it’s easy to be pessimistic about how companies are going to act. You’re going to say people are always going to be greedy. They’re going to be selfish,” Mata said. “But regardless, I think it’s still important to have somebody like that saying, even just stating, ‘It’s important that we do this, and doing this would clearly benefit the world.’”
Yanna Tenorio, a first-year undergraduate who’s interested in the energy side of materials science, zoomed out to the overarching questions raised in the talk. “Thinking about what happens at the end of these materials’ life, how can they be reused? How can we take accountability for them?” Tenorio asked. “What I find very exciting about material science in general is how much there is to be discovered.”
Guided learning lets “untrainable” neural networks realize their potentialCSAIL researchers find even “untrainable” neural nets can learn effectively when guided by another network’s built-in biases using their guidance method.Even networks long considered “untrainable” can learn effectively with a bit of a helping hand. Researchers at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) have shown that a brief period of alignment between neural networks, a method they call guidance, can dramatically improve the performance of architectures previously thought unsuitable for modern tasks.
Their findings suggest that many so-called “ineffective” networks may simply start from less-than-ideal starting points, and that short-term guidance can place them in a spot that makes learning easier for the network.
The team’s guidance method works by encouraging a target network to match the internal representations of a guide network during training. Unlike traditional methods like knowledge distillation, which focus on mimicking a teacher’s outputs, guidance transfers structural knowledge directly from one network to another. This means the target learns how the guide organizes information within each layer, rather than simply copying its behavior. Remarkably, even untrained networks contain architectural biases that can be transferred, while trained guides additionally convey learned patterns.
“We found these results pretty surprising,” says Vighnesh Subramaniam ’23, MEng ’24, MIT Department of Electrical Engineering and Computer Science (EECS) PhD student and CSAIL researcher, who is a lead author on a paper presenting these findings. “It’s impressive that we could use representational similarity to make these traditionally ‘crappy’ networks actually work.”
Guide-ian angel
A central question was whether guidance must continue throughout training, or if its primary effect is to provide a better initialization. To explore this, the researchers performed an experiment with deep fully connected networks (FCNs). Before training on the real problem, the network spent a few steps practicing with another network using random noise, like stretching before exercise. The results were striking: Networks that typically overfit immediately remained stable, achieved lower training loss, and avoided the classic performance degradation seen in something called standard FCNs. This alignment acted like a helpful warmup for the network, showing that even a short practice session can have lasting benefits without needing constant guidance.
The study also compared guidance to knowledge distillation, a popular approach in which a student network attempts to mimic a teacher’s outputs. When the teacher network was untrained, distillation failed completely, since the outputs contained no meaningful signal. Guidance, by contrast, still produced strong improvements because it leverages internal representations rather than final predictions. This result underscores a key insight: Untrained networks already encode valuable architectural biases that can steer other networks toward effective learning.
Beyond the experimental results, the findings have broad implications for understanding neural network architecture. The researchers suggest that success — or failure — often depends less on task-specific data, and more on the network’s position in parameter space. By aligning with a guide network, it’s possible to separate the contributions of architectural biases from those of learned knowledge. This allows scientists to identify which features of a network’s design support effective learning, and which challenges stem simply from poor initialization.
Guidance also opens new avenues for studying relationships between architectures. By measuring how easily one network can guide another, researchers can probe distances between functional designs and reexamine theories of neural network optimization. Since the method relies on representational similarity, it may reveal previously hidden structures in network design, helping to identify which components contribute most to learning and which do not.
Salvaging the hopeless
Ultimately, the work shows that so-called “untrainable” networks are not inherently doomed. With guidance, failure modes can be eliminated, overfitting avoided, and previously ineffective architectures brought into line with modern performance standards. The CSAIL team plans to explore which architectural elements are most responsible for these improvements and how these insights can influence future network design. By revealing the hidden potential of even the most stubborn networks, guidance provides a powerful new tool for understanding — and hopefully shaping — the foundations of machine learning.
“It’s generally assumed that different neural network architectures have particular strengths and weaknesses,” says Leyla Isik, Johns Hopkins University assistant professor of cognitive science, who wasn’t involved in the research. “This exciting research shows that one type of network can inherit the advantages of another architecture, without losing its original capabilities. Remarkably, the authors show this can be done using small, untrained ‘guide’ networks. This paper introduces a novel and concrete way to add different inductive biases into neural networks, which is critical for developing more efficient and human-aligned AI.”
Subramaniam wrote the paper with CSAIL colleagues: Research Scientist Brian Cheung; PhD student David Mayo ’18, MEng ’19; Research Associate Colin Conwell; principal investigators Boris Katz, a CSAIL principal research scientist, and Tomaso Poggio, an MIT professor in brain and cognitive sciences; and former CSAIL research scientist Andrei Barbu. Their work was supported, in part, by the Center for Brains, Minds, and Machines, the National Science Foundation, the MIT CSAIL Machine Learning Applications Initiative, the MIT-IBM Watson AI Lab, the U.S. Defense Advanced Research Projects Agency (DARPA), the U.S. Department of the Air Force Artificial Intelligence Accelerator, and the U.S. Air Force Office of Scientific Research.
Their work was recently presented at the Conference and Workshop on Neural Information Processing Systems (NeurIPS).
Population decline often goes hand-in-hand with economic stagnation in rural areas — and the two reinforce each other in a cycle. Can digital technologies advance equitable innovation and, at the same time, preserve cultural heritage in shrinking regions?
A new open-access book, edited by MIT Vice Provost and Department of Urban Studies and Planning (DUSP) Professor Brent D. Ryan PhD ’02, Carmelo Ignaccolo PhD ’24 of Rutgers University, and Giovanna Fossa of the Politecnico di Milano, explores the transformative power of community-centered technologies in the rural areas of Italy.
“Small Town Renaissance: Bridging Technology, Heritage and Planning in Shrinking Italy” (Springer Nature, 2025) investigates the future of small towns through empirical analyses of cellphone data, bold urban design visions, collaborative digital platforms for small businesses, and territorial strategies for remote work. The work examines how technology may open up these regions to new economic opportunities. The book shares data-driven scholarly work on shrinking towns, economic development, and digital innovation from multiple planning scholars and practitioners, several of whom traveled to Italy in fall 2022 as part of a DUSP practicum taught by Ryan and Ignaccolo, and sponsored by MISTI Italy and Fondazione Rocca, in collaboration with Liminal.
“What began as a hands-on MIT practicum grew into a transatlantic book collaboration uniting scholars in design, planning, heritage, law, and telecommunications to explore how technology can sustain local economies and culture,” says Ignaccolo.
Now an assistant professor of city planning at Rutgers University’s E.J. Bloustein School of Planning and Public Policy, Ignaccolo says the book provides concrete and actionable strategies to support shrinking regions in leveraging cultural heritage and smart technologies to strengthen opportunities and local economies.
“Depopulation linked to demographic change is reshaping communities worldwide,” says Ryan. “Italy is among the hardest hit, and the United States is heading in the same direction. This project offered students a chance to harness technology and innovation to imagine bold responses to this growing challenge.”
The researchers note that similar struggles also exist in rural communities across Germany, Spain, Japan, and Korea. The book provides policymakers, urban planners, designers, tech innovators, and heritage advocates with fresh insights and actionable strategies to shape the future of rural development in the digital age. The book and chapters can be downloaded for free through most university libraries via open access.
Post-COP30, more aggressive policies needed to cap global warming at 1.5 CGlobal Change Outlook report for 2025 shows how accelerated action can reduce climate risks and improve sustainability outcomes, while highlighting potential geopolitical hurdles.The latest United Nations Climate Change Conference (COP30) concluded in November without a roadmap to phase out fossil fuels and without significant progress in strengthening national pledges to reduce climate-altering greenhouse gas emissions. In aggregate, today’s climate policies remain far too unambitious to meet the Paris Agreement’s goal of capping global warming at 1.5 degrees Celsius, setting the world on course to experience more frequent and intense storms, flooding, droughts, wildfires, and other climate impacts. A global policy regime aligned with the 1.5 C target would almost certainly reduce the severity of those impacts.
In the “2025 Global Change Outlook,” researchers at the MIT Center for Sustainability Science and Strategy (CS3) compare the consequences of these two approaches to climate policy through modeled projections of critical natural and societal systems under two scenarios. The Current Trends scenario represents the researchers’ assessment of current measures for reducing greenhouse gas (GHG) emissions; the Accelerated Actions scenario is a credible pathway to stabilizing the climate at a global mean surface temperature of 1.5 C above preindustrial levels, in which countries impose more aggressive GHG emissions-reduction targets.
By quantifying the risks posed by today’s climate policies — and the extent to which accelerated climate action aligned with the 1.5 C goal could reduce them — the “Global Change Outlook” aims to clarify what’s at stake for environments and economies around the world. Here, we summarize the report’s key findings at the global level; regional details can also be accessed in several sections and through MIT CS3’s interactive global visualization tool.
Emerging headwinds for global climate action
Projections under Current Trends show higher GHG emissions than in our previous 2023 outlook, indicating reduced action on GHG emissions mitigation in the upcoming decade. The difference, roughly equivalent to the annual emissions from Brazil or Japan, is driven by current geopolitical events.
Additional analysis in this report indicates that global GHG emissions in 2050 could be 10 percent higher than they would be under Current Trends if regional rivalries triggered by U.S. tariff policy prompt other regions to weaken their climate regulations. In that case, the world would see virtually no emissions reduction in the next 25 years.
Energy and electricity projections
Between 2025 and 2050, global energy consumption rises by 17 percent under Current Trends, with a nearly nine-fold increase in wind and solar. Under Accelerated Actions, global energy consumption declines by 16 percent, with a nearly 13-fold increase in wind and solar, driven by improvements in energy efficiency, wider use of electricity, and demand response. In both Current Trends and Accelerated Actions, global electricity consumption increases substantially (by 90 percent and 100 percent, respectively), with generation from low-carbon sources becoming a dominant source of power, though Accelerated Actions has a much larger share of renewables.
“Achieving long-term climate stabilization goals will require more ambitious policy measures that reduce fossil-fuel dependence and accelerate the energy transition toward low-carbon sources in all regions of the world. Our Accelerated Actions scenario provides a pathway for scaling up global climate ambition,” says MIT CS3 Deputy Director Sergey Paltsev, co-lead author of the report.
Greenhouse gas emissions and climate projections
Under Current Trends, global anthropogenic (human-caused) GHG emissions decline by 10 percent between 2025 and 2050, but start to rise again later in the century; under Accelerated Actions, however, they fall by 60 percent by 2050. Of the two scenarios, only the latter could put the world on track to achieve long-term climate stabilization.
Median projections for global warming by 2050, 2100, and 2150 are projected to reach 1.79, 2.74, and 3.72 degrees C (relative to the global mean surface temperature (GMST) average for the years 1850-1900) under Current Trends and 1.62, 1.56, and 1.50 C under Accelerated Actions. Median projections for global precipitation show increases from 2025 levels of 0.04, 0.11, and 0.18 millimeters per day in 2050, 2100, and 2150 under Current Trends and 0.03, 0.04, and 0.03 mm/day for those years under Accelerated Actions.
“Our projections demonstrate that aggressive cuts in GHG emissions can lead to substantial reductions in the upward trends of GMST, as well as global precipitation,” says CS3 deputy director C. Adam Schlosser, co-lead author of the outlook. “These reductions to both climate warming and acceleration of the global hydrologic cycle lower the risks of damaging impacts, particularly toward the latter half of this century.”
Implications for sustainability
The report’s modeled projections imply significantly different risk levels under the two scenarios for water availability, biodiversity, air quality, human health, economic well-being, and other sustainability indicators.
Among the key findings: Policies that align with Accelerated Actions could yield substantial co-benefits for water availability, biodiversity, air quality, and health. For example, combining Accelerated Actions-aligned climate policies with biodiversity targets, or with air-quality targets, could achieve biodiversity and air quality/health goals more efficiently and cost-effectively than a more siloed approach. The outlook’s analysis of the global economy under Current Trends suggests that decision-makers need to account for climate impacts outside their home region and the resilience of global supply chains.
Finally, CS3’s new data-visualization platform provides efficient, screening-level mapping of current and future climate, socioeconomic, and demographic-related conditions and changes — including global mapping for many of the model outputs featured in this report.
“Our comparison of outcomes under Current Trends and Accelerated Actions scenarios highlights the risks of remaining on the world’s current emissions trajectory and the benefits of pursuing a much more aggressive strategy,” says CS3 Director Noelle Selin, a co-author of the report and a professor in the Institute for Data, Systems and Society and Department of Earth, Atmospheric and Planetary Sciences at MIT. “We hope that our risk-benefit analysis will help inform decision-makers in government, industry, academia, and civil society as they confront sustainability-relevant challenges.”
Student Spotlight: Diego TemkinThe senior, who is involved in Dormitory Council, Hydrant, the Student Information Processing Board, and SuperUROP, is double majoring in computer science and engineering and in urban planning.This interview is part of a series of short interviews from the Department of Electrical Engineering and Computer Science (EECS). Each spotlight features a student answering their choice of questions about themselves and life at MIT. Today’s interviewee, senior Diego Temkin, is double majoring in courses 6-3 (Computer Science and Engineering) and 11 (Urban Planning). The McAllen, Texas, native is involved with MIT’s Dormitory Council (DormCon), helps to maintain Hydrant (formerly Firehose)/CourseRoad, and is both a member of the Student Information Processing Board (MIT’s oldest computing club) and an Advanced Undergraduate Research Opportunities Program (SuperUROP) scholar.
Q: What’s your favorite key on a standard computer keyboard, and why?
A: The “1” key! During Covid, I ended up starting a typewriter collection and trying to fix them up, and I always thought it was interesting how they didn’t have a 1 key. People were just expected to use the lowercase “l,” which presumably makes anyone who cares about ASCII very upset.
Q: Tell us about a teacher from your past who had an influence on the person you’ve become.
A: Back in middle school, everyone had to take a technology class that taught things like typing skills, Microsoft Word and Excel, and some other things. I was a bit of a nerd and didn’t have too many friends interested in the sort of things I was, but the teacher of that technology class, Mrs. Camarena, would let me stay for a bit after school and encouraged me to explore more of my interests. She helped me become more confident in wanting to go into computer science, and now here I am.
Q: What’s your favorite trivia factoid?
A: Every floor in Building 13 is painted as a different MBTA line. I don’t know why and can’t really find anything about it online, but once you notice it you can’t unsee it!
Q: Do you have any pets?
A: I do! His name is Skateboard, and he is the most quintessentially orange cat. I got him off reuse@mit.edu during my first year here at MIT (shout out to Patty K), and he’s been with me ever since. He’s currently five years old, and he’s a big fan of goldfish and stepping on my face at 7 a.m. Best decision I’ve ever made.
Q: Are you a re-reader or a re-watcher? If so, what are your comfort books, shows, or movies?
A: Definitely a re-watcher, and definitely “Doctor Who.” I’ve watched far too much of that show and there are episodes I can recite from memory (looking at you, “The Eleventh Hour”). Anyone I know will tell you that I can go on about that show for hours, and before anyone asks, my favorite doctor is Matt Smith (sorry to the David Tennant fans; I like him too, though!)
Q: Do you have a bucket list? If so, share one or two of the items on it.
A: I’ve been wanting to take a cross-country Amtrak trip for a while … I think I might try going to the West Coast and some national parks during IAP [Independent Activities Period], if I have the time. Now that it’s on here, I definitely have to do it!
A “scientific sandbox” lets researchers explore the evolution of vision systemsThe AI-powered tool could inform the design of better sensors and cameras for robots or autonomous vehicles.Why did humans evolve the eyes we have today?
While scientists can’t go back in time to study the environmental pressures that shaped the evolution of the diverse vision systems that exist in nature, a new computational framework developed by MIT researchers allows them to explore this evolution in artificial intelligence agents.
The framework they developed, in which embodied AI agents evolve eyes and learn to see over many generations, is like a “scientific sandbox” that allows researchers to recreate different evolutionary trees. The user does this by changing the structure of the world and the tasks AI agents complete, such as finding food or telling objects apart.
This allows them to study why one animal may have evolved simple, light-sensitive patches as eyes, while another has complex, camera-type eyes.
The researchers’ experiments with this framework showcase how tasks drove eye evolution in the agents. For instance, they found that navigation tasks often led to the evolution of compound eyes with many individual units, like the eyes of insects and crustaceans.
On the other hand, if agents focused on object discrimination, they were more likely to evolve camera-type eyes with irises and retinas.
This framework could enable scientists to probe “what-if” questions about vision systems that are difficult to study experimentally. It could also guide the design of novel sensors and cameras for robots, drones, and wearable devices that balance performance with real-world constraints like energy efficiency and manufacturability.
“While we can never go back and figure out every detail of how evolution took place, in this work we’ve created an environment where we can, in a sense, recreate evolution and probe the environment in all these different ways. This method of doing science opens to the door to a lot of possibilities,” says Kushagra Tiwary, a graduate student at the MIT Media Lab and co-lead author of a paper on this research.
He is joined on the paper by co-lead author and fellow graduate student Aaron Young; graduate student Tzofi Klinghoffer; former postdoc Akshat Dave, who is now an assistant professor at Stony Brook University; Tomaso Poggio, the Eugene McDermott Professor in the Department of Brain and Cognitive Sciences, an investigator in the McGovern Institute, and co-director of the Center for Brains, Minds, and Machines; co-senior authors Brian Cheung, a postdoc in the Center for Brains, Minds, and Machines and an incoming assistant professor at the University of California San Francisco; and Ramesh Raskar, associate professor of media arts and sciences and leader of the Camera Culture Group at MIT; as well as others at Rice University and Lund University. The research appears today in Science Advances.
Building a scientific sandbox
The paper began as a conversation among the researchers about discovering new vision systems that could be useful in different fields, like robotics. To test their “what-if” questions, the researchers decided to use AI to explore the many evolutionary possibilities.
“What-if questions inspired me when I was growing up to study science. With AI, we have a unique opportunity to create these embodied agents that allow us to ask the kinds of questions that would usually be impossible to answer,” Tiwary says.
To build this evolutionary sandbox, the researchers took all the elements of a camera, like the sensors, lenses, apertures, and processors, and converted them into parameters that an embodied AI agent could learn.
They used those building blocks as the starting point for an algorithmic learning mechanism an agent would use as it evolved eyes over time.
“We couldn’t simulate the entire universe atom-by-atom. It was challenging to determine which ingredients we needed, which ingredients we didn’t need, and how to allocate resources over those different elements,” Cheung says.
In their framework, this evolutionary algorithm can choose which elements to evolve based on the constraints of the environment and the task of the agent.
Each environment has a single task, such as navigation, food identification, or prey tracking, designed to mimic real visual tasks animals must overcome to survive. The agents start with a single photoreceptor that looks out at the world and an associated neural network model that processes visual information.
Then, over each agent’s lifetime, it is trained using reinforcement learning, a trial-and-error technique where the agent is rewarded for accomplishing the goal of its task. The environment also incorporates constraints, like a certain number of pixels for an agent’s visual sensors.
“These constraints drive the design process, the same way we have physical constraints in our world, like the physics of light, that have driven the design of our own eyes,” Tiwary says.
Over many generations, agents evolve different elements of vision systems that maximize rewards.
Their framework uses a genetic encoding mechanism to computationally mimic evolution, where individual genes mutate to control an agent’s development.
For instance, morphological genes capture how the agent views the environment and control eye placement; optical genes determine how the eye interacts with light and dictate the number of photoreceptors; and neural genes control the learning capacity of the agents.
Testing hypotheses
When the researchers set up experiments in this framework, they found that tasks had a major influence on the vision systems the agents evolved.
For instance, agents that were focused on navigation tasks developed eyes designed to maximize spatial awareness through low-resolution sensing, while agents tasked with detecting objects developed eyes focused more on frontal acuity, rather than peripheral vision.
Another experiment indicated that a bigger brain isn’t always better when it comes to processing visual information. Only so much visual information can go into the system at a time, based on physical constraints like the number of photoreceptors in the eyes.
“At some point a bigger brain doesn’t help the agents at all, and in nature that would be a waste of resources,” Cheung says.
In the future, the researchers want to use this simulator to explore the best vision systems for specific applications, which could help scientists develop task-specific sensors and cameras. They also want to integrate LLMs into their framework to make it easier for users to ask “what-if” questions and study additional possibilities.
“There’s a real benefit that comes from asking questions in a more imaginative way. I hope this inspires others to create larger frameworks, where instead of focusing on narrow questions that cover a specific area, they are looking to answer questions with a much wider scope,” Cheung says.
This work was supported, in part, by the Center for Brains, Minds, and Machines and the Defense Advanced Research Projects Agency (DARPA) Mathematics for the Discovery of Algorithms and Architectures (DIAL) program.
Teen builds an award-winning virtual reality prototype thanks to free MIT coursesNineteen-year-old Freesia Gaul built a VR prototype thanks to MIT OpenCourseWare classes that provided “a solid foundation of knowledge and problem-solving abilities.”When Freesia Gaul discovered MIT Open Learning’s OpenCourseWare at just 14 years old, it opened up a world of learning far beyond what her classrooms could offer. Her parents had started a skiing company, and the seasonal work meant that Gaul had to change schools every six months. Growing up in small towns in Australia and Canada, she relied on the internet to fuel her curiosity.
“I went to 13 different schools, which was hard because you're in a different educational system every single time,” says Gaul. “That’s one of the reasons I gravitated toward online learning and teaching myself. Knowledge is something that exists beyond a curriculum.”
The small towns she lived in often didn’t have a lot of resources, she says, so a computer served as a main tool for learning. She enjoyed engaging with Wikipedia, ultimately researching topics and writing and editing content for pages. In 2018, she discovered MIT OpenCourseWare, part of MIT Open Learning, and took her first course. OpenCouseWare offers free, online, open educational resources from more than 2,500 MIT undergraduate and graduate courses.
“I really got started with the OpenCourseWare introductory electrical engineering classes, because I couldn’t find anything else quite like it online,” says Gaul, who was initially drawn to courses on circuits and electronics, such as 6.002 (Circuits and Electronics) and 6.01SC (Introduction to Electrical Engineering and Computer Science). “It really helped me in terms of understanding how electrical engineering worked in a practical sense, and I just started modding things.”
In true MIT “mens et manus” (“mind and hand”) fashion, Gaul spent much of her childhood building and inventing, especially when she was able to access a 3D printer. She says that a highlight was when she built a life-sized, working version of a Mario Kart, constructed out of materials she had printed.
Gaul calls herself a “serial learner,” and has taken many OpenCourseWare courses. In addition to classes on circuits and electronics, she also took courses in linear algebra, calculus, and quantum physics — in which she took a particular interest.
When she was 15, she participated in Qubit by Qubit. Hosted by The Coding School, in collaboration with universities (including MIT) and tech companies, this two-semester course introduces high schoolers to quantum computing and quantum physics.
During that time she started a blog called On Zero, representing the “zero state” of a qubit. “The ‘zero state’ in a quantum computer is the representation of creativity from nothing, infinite possibilities,” says Gaul. For the blog, she found different topics and researched them in depth. She would think of a topic or question, such as “What is color?” and then explore it in great detail. What she learned eventually led her to start asking questions such as “What is a hamiltonian?” and teaching quantum physics alongside PhDs.
Building on these interests, Gaul chose to study quantum engineering at the University of New South Wales. She notes that on her first day of university, she participated in iQuHack, the MIT Quantum Hackathon. Her team worked to find a new way to approximate the value of a hyperbolic function using quantum logic, and received an honorable mention for “exceptional creativity.”
Gaul’s passion for making things continued during her college days, especially in terms of innovating to solve a problem. When she found herself on a train, wanting to code a personal website on a computer with a dying battery, she wondered if there might be a way to make a glove that can act as a type of Bluetooth keyboard — essentially creating a way to type in the air. In her spare time, she started working on such a device, ultimately finding a less expensive way to build a lightweight, haptic, gesture-tracking glove with applications for virtual reality (VR) and robotics.
Gaul says she has always had an interest in VR, using it to create her own worlds, reconstruct an old childhood house, and play Dungeons and Dragons with friends. She discovered a way to put into a glove some small linear resonant actuators, which can be found in a smartphone or gaming controller, and map to any object in VR so that the user can feel it.
An early prototype that Gaul put together in her dorm room received a lot of attention on YouTube. She went on to win the People’s Choice award for it at the SxSW Sydney 2025 Tech and Innovation Festival. This design also sparked her co-founding of the tech startup On Zero, named after her childhood blog dedicated to the love of creation from nothing.
Gaul sees the device, in general, as a way of “paying it forward,” making improved human-computer interaction available to many — from young students to professional technologists. She hopes to enable creative freedom in as many as she can. “The mind is just such a fun thing. I want to empower others to have the freedom to follow their curiosity, even if it's pointless on paper.
“I’ve benefited from people going far beyond what they needed to do to help me,” says Gaul. “I see OpenCourseWare as a part of that. The free courses gave me a solid foundation of knowledge and problem-solving abilities. Without these, it wouldn’t be possible to do what I’m doing now.”
MIT-Hood Pediatric Innovation Hub convenes leaders to advance pediatric healthThe Hood Pediatric Innovation Hub brings together clinicians, researchers, and industry to bridge the gap between discovery and care.Facing hospital closures, underfunded pediatric trials, and a persistent reliance on adult-oriented tools for children, the Hood Pediatric Innovation Hub welcomed nearly 200 leaders at Boston’s Museum of Science for MIT-Hood Pediatric Innovation 2025, an event focused on transforming the future of pediatric care through engineering and collaboration.
Hosted by the Hood Pediatric Innovation Hub — established at MIT through a gift by the Hood Foundation — the event brought together attendees from academia, health care, and industry to rethink how medical and technological breakthroughs can reach children faster. The gathering marked a new phase in the hub’s mission to connect scientific discovery with real-world impact.
“We have extraordinary science emerging every day, but the translation gap is widening,” said Joseph Frassica, professor of the practice in MIT’s Institute for Medical Engineering and Science and executive director of the Hood Pediatric Innovation Hub. “We can’t rely on the old model of innovation — we need new connective tissue between ideas, institutions, and implementation.”
Building collaboration across sectors
Speakers emphasized that pediatric medicine has long faced structural disadvantages compared with other fields — from smaller patient populations to limited commercial incentives. Yet they also described a powerful opportunity: to make pediatric innovation a proving ground for smarter, more human-centered health systems.
“The Hood Foundation has always believed that if you can improve care for children, you improve care for everyone,” said Neil Smiley, president of the Charles H. Hood Foundation. “Pediatrics pushes medicine to be smarter, more precise, and more humane — and that’s why this collaboration with MIT feels so right.”
Participants discussed how aligning efforts across universities, hospitals, and industry partners could help overcome the fragmentation that slows innovation, and ultimately translation. Speakers at the event highlighted case studies where cross-sector collaboration is already yielding results — from novel medical devices to data-driven clinical insights.
Connecting discovery to delivery
In his remarks, Elazer R. Edelman, the Edward J. Poitras Professor in Medical Engineering and Science at MIT and faculty lead for the Hood Pediatric Innovation Hub, reflected on how MIT’s engineering and medical communities can help close the loop between research and clinical application.
“This isn’t about creating something new for the sake of it — it’s about finally connecting the extraordinary expertise that already exists, from the lab to the clinic to the child’s bedside,” Edelman said. “That’s what MIT does best — we connect the dots.”
Throughout the day, attendees shared experiences from both the engineering and clinical viewpoints — acknowledging the complexities of regulation, funding, and adoption, while highlighting the shared responsibility to move faster on behalf of children.
A moment of convergence
The conversation also turned to the economics of innovation and the broader societal benefits of investing in pediatric health.
“The economic and social stakes couldn’t be higher,” said Jonathan Gruber, Ford Professor of Economics at MIT. “When we invest in children’s health, we invest in longer lives, stronger communities, and greater prosperity. The energy in this room shows what’s possible when we stop working in silos.”
By the end of the event, discussions had shifted from identifying barriers to designing solutions. Participants explored ideas ranging from translational fellowships and shared data platforms to new models for academic–industry partnership — each aimed at accelerating impact where it is needed most.
Looking ahead
“There’s a feeling that this is the moment,” Frassica said. “We have the tools, the data, and the will to transform how we care for children. The key now is keeping that spirit of collaboration alive — because when we do, we move the whole field forward.”
Building on the momentum from MIT-Hood Pediatric Innovation 2025, the Hood Pediatric Innovation Hub will continue to serve as a connector across disciplines and institutions, advancing projects that translate cutting-edge research into improved outcomes for children everywhere. In January, a new cohort of MIT Catalyst Fellows — early-career researchers embedded with frontline clinicians to identify unmet needs — will begin exploring solutions to challenges in pediatric and neonatal health care in partnership with the hub.
This work is also part of a wider Institute effort. The Hood Pediatric Innovation Hub contributes to the broader mission of the MIT Health and Life Sciences Collaborative (HEALS), which brings together faculty, clinicians, and industry partners to accelerate breakthroughs across all areas of human health. As the hub deepens its own collaborations, its connection to HEALS helps ensure that advances in pediatric medicine are integrated into MIT’s larger push to improve health outcomes at scale.
The hub will also release a request for proposals in the coming months for the development of its first mentored projects — designed to bring together teams from engineering, medicine, and industry to accelerate progress in children’s health. Updates and details will be available at hoodhub.mit.edu.
As Smiley noted, progress in pediatric health often drives progress across all of medicine — and this gathering underscored that shared belief: when we work together for children, we build a healthier future for everyone.
New study suggests a way to rejuvenate the immune systemStimulating the liver to produce some of the signals of the thymus can reverse age-related declines in T-cell populations and enhance response to vaccination.As people age, their immune system function declines. T cell populations become smaller and can’t react to pathogens as quickly, making people more susceptible to a variety of infections.
To try to overcome that decline, researchers at MIT and the Broad Institute have found a way to temporarily program cells in the liver to improve T-cell function. This reprogramming can compensate for the age-related decline of the thymus, where T cell maturation normally occurs.
Using mRNA to deliver three key factors that usually promote T-cell survival, the researchers were able to rejuvenate the immune systems of mice. Aged mice that received the treatment showed much larger and more diverse T cell populations in response to vaccination, and they also responded better to cancer immunotherapy treatments.
If developed for use in patients, this type of treatment could help people lead healthier lives as they age, the researchers say.
“If we can restore something essential like the immune system, hopefully we can help people stay free of disease for a longer span of their life,” says Feng Zhang, the James and Patricia Poitras Professor of Neuroscience at MIT, who has joint appointments in the departments of Brain and Cognitive Sciences and Biological Engineering.
Zhang, who is also an investigator at the McGovern Institute for Brain Research at MIT, a core institute member at the Broad Institute of MIT and Harvard, an investigator in the Howard Hughes Medical Institute, and co-director of the K. Lisa Yang and Hock E. Tan Center for Molecular Therapeutics at MIT, is the senior author of the new study. Former MIT postdoc Mirco Friedrich is the lead author of the paper, which appears today in Nature.
A temporary factory
The thymus, a small organ located in front of the heart, plays a critical role in T-cell development. Within the thymus, immature T cells go through a checkpoint process that ensures a diverse repertoire of T cells. The thymus also secretes cytokines and growth factors that help T cells to survive.
However, starting in early adulthood, the thymus begins to shrink. This process, known as thymic involution, leads to a decline in the production of new T cells. By the age of approximately 75, the thymus is greatly reduced.
“As we get older, the immune system begins to decline. We wanted to think about how can we maintain this kind of immune protection for a longer period of time, and that's what led us to think about what we can do to boost immunity,” Friedrich says.
Previous work on rejuvenating the immune system has focused on delivering T cell growth factors into the bloodstream, but that can have harmful side effects. Researchers are also exploring the possibility of using transplanted stem cells to help regrow functional tissue in the thymus.
The MIT team took a different approach: They wanted to see if they could create a temporary “factory” in the body that would generate the T-cell-stimulating signals that are normally produced by the thymus.
“Our approach is more of a synthetic approach,” Zhang says. “We're engineering the body to mimic thymic factor secretion.”
For their factory location, they settled on the liver, for several reasons. First, the liver has a high capacity for producing proteins, even in old age. Also, it’s easier to deliver mRNA to the liver than to most other organs of the body. The liver was also an appealing target because all of the body’s circulating blood has to flow through it, including T cells.
To create their factory, the researchers identified three immune cues that are important for T-cell maturation. They encoded these three factors into mRNA sequences that could be delivered by lipid nanoparticles. When injected into the bloodstream, these particles accumulate in the liver and the mRNA is taken up by hepatocytes, which begin to manufacture the proteins encoded by the mRNA.
The factors that the researchers delivered are DLL1, FLT-3, and IL-7, which help immature progenitor T cells mature into fully differentiated T cells.
Immune rejuvenation
Tests in mice revealed a variety of beneficial effects. First, the researchers injected the mRNA particles into 18-month-old mice, equivalent to humans in their 50s. Because mRNA is short-lived, the researchers gave the mice multiple injections over four weeks to maintain a steady production by the liver.
After this treatment, T cell populations showed significant increases in size and function.
The researchers then tested whether the treatment could enhance the animals’ response to vaccination. They vaccinated the mice with ovalbumin, a protein found in egg whites that is commonly used to study how the immune system responds to a specific antigen. In 18-month-old mice that received the mRNA treatment before vaccination, the researchers found that the population of cytotoxic T-cells specific to ovalbumin doubled, compared to mice of the same age that did not receive the mRNA treatment.
The mRNA treatment can also boost the immune system’s response to cancer immunotherapy, the researchers found. They delivered the mRNA treatment to 18-month-old mice, who were then implanted with tumors and treated with a checkpoint inhibitor drug. This drug, which targets the protein PD-L1, is designed to help take the brakes off the immune system and stimulate T cells to attack tumor cells.
Mice that received the treatment showed much higher survival rates and longer lifespan that those that received the checkpoint inhibitor drug but not the mRNA treatment.
The researchers found that all three factors were necessary to induce this immune enhancement; none could achieve all aspects of it on their own. They now plan to study the treatment in other animal models and to identify additional signaling factors that may further enhance immune system function. They also hope to study how the treatment affects other immune cells, including B cells.
Other authors of the paper include Julie Pham, Jiakun Tian, Hongyu Chen, Jiahao Huang, Niklas Kehl, Sophia Liu, Blake Lash, Fei Chen, Xiao Wang, and Rhiannon Macrae.
The research was funded, in part, by the Howard Hughes Medical Institute, the K. Lisa Yang Brain-Body Center, part of the Yang Tan Collective at MIT, Broad Institute Programmable Therapeutics Gift Donors, the Pershing Square Foundation, J. and P. Poitras, and an EMBO Postdoctoral Fellowship.
Nuno Loureiro, professor and director of MIT’s Plasma Science and Fusion Center, dies at 47In his 10 years at MIT, Loureiro helped illuminate the physics occurring at the center of fusion vacuum chambers and at the edges of the universe.This article may be updated.
Nuno Loureiro, a professor of nuclear science and engineering and of physics at MIT, has died. He was 47.
In a letter to the MIT community, President Sally Kornbluth wrote, “With great sadness, I write to share the tragic news that Professor Nuno Loureiro, director of the Plasma Science and Fusion Center (PSFC), died early this morning from gunshot wounds he sustained a few hours before. In the face of this shocking loss, our hearts go out to his wife and their family and to his many devoted students, friends and colleagues.”
A lauded theoretical physicist and fusion scientist, Loureiro joined MIT’s faculty in 2016. His research addressed complex problems lurking at the center of fusion vacuum chambers and at the edges of the universe.
Loureiro’s research at MIT advanced scientists’ understanding of plasma behavior, including turbulence, and uncovered the physics behind astronomical phenomena like solar flares. He was the Herman Feshbach (1942) Professor of Physics at MIT and was named director of the Plasma Science and Fusion Center in 2024, though his contributions to fusion science and engineering began far before that.
His research on magnetized plasma dynamics, magnetic field amplification, and confinement and transport in fusion plasmas helped inform the design of fusion devices that could harness the energy of fusing plasmas, bringing the dream of clean, near-limitless fusion power closer to reality.
“Nuno was not only a brilliant scientist, he was a brilliant person,” says Dennis Whyte, the Hitachi America Professor of Engineering, who previously served as the head of the Department of Nuclear Science and Engineering and director of the Plasma Science and Fusion Center. “He shone a bright light as a mentor, friend, teacher, colleague and leader, and was universally admired for his articulate, compassionate manner. His loss is immeasurable to our community at the PSFC, NSE and MIT, and around the entire fusion and plasma research world.”
“Nuno was a champion for plasma physics within the Physics Department, a wonderful and engaging colleague, and an inspiring and caring mentor for graduate students working in plasma science. His recent work on quantum computing algorithms for plasma physics simulations was a particularly exciting new scientific direction,” says Deepto Chakrabarty, the William A. M. Burden Professor in Astrophysics and head of the Department of Physics.
Whether working on fusion or astrophysics research, Loureiro merged fundamental physics with technology and engineering, to maximize impact.
“There are people who are driven by technology and engineering, and others who are driven by fundamental mathematics and physics. We need both,” Loureiro said in 2019. “When we stimulate theoretically inclined minds by framing plasma physics and fusion challenges as beautiful theoretical physics problems, we bring into the game incredibly brilliant students — people who we want to attract to fusion development.”
Loureiro majored in physics at Instituto Superior Tecnico (IST) in Portugal and obtained a PhD in physics at Imperial College London in 2005. He conducted postdoctoral work at the Princeton Plasma Physics Laboratory for the next two years before moving to the UKAEA Culham Center for Fusion Energy in 2007. Loureiro returned to IST in 2009, where he was a researcher at the Institute for Plasmas and Nuclear Fusion until coming to MIT in 2016.
He wasted no time contributing to the intellectual environment at MIT, spending part of his first two years at the Institute working on the vexing problem of plasma turbulence. Plasma is the super-hot state of matter that serves as the fuel for fusion reactors. Loureiro’s lab at PSFC illuminated how plasma behaves inside fusion reactors, which could help prevent material failures and better contain the plasma to harvest electricity.
“Nuno was not only an extraordinary scientist and educator, but also a tremendous colleague, mentor, and friend who cared deeply about his students and his community. His absence will be felt profoundly across NSE and far beyond,” Benoit Forget, the KEPCO Professor and head of the Department of Nuclear Science and Engineering, wrote in an email to the department today.
On other fronts, Loureiro’s work in astrophysics helped reveal fundamental mechanisms of the universe. He put forward the first theory of turbulence in pair plasmas, which differ from regular plasmas and may be abundant in space. The work was driven, in part, by unprecedented observations of a binary neutron star merger in 2018.
As an assistant professor and then a full professor at MIT, Loureiro taught course 22.612 (Intro to Plasma Physics) and course 22.615 (MHD Theory of Fusion Systems), for which he was twice recognized with the Department of Nuclear Science and Engineering’s PAI Outstanding Professor Award.
Loureiro’s research earned him many prominent awards throughout his prolific career, including the National Science Foundation Career Award and the American Physical Society Thomas H. Stix Award for Outstanding Early Career Contributions to Plasma Physics Research. He was also an American Physical Society Fellow. Earlier this year, he earned the Presidential Early Career Award for Scientists and Engineers.
Friends of the Loureiro family have set up a GoFundMe account to support the family, and the Nuno Loureiro Memorial Fund has been established to support MIT graduate students at NSE and PSFC.
Additional tributes from those in the MIT community who knew Nuno Loureiro
“I was one of Nuno’s PhD students at PSFC. Nuno has granted me some of the most rewarding years of my life. He was an incredible mentor, a caring teacher, and a good friend. I am grateful to have had a couple of truly transformative years with him.”
—Dion Li, graduate student in physics
“I worked closely with Nuno since I joined the PSFC in 2018. In my 15 years working at MIT, Nuno has been one of the best PIs I have had the privilege to work with. I witnessed him start as an associate professor and rise to become the head of our lab. Over the years, we worked, laughed, and grew together. I saw firsthand how hard he worked, how many proposals he wrote, and how deeply he cared for his family, students, colleagues, and friends. He was impactful, kind, and grounded, and through humor and sincerity, he reminded us that scientists don’t just do science — they also carry deep feelings for the people around them.”
—Kwokin Ou, research administrator in the MIT Plasma Science and Fusion Center
“In losing Nuno, we have lost a singularly brilliant scientist and human being. His leadership was built upon not only scientific excellence, but also the personal connections he forged by making people in the laboratory community feel valued. Nuno treated teaching with tremendous care, and his love of the field shone through continuously. I am so fortunate to have learned from him.”
—Rachel Bielajew, visiting scientist in the MIT Plasma Science and Fusion Center
“Speaking at a PSFC all-hands meeting in May 2024 — his first as the newly appointed PSFC director — Nuno said the following, which I found to be quite inspiring: ‘I am very certain that there is no point whatsoever in doing anything here [at the PSFC] that we don’t have the chance of being the best in the world at. … If we do something new, or if we keep doing what we’re doing, let it be for the reason that we can be the best. So if we’re not the best, that’s what we should be aspiring to be; if we are the best, let’s keep it that way.’”
—Alex Tinguely, research scientist and group leader in the MIT Plasma Science and Fusion Center
“From the very beginning and throughout, Nuno was a foundational part of my life here at MIT — he interviewed me when I applied, he and my primary advisor held joint group social events, he helped me study for qualifying exams, he taught a class I took, and he was on my qualifying exam and thesis committees. Shortly after my final oral presentation for quals, I ran into him in a PSFC hallway, and we were alone. Nuno told me that he was seriously impressed, that I should be proud of myself, and that he was excited to see how our research unfolds. I will forever carry this and countless other memories of Nuno’s kindness. I already miss him deeply.”
—Lansing Horan IV, graduate student in nuclear science and engineering
“Nuno strived for and inspired excellence with warmth and compassion. As an advisor, teacher, and director, he thought deeply about how to enable people, including me, to do their best science and grow to their full potential. I am deeply honored that he put his faith in me to help him reach his community building and career development goals and I will do everything I can to keep the initiatives he started in motion going forward. He leaves an unfillable hole and will be sorely missed.”
—Maria Gatu Johnson, principal research scientist and assistant director in the MIT Plasma Science and Fusion Center
“During the first two years of my PhD here, I took every class Nuno taught, even when not required, because he was a tremendous teacher, and I knew I would learn and laugh a lot. Nuno was one of the smartest people I’ve met and also one of the most charismatic. I will cherish my time with him.”
—Henry Wietfeldt, graduate student in physics
“My first graduate class was taught by Nuno, and to this day it remains the hardest class I have ever taken. His passion for plasma physics and his fun, snarky yet rigorous teaching style inspired me and taught me so much. He also provided me with tremendous help and encouragement when I was going through academic hardships. He believed in my ability and potential, and I will forever remember our conversations and carry that support with me throughout the rest of my academic journey.”
—Lily Li, graduate student in nuclear science and engineering
“Nuno was my advisor, and to say that he was one of my biggest supporters and advocates is an understatement. I am grateful for having the privilege of being his student. I was always in awe of his brilliance and compassion, and I aspire to be even half the person he was. He was a great mentor and friend, and I will truly cherish the time I have spent here at MIT learning from him.”
—Simran Chowdhry, graduate student in nuclear science and engineering
“Although I did not work with Nuno directly, my interactions with him through classes and his help with my qualifying exam left a profound impact on my life. Always student focused, Nuno never let his successes interfere with being a great educator and friend. Whether it was through quick updates in the hallways of the PSFC or joking about who makes the best espresso during meetings, Nuno was always willing to give students his time.”
—Evan Lambert, graduate student in nuclear science and engineering
“I was lucky to have taken Intro to Plasma with Nuno. Nuno was endlessly patient with my stubborn questions and filled each class with witty remarks. When I recently pitched him a project that he had every right to call crazy, he instead was nothing but supportive and had faith I could handle it. Nuno’s belief in the PSFC’s students will be sorely missed for years to come, and it is hard to imagine the center without him.”
—Grant Rutherford, graduate student in nuclear science and engineering
“Chairing my qualifying exam, Professor Loureiro tried to look stern, pushing me to the edges of my knowledge. A gentle smile revealed that he was still my biggest cheerleader, rooting for me to succeed. Nuno was a friend and mentor to all his students, teaching by listening, understanding, and encouraging us to persevere. I will fondly remember the thoughtful conversations I shared with him.”
—Nikola Goleš, graduate student in nuclear science and engineering
“In Nuno I found a mentor, a teacher, and a friend. Our work meetings always began with conversations about our families, moments that reminded me how deeply he cared about the people behind the work. He listened to me with generosity and patience, offered honest and unfiltered feedback, trusted my opinions, and helped shape them through thoughtful, critical discussions. He helped me grow and ultimately entrusted me with the role of division head. I will do my very best to honor him by continuing to support PSFC’s excellence, treasuring the lessons he taught me, and carrying in my heart his joyful smile.”
—Cristina Rea, Data Science Division Head at MIT Plasma Science and Fusion Center
“During a moment of intense stress, when I was visibly shaken and about to give a major presentation, Nuno noticed even as others were focused on the meeting ahead. He came over, quietly asked if I was okay, and waited for the answer. It’s clear to me that if I’d said no, he would’ve found a way to make space for me to collect myself. I’ll never forget that simple act of kindness and genuine care when I needed it most.”
—Julianna Mullen, communications director at MIT Plasma Science and Fusion Center
“A great smile upon entering the PSFC early every morning revealed to me Nuno’s delight to come work on his passions with his community, every day. His leadership was motivating. His energy was brighter than the plasmas he loved to observe and his purposeful steps leave great imprints on our spirits. Thank you, Nuno.”
—Alicia Valeriano, administrative assistant in the MIT Plasma Science and Fusion Center
The world’s most common construction material has a secret. Cement, the “glue” that holds concrete together, gradually “breathes in” and stores millions of tons of carbon dioxide (CO2) from the air over the lifetimes of buildings and infrastructure.
A new study from the MIT Concrete Sustainability Hub quantifies this process, carbon uptake, at a national scale for the first time. Using a novel approach, the research team found that the cement in U.S. buildings and infrastructure sequesters over 6.5 million metric tons of CO2 annually. This corresponds to roughly 13 percent of the process emissions — the CO2 released by the underlying chemical reaction — in U.S. cement manufacturing. In Mexico, the same building stock sequesters about 5 million tons a year.
But how did the team come up with those numbers?
Scientists have known how carbon uptake works for decades. CO2 enters concrete or mortar — the mixture that glues together blocks, brick, and stones — through tiny pores, reacts with the calcium-rich products in cement, and becomes locked into a stable mineral called calcium carbonate, or limestone.
The chemistry is well-known, but calculating the magnitude of this at scale is not. A concrete highway in Dallas sequesters CO2 differently than Mexico City apartments made from concrete masonry units (CMUs), also called concrete blocks or, colloquially, cinder blocks. And a foundation slab buried under the snow in Fairbanks, Alaska, “breathes in” CO2 at a different pace entirely.
As Hessam AzariJafari, lead author and research scientist in the MIT Department of Civil and Environmental Engineering, explains, “Carbon uptake is very sensitive to context. Four major factors drive it: the type of cement used, the product we make with it — concrete, CMUs, or mortar — the geometry of the structure, and the climate and conditions it’s exposed to. Even within the same structure, uptake can vary five-fold between different elements.”
As no two structures sequester CO2 in the same way, estimating uptake nationwide would normally require simulating an array of cement-based elements: slabs, walls, beams, columns, pavements, and more. On top of that, each of those has its own age, geometry, mixture, and exposure condition to account for.
Seeing that this approach would be like trying to count every grain of sand on a beach, the team took a different route. They developed hundreds of archetypes, typical designs that could stand in for different buildings and pieces of infrastructure. It’s a bit like measuring the beach instead by mapping out its shape, depth, and shoreline to estimate how much sand usually sits in a given spot.
With these archetypes in hand, the team modeled how each one sequesters CO2 in different environments and how common each is across every state in the United States and Mexico. In this way, they could estimate not just how much CO2 structures sequester, but why those numbers differ.
Two factors stood out. The first was the “construction trend,” or how the amount of new construction had changed over the previous five years. Because it reflects how quickly cement products are being added to the building stock, it shapes how much cement each state consumes and, therefore, how much of that cement is actively carbonating. The second was the ratio of mortar to concrete, since porous mortars sequester CO2 an order of magnitude faster than denser concrete.
In states where mortar use was higher, the fraction of CO2 uptake relative to process emissions was noticeably greater. “We observed something unique about Mexico: Despite using half the cement that the U.S. does, the country has three-quarters of the uptake,” notes AzariJafari. “This is because Mexico makes more use of mortars and lower-strength concrete, and bagged cement mixed on-site. These practices are why their uptake sequesters about a quarter of their cement manufacturing emissions.”
While care must be taken for structural elements that use steel reinforcement, as uptake can accelerate corrosion, it’s possible to enhance the uptake of many elements without negative impacts.
Randolph Kirchain, director of the MIT Concrete Sustainability Hub, principal research scientist in the MIT Materials Research Laboratory, and the senior author of this study, explains: “For instance, increasing the amount of surface area exposed to air accelerates uptake and can be achieved by foregoing painting or tiling, or choosing designs like waffle slabs with a higher surface area-to-volume ratio. Additionally, avoiding unnecessarily stronger, less-porous concrete mixtures than required would speed up uptake while using less cement.”
“There is a real opportunity to refine how carbon uptake from cement is represented in national inventories,” AzariJafari comments. “The buildings around us and the concrete beneath our feet are constantly ‘breathing in’ millions of tons of CO2. Nevertheless, some of the simplified values in widely used reporting frameworks can lead to higher estimates than what we observe empirically. Integrating updated science into international inventories and guidelines such as the Intergovernmental Panel on Climate Change (IPCC) would help ensure that reported numbers reflect the material and temporal realities of the sector.”
By offering the first rigorous, bottom-up estimation of carbon uptake at a national scale, the team’s work provides a more representative picture of cement’s environmental impact. As we work to decarbonize the built environment, understanding what our structures are already doing in the background may be just as important as the innovations we pursue moving forward. The approach developed by MIT researchers could be extended to other countries by combining global building-stock databases with national cement-production statistics. It could also inform the design of structures that safely maximize uptake.
The findings were published Dec. 15 in the Proceedings of the National Academy of Sciences. Joining AzariJafari and Kirchain on the paper are MIT researchers Elizabeth Moore of the Department of Materials Science and Engineering and the MIT Climate Project and former postdocs Ipek Bensu Manav SM ’21, PhD ’24 and Motahareh Rahimi, along with Bruno Huet and Christophe Levy from the Holcim Innovation Center in France.
Researchers at MIT and Stanford University have developed a new way to stimulate the immune system to attack tumor cells, using a strategy that could make cancer immunotherapy work for many more patients.
The key to their approach is reversing a “brake” that cancer cells engage to prevent immune cells from launching an attack. This brake is controlled by sugar molecules known as glycans that are found on the surface of cancer cells.
By blocking those glycans with molecules called lectins, the researchers showed they could dramatically boost the immune system’s response to cancer cells. To achieve this, they created multifunctional molecules known as AbLecs, which combine a lectin with a tumor-targeting antibody.
“We created a new kind of protein therapeutic that can block glycan-based immune checkpoints and boost anti-cancer immune responses,” says Jessica Stark, the Underwood-Prescott Career Development Professor in the MIT departments of Biological Engineering and Chemical Engineering. “Because glycans are known to restrain the immune response to cancer in multiple tumor types, we suspect our molecules could offer new and potentially more effective treatment options for many cancer patients.”
Stark, who is also a member of MIT’s Koch Institute for Integrative Cancer Research, is the lead author of the paper. Carolyn Bertozzi, a professor of chemistry at Stanford and director of the Sarafan ChEM Institute, is the senior author of the study, which appears today in Nature Biotechnology.
Releasing the brakes
Training the immune system to recognize and destroy tumor cells is a promising approach to treating many types of cancer. One class of immunotherapy drugs known as checkpoint inhibitors stimulate immune cells by blocking an interaction between the proteins PD-1 and PD-L1. This removes a brake that tumor cells use to prevent immune cells like T cells from killing cancer cells.
Drugs targeting the PD-1- PD-L1 checkpoint have been approved to treat several kinds of cancer. In some of these patients, checkpoint inhibitors can lead to long-lasting remission, but for many others, they don’t work at all.
In hopes of generating immune responses in a greater number of patients, researchers are now working on ways to target other immunosuppressive interactions between cancer cells and immune cells. One such interaction occurs between glycans on tumor cells and receptors found on immune cells.
Glycans are found on nearly all living cells, but tumor cells often express glycans that are not found on healthy cells, including glycans that contain a monosaccharide called sialic acid. When sialic acids bind to lectin receptors, located on immune cells, it turns on an immunosuppressive pathway in the immune cells. These lectins that bind to sialic acid are known as Siglecs.
“When Siglecs on immune cells bind to sialic acids on cancer cells, it puts the brakes on the immune response. It prevents that immune cell from becoming activated to attack and destroy the cancer cell, just like what happens when PD-1 binds to PD-L1,” Stark says.
Currently, there aren’t any approved therapies that target this Siglec-sialic acid interaction, despite a number of drug development approaches that have been tried. For example, researchers have tried to develop lectins that could bind to sialic acids and prevent them from interacting with immune cells, but so far, this approach hasn’t worked well because lectins don’t bind strongly enough to accumulate on the cancer cell surface in large numbers.
To overcome that, Stark and her colleagues developed a way to deliver larger quantities of lectins by attaching them to antibodies that target cancer cells. Once there, the lectins can bind to sialic acid, preventing sialic acid from interacting with Siglec receptors on immune cells. This lifts the brakes off the immune response, allowing immune cells such as macrophages and natural killer (NK) cells to launch an attack on the tumor.
“This lectin binding domain typically has relatively low affinity, so you can’t use it by itself as a therapeutic. But, when the lectin domain is linked to a high-affinity antibody, you can get it to the cancer cell surface where it can bind and block sialic acids,” Stark says.
A modular system
In this study, the researchers designed an AbLec based on the antibody trastuzumab, which binds to HER2 and is approved as a cancer therapy to treat breast, stomach, and colorectal cancers. To form the AbLec, they replaced one arm of the antibody with a lectin, either Siglec-7 or Siglec-9.
Tests using cells grown in the lab showed that this AbLec rewired immune cells to attack and destroy cancer cells.
The researchers then tested their AbLecs in a mouse model that was engineered to express human Siglec receptors and antibody receptors. These mice were then injected with cancer cells that formed metastases in the lungs. When treated with the AbLec, these mice showed fewer lung metastases than mice treated with trastuzumab alone.
The researchers also showed that they could swap in other tumor-specific antibodies, such as rituximab, which targets CD20, or cetuximab, which targets EGFR. They could also swap in lectins that target other glycans involved in immunosuppression, or antibodies that target checkpoint proteins such as PD-1.
“AbLecs are really plug-and-play. They’re modular,” Stark says. “You can imagine swapping out different decoy receptor domains to target different members of the lectin receptor family, and you can also swap out the antibody arm. This is important because different cancer types express different antigens, which you can address by changing the antibody target.”
Stark, Bertozzi, and others have started a company called Valora Therapeutics, which is now working on developing lead AbLec candidates. They hope to begin clinical trials in the next two to three years.
The research was funded, in part, by a Burroughs Wellcome Fund Career Award at the Scientific Interface, a Society for Immunotherapy of Cancer Steven A. Rosenberg Scholar Award, a V Foundation V Scholar Grant, the National Cancer Institute, the National Institute of General Medical Sciences, a Merck Discovery Biologics SEEDS grant, an American Cancer Society Postdoctoral Fellowship, and a Sarafan ChEM-H Postdocs at the Interface seed grant.
“Robot, make me a chair” An AI-driven system lets users design and build simple, multicomponent objects by describing them with words.Computer-aided design (CAD) systems are tried-and-true tools used to design many of the physical objects we use each day. But CAD software requires extensive expertise to master, and many tools incorporate such a high level of detail they don’t lend themselves to brainstorming or rapid prototyping.
In an effort to make design faster and more accessible for non-experts, researchers from MIT and elsewhere developed an AI-driven robotic assembly system that allows people to build physical objects by simply describing them in words.
Their system uses a generative AI model to build a 3D representation of an object’s geometry based on the user’s prompt. Then, a second generative AI model reasons about the desired object and figures out where different components should go, according to the object’s function and geometry.
The system can automatically build the object from a set of prefabricated parts using robotic assembly. It can also iterate on the design based on feedback from the user.
The researchers used this end-to-end system to fabricate furniture, including chairs and shelves, from two types of premade components. The components can be disassembled and reassembled at will, reducing the amount of waste generated through the fabrication process.
They evaluated these designs through a user study and found that more than 90 percent of participants preferred the objects made by their AI-driven system, as compared to different approaches.
While this work is an initial demonstration, the framework could be especially useful for rapid prototyping complex objects like aerospace components and architectural objects. In the longer term, it could be used in homes to fabricate furniture or other objects locally, without the need to have bulky products shipped from a central facility.
“Sooner or later, we want to be able to communicate and talk to a robot and AI system the same way we talk to each other to make things together. Our system is a first step toward enabling that future,” says lead author Alex Kyaw, a graduate student in the MIT departments of Electrical Engineering and Computer Science (EECS) and Architecture.
Kyaw is joined on the paper by Richa Gupta, an MIT architecture graduate student; Faez Ahmed, associate professor of mechanical engineering; Lawrence Sass, professor and chair of the Computation Group in the Department of Architecture; senior author Randall Davis, an EECS professor and member of the Computer Science and Artificial Intelligence Laboratory (CSAIL); as well as others at Google Deepmind and Autodesk Research. The paper was recently presented at the Conference on Neural Information Processing Systems.
Generating a multicomponent design
While generative AI models are good at generating 3D representations, known as meshes, from text prompts, most do not produce uniform representations of an object’s geometry that have the component-level details needed for robotic assembly.
Separating these meshes into components is challenging for a model because assigning components depends on the geometry and functionality of the object and its parts.
The researchers tackled these challenges using a vision-language model (VLM), a powerful generative AI model that has been pre-trained to understand images and text. They task the VLM with figuring out how two types of prefabricated parts, structural components and panel components, should fit together to form an object.
“There are many ways we can put panels on a physical object, but the robot needs to see the geometry and reason over that geometry to make a decision about it. By serving as both the eyes and brain of the robot, the VLM enables the robot to do this,” Kyaw says.
A user prompts the system with text, perhaps by typing “make me a chair,” and gives it an AI-generated image of a chair to start.
Then, the VLM reasons about the chair and determines where panel components go on top of structural components, based on the functionality of many example objects it has seen before. For instance, the model can determine that the seat and backrest should have panels to have surfaces for someone sitting and leaning on the chair.
It outputs this information as text, such as “seat” or “backrest.” Each surface of the chair is then labeled with numbers, and the information is fed back to the VLM.
Then the VLM chooses the labels that correspond to the geometric parts of the chair that should receive panels on the 3D mesh to complete the design.
Human-AI co-design
The user remains in the loop throughout this process and can refine the design by giving the model a new prompt, such as “only use panels on the backrest, not the seat.”
“The design space is very big, so we narrow it down through user feedback. We believe this is the best way to do it because people have different preferences, and building an idealized model for everyone would be impossible,” Kyaw says.
“The human‑in‑the‑loop process allows the users to steer the AI‑generated designs and have a sense of ownership in the final result,” adds Gupta.
Once the 3D mesh is finalized, a robotic assembly system builds the object using prefabricated parts. These reusable parts can be disassembled and reassembled into different configurations.
The researchers compared the results of their method with an algorithm that places panels on all horizontal surfaces that are facing up, and an algorithm that places panels randomly. In a user study, more than 90 percent of individuals preferred the designs made by their system.
They also asked the VLM to explain why it chose to put panels in those areas.
“We learned that the vision language model is able to understand some degree of the functional aspects of a chair, like leaning and sitting, to understand why it is placing panels on the seat and backrest. It isn’t just randomly spitting out these assignments,” Kyaw says.
In the future, the researchers want to enhance their system to handle more complex and nuanced user prompts, such as a table made out of glass and metal. In addition, they want to incorporate additional prefabricated components, such as gears, hinges, or other moving parts, so objects could have more functionality.
“Our hope is to drastically lower the barrier of access to design tools. We have shown that we can use generative AI and robotics to turn ideas into physical objects in a fast, accessible, and sustainable manner,” says Davis.
MIT community members elected to the National Academy of Inventors for 2025Professors Ahmad Bahai and Kripa Varanasi, plus seven additional MIT alumni, are honored for highly impactful inventions.The National Academy of Inventors (NAI) has named nine MIT affiliates as members of the 2025 class of NAI Fellows. They include Ahmad Bahai, an MIT professor of the practice in the Department of Electrical Engineering and Computer Science (EECS), and Kripa K. Varanasi, MIT professor in the Department of Mechanical Engineering, as well as seven additional MIT alumni. NAI fellowship is the highest professional distinction awarded solely to inventors.
“NAI Fellows are a driving force within the innovation ecosystem, and their contributions across scientific disciplines are shaping the future of our world,” says Paul R. Sanberg, fellow and president of the National Academy of Inventors. “We are thrilled to welcome this year’s class of fellows to the academy.”
This year’s 169 U.S. fellows represent 127 universities, government agencies, and research institutions across 40 U.S. states. Together, the 2025 class hold more than 5,300 U.S. patents and include recipients of the Nobel Prize, the National Medal of Science and National Medal of Technology and Innovation, as well as members of the national academies of Sciences, Engineering, and Medicine, among others.
Ahmad Bahai is professor of the practice in EECS. He was an adjunct professor at Stanford University from 2017 to 2022 and a professor in residence at the University of California at Berkeley from 2001 to 2010. Bahai has held a number of leadership roles, including director of research labs and chief technology officer of National Semiconductor, technical manager of a research group at Bell Laboratories, and founder of Algorex, a communication and acoustic integrated circuit and system company, which was acquired by National Semiconductor.
Currently, Bahai is the chief technology officer and director of corporate research of Texas Instruments and director of Kilby Labs and corporate research, and is a member of the Industrial Advisory Committee of CHIPS Act. Bahai is an IEEE Fellow and an AIMBE Fellow; he has authored over 80 publications in IEEE/IEE journals and holds more than 40 patents related to systems and circuits.
He holds an MS in electrical engineering from Imperial College London and a doctorate degree in electrical engineering from UC Berkeley.
Kripa K. Varanasi SM ’02, PhD ’04, professor of mechanical engineering, is widely recognized for his significant contributions in the field of interfacial science, thermal fluids, electrochemical systems, advanced materials, and manufacturing. A member of the MIT faculty since 2009, he leads the interdisciplinary Varanasi Research Group, which focuses on understanding physico-chemical and biological phenomena at the interfaces of matter. His group develops innovative surfaces, materials, devices, processes, and associated technologies that improve efficiency and performance across industries, including energy, decarbonization, life sciences, water, agriculture, transportation, and consumer products.
Varanasi has also scaled basic research into practical, market-ready technologies. He has co-founded six companies, including AgZen, Alsym Energy, CoFlo Medical, Dropwise, Infinite Cooling, and LiquiGlide, and his companies have been widely recognized for driving innovation across a range of industries. Throughout his career, Varanasi has been recognized for excellence in research and mentorship. Honors include the National Science Foundation CAREER Award, DARPA Young Faculty Award, SME Outstanding Young Manufacturing Engineer Award, ASME’s Bergles-Rohsenow Heat Transfer Award and Gustus L. Larson Memorial Award, Boston Business Journal’s 40 Under 40, and MIT’s Frank E. Perkins Award for Excellence in Graduate Advising.
Varanasi earned his undergraduate degree in mechanical engineering from the Indian Institute of Technology Madras, and his master’s degree and PhD from MIT. Prior to joining the faculty, he served as lead researcher and project leader at the GE Global Research Center, where he received multiple internal awards for innovation, leadership, and technical excellence. He was recently named faculty director of the Deshpande Center for Technological Innovation.
The seven additional MIT alumni who were elected to the NAI for 2025 include:
The NAI Fellows program was founded in 2012 and has grown to include 2,253 distinguished researchers and innovators, who hold over 86,000 U.S. patents and 20,000 licensed technologies. Collectively, NAI Fellows’ innovations have generated an estimated $3.8 trillion in revenue and 1.4 million jobs.
The 2025 class will be honored and presented with their medals by a senior official of the United States Patent and Trademark Office at the NAI 15th Annual Conference on June 4, 2026, in Los Angeles.
What makes a good proton conductor?MIT researchers found a way to predict how efficiently materials can transport protons in clean energy devices and other advanced technologies.A number of advanced energy technologies — including fuel cells, electrolyzers, and an emerging class of low-power electronics — use protons as the key charge carrier. Whether or not these devices will be widely adopted hinges, in part, on how efficiently they can move protons.
One class of materials known as metal oxides has shown promise in conducting protons at temperatures above 400 degrees Celsius. But researchers have struggled to find the best materials to increase the proton conductivity at lower temperatures and improve efficiency.
Now, MIT researchers have developed a physical model to predict proton mobility across a wide range of metal oxides. In a new paper, the researchers ranked the most important features of metal oxides for facilitating proton conduction, and demonstrated for the first time how much the flexibility of the materials’ oxide ions improves their ability to transfer protons.
The researchers believe their findings can guide scientists and engineers as they develop materials for more efficient energy technologies enabled by protons, which are lighter, smaller, and more abundant than more common charge carriers like lithium ions.
“If you understand the mechanism of a process and what material traits govern that mechanism, then you can tune those traits to improve the speed of that process — in this case, proton conduction,” says Bilge Yildiz, the Breen M. Kerr Professor in the departments of Nuclear Science and Engineering (NSE) and Materials Science and Engineering (DMSE) at MIT and the senior author of a paper describing the work. “For this application, we need to understand these quantitative relations between the proton transfer and the material’s structural, chemical, electronic, and dynamic traits. Establishing these relations can help us screen material databases to find compounds that satisfy those material traits, or even go beyond screening. There could be ways to use generative AI tools to create compounds that optimize for those traits.”
The paper appears in the journal Matter. Joining Yildiz are Heejung W. Chung, the paper’s first author and an MIT PhD student in DMSE; Pjotrs Žguns, a former postdoc in DMSE; and Ju Li, the Carl Richard Soderberg Professor of Power Engineering in NSE and DMSE.
Making protons hop
Protons are already used at scale in electrolyzers for hydrogen production and in fuel cells. They are also expected to be used in promising energy-storage technologies such as proton batteries, which could be water-based and rely on cheaper materials than lithium-ion batteries. A more recent and exciting application is low-energy, brain-inspired computing to emulate synaptic functions in devices for artificial intelligence.
“Proton conductors are important materials in different energy conversion technologies for clean electricity, clean fuels, and clean industrial chemical synthesis,” explains Yildiz. “Inorganic, scalable proton conductors that work at room temperature are also needed for energy-efficient brain-inspired computing.”
Protons, which are the positively charged state of hydrogen, are different from lithium or sodium ions because they don’t have their own electrons — protons consist of just the bare nucleus. Therefore, protons prefer to embed into the electron clouds of nearby ions, hopping from one to the next. In metal oxides, protons embed into oxygen ions, forming a covalent bond, and hop to a nearby oxygen ion through a hydrogen bond. After every hop, the covalent H-O bond rotates to prevent the proton from shuttling back and forth.
All that hopping and rotating got MIT’s researchers thinking that the flexibility of those oxide ion sublattices must be important for conducting protons. Indeed, their previous studies in another class of proton conductors had shown how lattice flexibility impacts proton transport.
For their study, the researchers created a metric to quantify lattice flexibility across materials that they call “O…O fluctuation,” which measures the change in spacing between oxygen ions contributed by phonons at finite temperature. They also created a dataset of other material features that influence proton mobility and set out to quantify how important each one is for facilitating proton conduction.
“We were trying to better understand how protons move through these inorganic materials so that we can optimize them and improve the efficiency of downstream energy and computing applications,” Chung explains.
The researchers ranked the importance of all seven features they studied, which also included structural and chemical traits of materials, and trained a model on the findings to predict how well materials would conduct protons. The model found that the two most important features in predicting proton transfer barriers are the hydrogen bond length and the oxygen sublattice flexibility characterized by the O…O fluctuation metric. The shorter the hydrogen bond length, the better the material was at transporting protons, which aligned with previous studies of metal oxides. The researchers’ O…O fluctuation metric was the new and the second most important feature they studied. The more flexible the oxygen ion chains, the better the proton conduction.
Better proton conductors
The researchers believe their model could be used to estimate proton conduction across a broader range of materials.
“We always have to be cautious about generalizing findings, but the local chemistries and structures we studied have a wide enough spectrum that we think this finding is broadly applicable to a range of inorganic proton conductors,” Yildiz says.
Beyond being used to screen for promising materials, the researchers say their findings could also be used to train generative AI models to create materials optimized for proton transfer. As our understanding of materials improves, that could enable a new class of hyper-efficient clean energy technologies.
“There are very large materials databases generated recently in the field, for example those by Google and Microsoft, that could be screened for these relations we’ve found,” Yildiz says. “If the material compound that satisfies these parameters does not exist, we could also use these parameters to generate new compounds. That would enable increases in the energy efficiency and viability of clean energy conversion and low-power computing devices. For that, we need to figure out how to get more flexible oxide ion sublattices that are percolated. What are the composition and structure metrics that I can use to design the material to have that flexibility? Those are the next steps.”
The research was supported by the U.S. Department of Energy’s Energy Frontier Center – Hydrogen in Energy and Information Sciences – and the National Science Foundation’s Graduate Research Fellowship Program.
Deep-learning model predicts how fruit flies form, cell by cellThe approach could apply to more complex tissues and organs, helping researchers to identify early signs of disease.During early development, tissues and organs begin to bloom through the shifting, splitting, and growing of many thousands of cells.
A team of MIT engineers has now developed a way to predict, minute by minute, how individual cells will fold, divide, and rearrange during a fruit fly’s earliest stage of growth. The new method may one day be applied to predict the development of more complex tissues, organs, and organisms. It could also help scientists identify cell patterns that correspond to early-onset diseases, such as asthma and cancer.
In a study appearing today in the journal Nature Methods, the team presents a new deep-learning model that learns, then predicts, how certain geometric properties of individual cells will change as a fruit fly develops. The model records and tracks properties such as a cell’s position, and whether it is touching a neighboring cell at a given moment.
The team applied the model to videos of developing fruit fly embryos, each of which starts as a cluster of about 5,000 cells. They found the model could predict, with 90 percent accuracy, how each of the 5,000 cells would fold, shift, and rearrange, minute by minute, during the first hour of development, as the embryo morphs from a smooth, uniform shape into more defined structures and features.
“This very initial phase is known as gastrulation, which takes place over roughly one hour, when individual cells are rearranging on a time scale of minutes,” says study author Ming Guo, associate professor of mechanical engineering at MIT. “By accurately modeling this early period, we can start to uncover how local cell interactions give rise to global tissues and organisms.”
The researchers hope to apply the model to predict the cell-by-cell development in other species, such zebrafish and mice. Then, they can begin to identify patterns that are common across species. The team also envisions that the method could be used to discern early patterns of disease, such as in asthma. Lung tissue in people with asthma looks markedly different from healthy lung tissue. How asthma-prone tissue initially develops is an unknown process that the team’s new method could potentially reveal.
“Asthmatic tissues show different cell dynamics when imaged live,” says co-author and MIT graduate student Haiqian Yang. “We envision that our model could capture these subtle dynamical differences and provide a more comprehensive representation of tissue behavior, potentially improving diagnostics or drug-screening assays.”
The study’s co-authors are Markus Buehler, the McAfee Professor of Engineering in MIT’s Department of Civil and Environmental Engineering; George Roy and Tomer Stern of the University of Michigan; and Anh Nguyen and Dapeng Bi of Northeastern University.
Points and foams
Scientists typically model how an embryo develops in one of two ways: as a point cloud, where each point represents an individual cell as point that moves over time; or as a “foam,” which represents individual cells as bubbles that shift and slide against each other, similar to the bubbles in shaving foam.
Rather than choose between the two approaches, Guo and Yang embraced both.
“There’s a debate about whether to model as a point cloud or a foam,” Yang says. “But both of them are essentially different ways of modeling the same underlying graph, which is an elegant way to represent living tissues. By combining these as one graph, we can highlight more structural information, like how cells are connected to each other as they rearrange over time.”
At the heart of the new model is a “dual-graph” structure that represents a developing embryo as both moving points and bubbles. Through this dual representation, the researchers hoped to capture more detailed geometric properties of individual cells, such as the location of a cell’s nucleus, whether a cell is touching a neighboring cell, and whether it is folding or dividing at a given moment in time.
As a proof of principle, the team trained the new model to “learn” how individual cells change over time during fruit fly gastrulation.
“The overall shape of the fruit fly at this stage is roughly an ellipsoid, but there are gigantic dynamics going on at the surface during gastrulation,” Guo says. “It goes from entirely smooth to forming a number of folds at different angles. And we want to predict all of those dynamics, moment to moment, and cell by cell.”
Where and when
For their new study, the researchers applied the new model to high-quality videos of fruit fly gastrulation taken by their collaborators at the University of Michigan. The videos are one-hour recordings of developing fruit flies, taken at single-cell resolution. What’s more, the videos contain labels of individual cells’ edges and nuclei — data that are incredibly detailed and difficult to come by.
“These videos are of extremely high quality,” Yang says. “This data is very rare, where you get submicron resolution of the whole 3D volume at a pretty fast frame rate.”
The team trained the new model with data from three of four fruit fly embryo videos, such that the model might “learn” how individual cells interact and change as an embryo develops. They then tested the model on an entirely new fruit fly video, and found that it was able to predict with high accuracy how most of the embryo’s 5,000 cells changed from minute to minute.
Specifically, the model could predict properties of individual cells, such as whether they will fold, divide, or continue sharing an edge with a neighboring cell, with about 90 percent accuracy.
“We end up predicting not only whether these things will happen, but also when,” Guo says. “For instance, will this cell detach from this cell seven minutes from now, or eight? We can tell when that will happen.”
The team believes that, in principle, the new model, and the dual-graph approach, should be able to predict the cell-by-cell development of other multiceullar systems, such as more complex species, and even some human tissues and organs. The limiting factor is the availability of high-quality video data.
“From the model perspective, I think it’s ready,” Guo says. “The real bottleneck is the data. If we have good quality data of specific tissues, the model could be directly applied to predict the development of many more structures.”
This work is supported, in part, by the U.S. National Institutes of Health.
Fraternities and sororities at MIT raise funds for local charities“Our students’ ... dedication reflects not only their generosity, but also the spirit of engaging the MIT community in giving back through philanthropy.”Throughout campus and across the river in Boston and Brookline, MIT hosts a vibrant network of 43 fraternities and sororities, with more than 35 percent of undergraduate students belonging to one of these value-based communities. Each fraternity and sorority is a unique community that not only fosters leadership and builds lifelong friendships, but also takes its role in giving back seriously.
Keeping up a 143-year-long tradition of philanthropy, several fraternities and sororities raised funds for a variety of local charities this fall, including the Breast Cancer Research Foundation, Boston Area Rape Crisis Center, and Dignity Matters of Boston.
With donations still coming in, Liz Jason, associate dean of Fraternities, Sororities and Independent Living Groups (FSILG) at MIT, says, “Philanthropy is a defining tradition within our FSILG community; it’s where values become action. When chapters give back, they strengthen their bonds, uplift others, and demonstrate what it truly means to be part of MIT: using talent, passion, and collective effort to make a real difference.”
To raise money, the fraternities and sororities hosted a variety of fun, clever, and even unique events and challenges over the course of the fall semester.
Sorority Alpha Chi Omega held an event called Walk a Mile in Her Shoes, where participants donned heels for a relay race-style event to raise awareness of gender stereotypes, domestic violence, and sexual assault. They also held a bake sale at the event, with funds going to the Boston Area Rape Crisis Center.
The Interfraternity Council (IFC) hosted a Greek Carnival on Kresge Oval in October to benefit the Boston Area Rape Crisis Center and to raise awareness about sexual violence. They held a variety of games and activities, including a dunk tank, a bake sale, a tug-of-war competition, and other field-day games.
“In my own chapter, Delta Tau Delta, I’ve seen an interest in increasing our philanthropic efforts, and as a member of the IFC Executive Board, I realized we could take the initiative to reduce barriers to entry for all chapters through a single large fundraising event,” says senior Luc Gaitskell.
In mid-November, the MIT Panhellenic Association created an event in which members of the community donated clothing, and then Panhel used the clothing to set up a one-time thrift shop where community members could come buy second-hand clothes at discounted prices. All the money raised was donated to Dignity Matters.
“Service has always been at the heart of what MIT Panhel does,” says senior Sabrina Chen. “We chose to partner with Dignity Matters because their mission of helping individuals stay healthy and regain self-confidence resonates with our commitment to supporting women and advancing equity. Our thrift shop was a perfect way to raise money for the organization while encouraging affordable, sustainable fashion.”
Division of Student Life vice chancellor Suzy Nelson explains, “Our students are committed to a range of causes; their dedication reflects not only their generosity, but also the spirit of engaging the MIT community in giving back through philanthropy.”
Students interested in joining a fraternity, sorority, or an independent living group can find more information on the Division of Student Life website.
MIT HEALS leadership charts a bold path for convergence in health and life sciencesAngela Koehler, Iain Cheeseman, and Katharina Ribbeck are shaping the collaborative as a platform for transformative research, translation, and talent development across MIT.In February, President Sally Kornbluth announced the appointment of Professor Angela Koehler as faculty director of the MIT Health and Life Sciences Collaborative (MIT HEALS), with professors Iain Cheeseman and Katharina Ribbeck as associate directors. Since then, the leadership team has moved quickly to shape HEALS into an ambitious, community-wide platform for catalyzing research, translation, and education at MIT and beyond — at a moment when advances in computation, biology, and engineering are redefining what’s possible in health and the life sciences.
Rooted in MIT’s long-standing strengths in foundational discovery, convergence, and translational science, HEALS is designed to foster connections across disciplines — linking life scientists and engineers with clinicians, computational scientists, humanists, operations researchers, and designers. The initiative builds on a simple premise: that solving today’s most pressing challenges in health and life sciences requires bold thinking, deep collaboration, and sustained investment in people.
“HEALS is an opportunity to rethink how we support talent, unlock scientific ideas, and translate them into impact,” says Koehler, the Charles W. and Jennifer C. Johnson Professor in the Department of Biological Engineering and associate director of the Koch Institute for Integrative Cancer Research. “We’re building on MIT’s best traditions — convergence, experimentation, and entrepreneurship — while opening new channels for interdisciplinary research and community building.”
Koehler says her own path has been shaped by that same belief in convergence. Early collaborations between chemists, engineers, and clinicians convinced her that bringing diverse people together — what she calls “induced proximity” — can spark discoveries that wouldn’t emerge in isolation.
A culture of connection
Since stepping into their roles, the HEALS leadership team has focused on building a collaborative ecosystem that enables researchers to take on bold, interdisciplinary challenges in health and life sciences. Rather than creating a new center or department, their approach emphasizes connecting the MIT community across existing boundaries — disciplinary, institutional, and cultural.
“We want to fund science that wouldn’t otherwise happen — projects that bridge gaps, open new doors, and bring researchers together in ways that are genuinely constructive and collaborative,” says Iain Cheeseman, the Herman and Margaret Sokol Professor of Biology, core member of the Whitehead Institute for Biomedical Research, and associate head of the Department of Biology.
That vision is already taking shape through initiatives like the MIT HEALS seed grants, which support bold new collaborations between MIT principal investigators; the MIT–Mass General Brigham Seed Program, which supports joint research between investigators at MIT and clinicians at MGB; and the Biswas Postdoctoral Fellowship Program, designed to bring top early-career researchers to MIT to pursue cross-cutting work in areas such as computational biology, biomedical engineering, and therapeutic discovery.
The leadership team sees these programs not as endpoints, but as starting points for a broader shift in how MIT supports health and life sciences research.
For Cheeseman, whose lab is working to build on their fundamental discoveries on how human cells function to impact cancer treatment and rare human disease, HEALS represents a way to connect deep biological discovery with the translational insights emerging from MIT’s engineering and clinical communities. He puts it simply: “to me, this is deeply personal, recognizing the limitations that existed for my own work and hoping to unlock these possibilities for researchers across MIT.”
Training the next generation
Ribbeck, a biologist focused on mucus and microbial ecosystems, sees HEALS as a way to train scientists who are as comfortable discussing patient needs as they are conducting experiments at the bench. She emphasizes that preparing the next generation of researchers means equipping them with fluency in areas like clinical language, regulatory processes, and translational pathways — skills many current investigators lack. “Many PIs, although they do clinical research, may not have dedicated support for taking their findings to the next level — how to design a clinical trial, or what regulatory questions need to be addressed — reflecting a broader structural gap in translational training” she says.
A central focus for the HEALS leadership team is building new models for training researchers to move fluidly between disciplines, institutions, and methods of translation. Ribbeck and Koehler stress the importance of giving students and postdocs hands-on opportunities that connect research with real-world experience. That means expanding programs like the Undergraduate Research Opportunities Program (UROP), the Advanced UROP (SuperUROP), and the MIT New Engineering Education Transformation, and creating new ways for trainees to engage with industry, clinical partners, and entrepreneurship. They are learning at the intersection of engineering, biology, and medicine — and increasingly across disciplines that span economics, design, the social sciences, and the humanities, where students are already creating collaborations that do not yet have formal pathways.
Koehler, drawing from her leadership at the Deshpande Center for Technological Innovation and the Koch Institute, notes that “if we invest in the people, the solutions to problems will naturally arise.” She envisions HEALS as a platform for induced proximity — not just of disciplines, but of people at different career stages, working together in environments that support both risk-taking and mentorship.
“For me, HEALS builds on what I’ve seen work at MIT — bringing people with different skill sets together to tackle challenges in life sciences and medicine,” she says. “It’s about putting community first and empowering the next generation to lead across disciplines.”
A platform for impact
Looking ahead, the HEALS leadership team envisions the collaborative as a durable platform for advancing health and life sciences at MIT. That includes launching flagship events, supporting high-risk, high-reward ideas, and developing partnerships across the biomedical ecosystem in Boston and beyond. As they see it, MIT is uniquely positioned for this moment: More than three-quarters of the Institute’s faculty work in areas that touch health and life sciences, giving HEALS a rare opportunity to bring that breadth together in new configurations and amplify impact across disciplines.
From the earliest conversations, the leaders have heard a clear message from faculty across MIT — a strong appetite for deeper connection, for working across boundaries, and for tackling urgent societal challenges together. That shared sense of momentum is what gave rise to HEALS, and it now drives the team’s focus on building the structures that can support a community that wants to collaborate at scale.
“Faculty across MIT are already reaching out — looking to connect with clinics, collaborate on new challenges, and co-create solutions,” says Koehler. “That hunger for connection is why HEALS was created. Now we have to build the structures that support it.”
Cheeseman adds that this collaborative model is what makes MIT uniquely positioned to lead. “When you bring together people from different fields who are motivated by impact,” he says, “you create the conditions for discoveries that none of us could achieve alone.”
A better DNA material for genetic medicineWith its circular single-stranded DNA molecules, MIT spinout Kano Therapeutics plans to make gene and cell therapies safer and more effective.To our immune system, a potentially lifesaving gene therapy can look a lot like a dangerous infection. That’s because most genetic medicine uses viruses or double-stranded DNA to deliver genetic information to target cells. DNA in its traditional double helix form can lead to toxic immune stimulation and be difficult to package into cellular delivery vehicles. As a result, the reach of genetic medicine is limited today.
Kano Therapeutics is taking a different approach to genetic therapies. The company is developing gene-editing technologies using circular single-stranded DNA (cssDNA), a biomolecule that is less toxic than double stranded DNA and more stable than RNA, and could be delivered more efficiently to many parts of the body to treat genetic diseases, cancers, and more.
The company, which was founded by former MIT postdoc Floris Engelhardt, professor of biological engineering Mark Bathe, and John Vroom MBA ’22, is developing a platform for manufacturing cssDNA of customized lengths and sequences, which could deliver genetic material to fix or replace faulty genes.
“We can work with CRISPR and other gene-editing technologies,” Engelhardt says. “CRISPR finds a location in a genome, binds to it, and cuts at that location. That allows you to edit a gene or stop a gene from functioning. But what if you have a loss-of-function disease where you need to insert a new piece of genetic code? Our approach allows you to replace whole genes or add genetic information.”
Making DNA flexible
Around 2019, Bathe’s lab published research describing ways to engineer the sequence and length of cssDNA molecules, which have been used in labs for decades but have increasingly drawn interest for improving gene therapies. Several pharmaceutical companies immediately reached out.
“Single-stranded DNA is a little like messenger RNA, which can code for any protein in any cell, tumor, or organ,” Bathe says. “It fundamentally encodes for a protein, so it can be used across diseases, including rare diseases that may only affect a few people in the country.”
Engelhardt had also worked on cssDNA as a PhD student in Munich. She met Bathe at a conference.
“We were considering collaborating on research,” Engelhardt recalls. “Then Mark heard I was finishing my PhD and said, ‘Wait a minute. Instead of collaborating, I should hire you.’”
Within 48 hours of submitting her PhD thesis, Engelhardt received an email asking her to apply to Bathe’s lab as a postdoc. She was drawn to the position because she would be focusing on research that had the potential to help patients.
“MIT is very good at creating industry-focused postdocs,” Engelhardt says. “I was inspired by the idea of doing postdoc work with the goal of spinning out a company, as opposed to doing solely academic-focused research.”
Bathe and Engelhardt learned from members of the pharmaceutical industry how single-stranded DNA could help overcome limitations in gene and cell therapies. Although CRISPR-based treatments have recently been approved for a few genetic diseases, CRISPR’s effectiveness has been limited by its potential toxicity and inefficient delivery to specific sites in the body. Also, those treatments can only be administered once because CRISPR often gets labeled as foreign by our immune systems and rejected from the body.
Engelhardt began exploring MIT’s resources to help commercialize her research. She met Vroom through an online “founder speed dating” event at MIT. She also received support from the Venture Mentoring Service, took classes at MIT’s Sloan School of Management, and worked with MIT’s Industrial Liaison Program. Early on, Bathe suggested Engelhardt work with MIT’s Technology License Office, something she says she tells every founder to do the moment they start thinking about commercializing their research.
In 2021, Kano won the $20,000 first place prize at the MIT Sloan Healthcare Innovation Prize (SHIP) to commercialize a new way to design and manufacture single-stranded DNA. Kano uses fermentation to produce its cssDNA less expensively than approaches based on chemical DNA synthesis.
“No one had the ability to access this type of genetic material, and so a lot of our work was around creating the highest-quality, economically scalable process to allow circular single-stranded DNA to be commercially viable,” Engelhardt says.
Engelhardt and Vroom began meeting with investors as soon as Engelhardt finished her postdoc work in 2021. The founders worked to raise money over the next year while Vroom finished his MBA.
Today, Kano’s circular ssDNA can be used to insert entire genes, up to 10,000 nucleotides long, into the body. Kano is planning to partner with pharmaceutical companies to make their gene therapies more targeted and potent. For instance, pharmaceutical partners could use Kano’s platform to join the CD19 and CD20 genes, which are expressed in certain tumor cells, and stipulate that only if both genes bind to a cell receptor do they enter that cell’s genome and make edits.
Overall, Engelhardt says working with circular single-stranded DNA makes Kano’s approach more flexible than platforms like CRISPR.
“We realized working with pharmaceutical companies early on in my postdoc there was a lack of design understanding because of the lack of access to these molecules,” Engelhardt says. “When it comes to gene or cell therapies, people just think of the gene itself, not the flanking sequences or anything else that goes around the gene. Now that the DNA isn’t stuck in a double helix all the time, I can create small, three-dimensional structures — think loops or hairpins — that work, for example, as a binding protein that pulls it into the nucleus. That unlocks a completely new path for DNA because it makes it engineerable — not only on a structural level but also a sequence level.”
Partnering for impact
To facilitate more partnerships, Kano is signing agreements with partners that give it a smaller percentage of eventual drug royalties but allow it to work with many companies at the same time. In a recent collaboration with Merck KGaA, Kano combined its circular cssDNA platform with the company’s lipid nanoparticles solutions for delivering gene therapies. Kano is also in discussions with other large pharmaceutical companies to jointly bring cancer drugs into the clinic over the next two years.
“That’s exciting because we’ll be implementing our DNA into partners’ drug system, so when they file their new drug and dose their first patients, our DNA is going to be the therapeutic information carrier for efficacy,” Engelhardt says. “As a first-time founder, this is where you want to go. We talk about patient impact all the time, and this is how we’re going to get it.”
Kano is also developing the first databank mapping cssDNA designs to activity, to speed up the development of new treatments.
“Right now, there is no understanding of how to design DNA for these therapies,” Engelhardt says. “Everyone who wants to differentiate needs to come up with a new editing tool, a new delivery tool, and there’s no connecting company that can enable those areas of expertise. When partners come to us, we can say, ‘The gene sequence is all yours.’ But often it’s not just about the sequence. It’s also about the promoter or flanking sequence that allows you to insert your DNA into the genome, or that makes DNA package well into your delivery nanoparticle. At Kano, we’re building the best knowledgebase to use DNA material to treat diseases.”
President Tharman Shanmugaratnam of Singapore visits MITThe leader accepted the Miriam Pozen Prize for international financial policy and delivered a lecture at the MIT Sloan School of Management.President Tharman Shanmugaratnam of the Republic of Singapore visited MIT on Tuesday, meeting campus leaders while receiving the Miriam Pozen Prize and delivering a lecture on fiscal policy at the MIT Sloan School of Management.
“We really have to re-orient fiscal policy and develop new fiscal compacts,” said Tharman in his remarks, referring to the budget policy challenges countries face at a time of expanding government debt.
His talk, “The Compacts We Need: Fiscal Choices and Risk-sharing for Sustained Prosperity,” was delivered before a capacity audience of students, faculty, administrators, and staff at MIT’s Samberg Center.
Tharman is a trained economist who for many years ran Singapore’s central bank and has become a notable presence in global policymaking circles. Presenting a crisp summary of global trends, he observed that debt levels in major economies are at or beyond levels once regarded as unsustainable.
“There is no realistic solution to putting government debts back on a sustainable path other than having to make major adjustments to taxes and spending,” he said. However, he emphasized that his remarks were distinctly not “a call for austerity.” Instead, as he outlined, well-considered public investment can reduce the need for additional spending and thus be fiscally sound over time.
For instance, he noted, sound policy approaches can reduce individuals’ health care needs by better providing the conditions in which people stay healthy. Lowering some of these individual burdens and investing in community-building policies can help society both fiscally and by enhancing social solidarity.
“The challenge is to make these adjustments while re-fashioning fiscal policy so that people can see the adjustments — they can see the value in government spending that their taxes are contributing to — and to make adjustments in a way that doesn’t reduce growth,” Tharman said. “You do need growth for solidarity.”
In this sense, he proposed, “We need new fiscal compacts, new retirement compacts, and new global compacts to address the risks that are posed in the minds of individuals, as well as the largest risks” in society. Countries are vulnerable to a variety of shocks, he noted, calling climate change the “defining challenge of our time.” And yet, he added, for all of this, sensible policymaking can encourage people, creating more support for public-minded governance.
“It is that sharing of hopes and aspirations that is at the heart of true solidarity, not the sharing of fears,” Tharman concluded.
Before the lecture, Tharman was greeted by MIT Provost Anantha Chandrakasan, who presented him with a small gift from the MIT Glass Lab, and MIT Sloan Dean Richard Locke. Locke then made welcoming remarks at the event, praising Tharman’s “remarkable leadership in international financial policy, among other things.” After the lecture, Tharman also met with a group of MIT students from Singapore.
The Miriam Pozen Prize is awarded every two years by the MIT Golub Center for Finance and Policy, part of MIT Sloan. The prize, which recognizes extraordinary contributions to financial policy, was created to draw attention to the important research on financial policy conducted at the Golub Center, whose mission is to support research and educational initiatives related to governments’ roles as financial institutions and as regulators of the global financial system. It is named for the mother of MIT Sloan Senior Lecturer Robert C. Pozen, who is also the former executive chairman of MFS Investment Management, and a former vice chairman of Fidelity Investments and president of Fidelity Management and Research Company.
In introductory remarks. Robert Pozen said he was “deeply honored” to present the prize, adding, “It’s very unusual to have someone who is both a brilliant economist and an effective political leader, and that combination is exactly what we’re trying to honor and recognize.”
The previous recipients of the award are Mario Draghi PhD ’77, the former prime minister of Italy and president of the European Central Bank; and the late Stanley Fischer PhD ’69, an influential MIT economist who later became governor of the Bank of Israel, and then vice-chairman of the U.S. Federal Reserve. Draghi received the honor in 2023, and Fischer in 2021.
Tharman was first elected to his current office in 2023. In Singapore, he previously served as, among other roles, deputy prime minister, minister for finance, minister for education, and chairman of the Monetary Authority of Singapore.
Tharman holds a BA in economics from the London School of Economics, an MA in economics from the University of Cambridge, and an MPA from the Harvard Kennedy School at Harvard University.
MIT and Singapore have developed a sustained and productive relationship in research and education over the last quarter-century. The Singapore-MIT Alliance for Research and Technology (SMART), formally launched in 2007, is MIT’s first research center located outside of the United States, featuring work in several interdisciplinary areas of innovation.
The MIT-Singapore program also provides MIT students with research, work, and educational opportunities in Singapore. Additionally, MIT Institute Professor Emeritus Thomas Magnanti, who was present at Tuesday’s event, was the founding president of the Singapore University of Technology and Design, in 2009.
Tuesday’s event also had introductory remarks from Deborah J. Lucas, Sloan Distinguished Professor of Finance at MIT Sloan and director of the MIT Golub Center for Finance and Policy; Peter Fischer, Golub Distinguished Senior Fellow at MIT Sloan and a former under secretary in the U.S. Treasury Department; and Robert C. Merton, School of Managament Distinguished Professor of Finance at MIT Sloan.
In her comments, Lucas said that Tharman “personifies the qualities the award was created to honor,” while Fischer cited his emphasis on “the betterment of humankind.”
Merton praised Tharman’s “deep commitment for advancing financial policy in a way that serves both national and global arenas.” He added: “You have always believed that policy is not just about numbers, but about people. And that sound financial [policies] serve the many, not just the few.”
New method improves the reliability of statistical estimationsThe technique can help scientists in economics, public health, and other fields understand whether to trust the results of their experiments.Let’s say an environmental scientist is studying whether exposure to air pollution is associated with lower birth weights in a particular county.
They might train a machine-learning model to estimate the magnitude of this association, since machine-learning methods are especially good at learning complex relationships.
Standard machine-learning methods excel at making predictions and sometimes provide uncertainties, like confidence intervals, for these predictions. However, they generally don’t provide estimates or confidence intervals when determining whether two variables are related. Other methods have been developed specifically to address this association problem and provide confidence intervals. But, in spatial settings, MIT researchers found these confidence intervals can be completely off the mark.
When variables like air pollution levels or precipitation change across different locations, common methods for generating confidence intervals may claim a high level of confidence when, in fact, the estimation completely failed to capture the actual value. These faulty confidence intervals can mislead the user into trusting a model that failed.
After identifying this shortfall, the researchers developed a new method designed to generate valid confidence intervals for problems involving data that vary across space. In simulations and experiments with real data, their method was the only technique that consistently generated accurate confidence intervals.
This work could help researchers in fields like environmental science, economics, and epidemiology better understand when to trust the results of certain experiments.
“There are so many problems where people are interested in understanding phenomena over space, like weather or forest management. We’ve shown that, for this broad class of problems, there are more appropriate methods that can get us better performance, a better understanding of what is going on, and results that are more trustworthy,” says Tamara Broderick, an associate professor in MIT’s Department of Electrical Engineering and Computer Science (EECS), a member of the Laboratory for Information and Decision Systems (LIDS) and the Institute for Data, Systems, and Society, an affiliate of the Computer Science and Artificial Intelligence Laboratory (CSAIL), and senior author of this study.
Broderick is joined on the paper by co-lead authors David R. Burt, a postdoc, and Renato Berlinghieri, an EECS graduate student; and Stephen Bates an assistant professor in EECS and member of LIDS. The research was recently presented at the Conference on Neural Information Processing Systems.
Invalid assumptions
Spatial association involves studying how a variable and a certain outcome are related over a geographic area. For instance, one might want to study how tree cover in the United States relates to elevation.
To solve this type of problem, a scientist could gather observational data from many locations and use it to estimate the association at a different location where they do not have data.
The MIT researchers realized that, in this case, existing methods often generate confidence intervals that are completely wrong. A model might say it is 95 percent confident its estimation captures the true relationship between tree cover and elevation, when it didn’t capture that relationship at all.
After exploring this problem, the researchers determined that the assumptions these confidence interval methods rely on don’t hold up when data vary spatially.
Assumptions are like rules that must be followed to ensure results of a statistical analysis are valid. Common methods for generating confidence intervals operate under various assumptions.
First, they assume that the source data, which is the observational data one gathered to train the model, is independent and identically distributed. This assumption implies that the chance of including one location in the data has no bearing on whether another is included. But, for example, U.S. Environmental Protection Agency (EPA) air sensors are placed with other air sensor locations in mind.
Second, existing methods often assume that the model is perfectly correct, but this assumption is never true in practice. Finally, they assume the source data are similar to the target data where one wants to estimate.
But in spatial settings, the source data can be fundamentally different from the target data because the target data are in a different location than where the source data were gathered.
For instance, a scientist might use data from EPA pollution monitors to train a machine-learning model that can predict health outcomes in a rural area where there are no monitors. But the EPA pollution monitors are likely placed in urban areas, where there is more traffic and heavy industry, so the air quality data will be much different than the air quality data in the rural area.
In this case, estimates of association using the urban data suffer from bias because the target data are systematically different from the source data.
A smooth solution
The new method for generating confidence intervals explicitly accounts for this potential bias.
Instead of assuming the source and target data are similar, the researchers assume the data vary smoothly over space.
For instance, with fine particulate air pollution, one wouldn’t expect the pollution level on one city block to be starkly different than the pollution level on the next city block. Instead, pollution levels would smoothly taper off as one moves away from a pollution source.
“For these types of problems, this spatial smoothness assumption is more appropriate. It is a better match for what is actually going on in the data,” Broderick says.
When they compared their method to other common techniques, they found it was the only one that could consistently produce reliable confidence intervals for spatial analyses. In addition, their method remains reliable even when the observational data are distorted by random errors.
In the future, the researchers want to apply this analysis to different types of variables and explore other applications where it could provide more reliable results.
This research was funded, in part, by an MIT Social and Ethical Responsibilities of Computing (SERC) seed grant, the Office of Naval Research, Generali, Microsoft, and the National Science Foundation (NSF).
School of Science welcomed new faculty in 2024Eleven new professors join the departments of Biology; Brain and Cognitive Sciences; Earth, Atmospheric and Planetary Sciences; Mathematics; and Physics.The School of Science welcomed 11 new faculty members in 2024.
Shaoyun Bai researches symplectic topology, the study of even-dimensional spaces whose properties are reflected by two-dimensional surfaces inside them. He is interested in this area’s interaction with other fields, including algebraic geometry, algebraic topology, geometric topology, and dynamics. He has been developing new tool kits for counting problems from moduli spaces, which have been applied to classical questions, including the Arnold conjecture, periodic points of Hamiltonian maps, higher-rank Casson invariants, enumeration of embedded curves, and topology of symplectic fibrations.
Bai completed his undergraduate studies at Tsinghua University in 2017 and earned his PhD in mathematics from Princeton University in 2022, advised by John Pardon. Bai then held visiting positions at MSRI (now known as Simons Laufer Mathematical Sciences Institute) as a McDuff Postdoctoral Fellow and at the Simons Center for Geometry and Physics, and he was a Ritt Assistant Professor at Columbia University. He joined the MIT Department of Mathematics as an assistant professor in 2024.
Abigail Bodner investigates turbulence in the upper ocean using remote sensing measurements, in-situ ocean observations numerical simulations, climate models, and machine learning. Her research explores how the small-scale physics of turbulence near the ocean surface impacts the large-scale climate.
Bodner earned a BS and MS from Tel Aviv University studying mathematics and geophysics, atmospheric and planetary sciences. She then went on to Brown University, earning an MS in applied mathematics before completing her PhD studies in 2021 in Earth, environmental, and planetary science. Prior to coming to MIT, Bodner was a Simons Society Junior Fellow at New York University. Abigail Bodner is an assistant professor in the Department of Earth, Atmospheric, and Planetary Sciences, holding an MIT Schwarzman College of Computing shared position with the Department of Electrical Engineering and Computer Science.
Jacopo Borga is interested in probability theory and its connections to combinatorics, and in mathematical physics. He studies various random combinatorial structures — mathematical objects such as graphs or permutations — and their patterns and behavior at a large scale. This research includes random permutons, meanders, multidimensional constrained Brownian motions, Schramm-Loewner evolutions, and Liouville quantum gravity.
Borga earned bachelor’s and master’s degrees in mathematics from the Università degli Studi di Padova, and a master’s degree in mathematics from Université Sorbonne Paris Cité (USPC), then proceeded to complete a PhD in mathematics at Unstitut für Mathematik at the Universität Zürich. Borga was an assistant professor at Stanford University before joining MIT as an assistant professor of mathematics in 2024.
Linlin Fan aims to decipher the neural codes underlying learning and memory and to identify the physical basis of learning and memory. Her research focus is on the learning rules of brain circuits — what kinds of activity trigger the encoding and storing of information — how these learning rulers are implemented, and how memories can be inferred from mapping neural functional connectivity patterns. To answer these questions, Fan’s group leverages high-precision, all-optical technologies to map and control the electrical charges of neurons within the brain.
Fan earned her PhD at Harvard University after undergraduate studies at Peking University in China. She joined the MIT Department of Brain and Cognitive Sciences as the Samuel A. Goldblith Career Development Professor of Applied Biology, and the Picower Institute for Learning and Memory as an investigator in January 2024. Previously, Fan worked as a postdoc at Stanford University.
Whitney Henry investigates ferroptosis, a type of cell death dependent on iron, to uncover how oxidative stress, metabolism, and immune signaling intersect to shape cell fate decisions. Her research has defined key lipid metabolic and iron homeostatic programs that regulate ferroptosis susceptibility. By uncovering the molecular factors influencing ferroptosis susceptibility, investigating its effects on the tumor microenvironment, and developing innovative methods to manipulate ferroptosis resistance in living organisms, Henry’s lab aims to gain a comprehensive understanding of the therapeutic potential of ferroptosis, especially to target highly metastatic, therapy-resistant cancer cells.
Henry received her bachelor's degree in biology with a minor in chemistry from Grambling State University and her PhD from Harvard University. Following her doctoral studies, she worked at the Whitehead Institute for Biomedical Research and was supported by fellowships from the Jane Coffin Childs Memorial Fund for Medical Research and the Ludwig Center at MIT. Henry joined the MIT faculty in 2024 as an assistant professor in the Department of Biology and a member of the Koch Institute for Integrative Cancer Research, and was recently named the Robert A. Swanson (1969) Career Development Professor of Life Sciences and a HHMI Freeman Hrabowski Scholar.
Gian Michele Innocenti is an experimental physicist who probes new regimes of quantum chromodynamics (QCD) through collisions of ultra relativistic heavy ions at the Large Hadron Collider. He has developed advanced analysis techniques and data-acquisition strategies that enable novel measurements of open heavy-flavor and jet production in hadronic and ultraperipheral heavy-ion collisions, shedding light on the properties of high-temperature QCD matter and parton dynamics in Lorentz-contracted nuclei. He leads the MIT Pixel𝜑 program, which exploits CMOS MAPS technology to build a high-precision tracking detector for the ePIC experiment at the Electron–Ion Collider.
Innocenti received his PhD in particle and nuclear physics at the University of Turin in Italy in early 2014. He then joined the MIT heavy-ion group in the Laboratory of Nuclear Science in 2014 as a postdoc, followed by a staff research physicist position at CERN in 2018. Innocenti joined the MIT Department of Physics as an assistant professor in January 2024.
Mathematician Christoph Kehle's research interests lie at the intersection of analysis, geometry, and partial differential equations. In particular, he focuses on the Einstein field equations of general relativity and our current understanding of gravitation, which describe how matter and energy shape spacetime. His work addresses the Strong Cosmic Censorship conjecture, singularities in black hole interiors, and the dynamics of extremal black holes.
Prior to joining MIT, Kehle was a junior fellow at ETH Zürich and a member at the Institute for Advanced Study in Princeton. He earned his bachelor’s and master’s degrees at Ludwig Maximilian University and Technical University of Munich, and his PhD in 2020 from the University of Cambridge. Kehle joined the Department of Mathematics as an assistant professor in July 2024.
Aleksandr Logunov is a mathematician specializing in harmonic analysis and geometric analysis. He has developed novel techniques for studying the zeros of solutions to partial differential equations and has resolved several long-standing problems, including Yau’s conjecture, Nadirashvili’s conjecture, and Landis’ conjectures.
Logunov earned his PhD in 2015 from St. Petersburg State University. He then spent two years as a postdoc at Tel Aviv University, followed by a year as a member of the Institute for Advanced Study in Princeton. In 2018, he joined Princeton University as an assistant professor. In 2020, he spent a semester at Tel Aviv University as an IAS Outstanding Fellow, and in 2021, he was appointed full professor at the University of Geneva. Logunov joined MIT as a full professor in the Department of Mathematics in January 2024.
Lyle Nelson is a sedimentary geologist studying the co-evolution of life and surface environments across pivotal transitions in Earth history, especially during significant ecological change — such as extinction events and the emergence of new clades — and during major shifts in ocean chemistry and climate. Studying sedimentary rocks that were tectonically uplifted and are now exposed in mountain belts around the world, Nelson’s group aims to answer questions such as how the reorganization of continents influenced the carbon cycle and climate, the causes and effects of ancient ice ages, and what factors drove the evolution of early life forms and the rapid diversification of animals during the Cambrian period.
Nelson earned a bachelor’s degree in earth and planetary sciences from Harvard University in 2015 and then worked as an exploration geologist before completing his PhD at Johns Hopkins University in 2022. Prior to coming to MIT, he was an assistant professor in the Department of Earth Sciences at Carleton University in Ontario, Canada. Nelson joined the EAPS faculty in 2024.
Protein evolution is the process by which proteins change over time through mechanisms such as mutation or natural selection. Biologist Sergey Ovchinnikov uses phylogenetic inference, protein structure prediction/determination, protein design, deep learning, energy-based models, and differentiable programming to tackle evolutionary questions at environmental, organismal, genomic, structural, and molecular scales, with the aim of developing a unified model of protein evolution.
Ovchinnikov received his BS in micro/molecular biology from Portland State University in 2010 and his PhD in molecular and cellular biology from the University of Washington in 2017. He was next a John Harvard Distinguished Science Fellow at Harvard University until 2023. Ovchinnikov joined MIT as an assistant professor of biology in January 2024.
Shu-Heng Shao explores the structural aspects of quantum field theories and lattice systems. Recently, his research has centered on generalized symmetries and anomalies, with a particular focus on a novel type of symmetry without an inverse, referred to as non-invertible symmetries. These new symmetries have been identified in various quantum systems, including the Ising model, Yang-Mills theories, lattice gauge theories, and the Standard Model. They lead to new constraints on renormalization group flows, new conservation laws, and new organizing principles in classifying phases of quantum matter.
Shao obtained his BS in physics from National Taiwan University in 2010, and his PhD in physics from Harvard University in 2016. He was then a five-year long-term member at the Institute for Advanced Study in Princeton before he moved to the Yang Institute for Theoretical Physics at Stony Brook University as an assistant professor in 2021. In 2024, he joined the MIT faculty as an assistant professor of physics.
A new way to deliver antibodies could make treatment much easier for patientsTherapeutic antibodies packaged into microparticles could be injected with a standard syringe, avoiding the need for lengthy and often uncomfortable infusions.Antibody treatments for cancer and other diseases are typically delivered intravenously, because of the large volumes that are needed per dose. This means the patient has to go to a hospital for every treatment, where they may spend hours receiving the infusion.
MIT engineers have now taken a major step toward reformulating antibodies so that they can be injected using a standard syringe. The researchers found a way to create solid particles of highly concentrated antibodies, suspended in a solution. These particles carry enough antibodies that only about 2 milliliters of solution would be needed per dose.
This advance could make it much easier for patients to receive antibody treatments, and could make treatment more accessible for patients who have difficulty coming into a hospital, including older people.
“As the global population ages, making the treatment process more convenient and accessible for those populations is something that needs to be addressed,” says Talia Zheng, an MIT graduate student who is the lead author of the new study.
Patrick Doyle, the Robert T. Haslam Professor of Chemical Engineering, is the senior author of the open-access paper, which appears in Advanced Materials. MIT graduate student Lucas Attia and Janet Teng ’25 are also authors of the study.
Highly concentrated antibodies
Therapeutic antibody drugs such as rituximab, which is used to treat some cancers, consist of antibodies suspended in a water-based solution. In addition to cancers, antibodies are also used to treat infectious diseases, as well as autoimmune disorders such as rheumatoid arthritis, inflammatory bowel disease, and multiple sclerosis.
Because the antibody solutions are formulated at low concentrations (10 to 30 milligrams of antibody per milliliter of solution), patients need to be given at least 100 milliliters per dose, which is much too large to be injected using a standard syringe. To decrease this volume to the point where it could be injected, the antibody concentration would need to be at least 300 milligrams per milliliter, but that would make the solution much too thick to be injected.
“You can’t concentrate existing formulations to these concentrations,” Doyle says. “They’ll be very viscous and will exceed the force threshold of what you can inject into a patient.”
In 2023, Doyle’s lab developed a way to generated highly concentrated antibody formulations by encapsulating them into hydrogel particles. However, that process requires centrifugation, a step that would be difficult to scale up for manufacturing.
In their new study, the researchers took a different approach that allows them to create droplets suspended in an emulsion, similar to oil and vinegar. In this case, droplets containing antibodies dissolved in a watery solution are suspended in an organic solvent called pentanol.
These droplets can then be dehydrated, leaving behind highly concentrated solid antibodies — about 360 milligrams of antibody per milliliter of solution. These particles also include a small amount of polyethylene glycol (PEG), a polymer that helps stabilize the particles.
Once these solid particles form, the organic solvent surrounding them is removed and replaced with an aqueous solution (water containing dissolved salts and small amount of stabilizing polymer), similar to the solution now used to infuse therapeutic antibodies.
This assembly process can be done rapidly using a microfluidic setup and does not require centrifugation, which should allow it to be scaled up much more easily using emulsification devices compliant with GMP (good manufacturing practice) regulations.
“Our first approach was a bit brute force, and when we were developing this new approach, we said to it’s got to be simple if it’s going to be better and scalable,” Doyle says.
Injectable particles
The researchers showed that they could control the size of the particles — from about 60 to 200 microns in diameter — by changing the flow rate of the solutions that make up the droplets.
Using particles 100 microns in diameter, they tested the injectability of the solution using a mechanical force tester. Those studies showed that the force needed to push the plunger of a syringe containing the particle solution was less than 20 newtons.
“That is less than half of the maximum acceptable force that people usually try to aim for, so it’s very injectable,” Zheng says.
Using a 2-milliliter syringe, a typical size for subcutaneous injections, more than 700 milligrams of the target antibody could be given at once — enough for most therapeutic applications. The researchers also showed that their formulations remained stable under refrigeration for at least four months.
The researchers now plan to test their antibody particles for therapeutic applications in animal models. They are also working on scaling up the manufacturing process, so they can make enough for large-scale testing.
The research was funded by the MIT Undergraduate Research Opportunities Program and the U.S. Department of Energy.
Lisa Su ’90, SM ’91, PhD ’94 to deliver MIT’s 2026 Commencement addressAn electrical engineer by training, Su is the chair and CEO of the semiconductor company AMD.Lisa Su ’90, SM ’91, PhD ’94, a leading executive in the semiconductor industry and head of the company Advanced Micro Devices (AMD), will deliver the address at the OneMIT Commencement Ceremony on Thursday, May 28.
As chair and CEO of AMD, Su has transformed the company, which is now a global leader in high-performance and AI computing. In addition to designing industry-leading CPUs and the specialized GPUs that enable AI applications, AMD technology is the foundation of many of the world’s most advanced supercomputers and high-performance computing systems. The company continues to work on next-generation hardware and open software that will accelerate the adoption of AI, which Su has described as the most transformational technology of our time.
Su has maintained a close relationship with MIT since her days as a student. She was the speaker at the 2017 doctoral hooding ceremony, and in 2018 she established the Lisa Su Fellowship Fund. She served on the Electrical Engineering and Computer Science Visiting Committee for 10 years. In 2022, Building 12, which houses MIT.nano, was named in her honor.
“Long before she led the spectacular turnaround of AMD and lent her name to MIT’s world-class nano facility, Lisa Su was an MIT student who inspired and mentored her classmates. During her PhD studies, she created instructions that guided generations of student researchers in using some of the Institute’s most advanced equipment,” says MIT President Sally Kornbluth. “Lisa is renowned for her intellectual rigor, boldness, and originality, and we're absolutely thrilled that she has agreed to deliver the Commencement address to our graduates this year.”
“MIT has always held a special place in my life and career, and I’m thrilled to accept the invitation to speak at Commencement,” Su says. “The Class of 2026 will be graduating at an exciting time, as AI transforms our world and expands what is possible, and I look forward to celebrating them as they prepare to share their skills and ideas with the world.”
Born in Taiwan, Su grew up in Queens, New York. After earning bachelor’s, master’s, and doctoral degrees in electrical engineering from MIT, she worked at Texas Instruments, IBM, and Freescale Semiconductor, then joined AMD in 2012. In her current position, Su is a member of a small group: Only about 10 percent of Fortune 500 companies have female CEOs.
“Lisa Su has embraced MIT’s ‘mind and hand’ motto over the course of her career, first with important scientific discoveries in semiconductor design and engineering, and later as an extraordinary business executive leading the delivery of innovative products that play an essential role in the modern digital economy. We are very fortunate that she has agreed to share some of the lessons learned on her journey,” says Jim Poterba, the Mitsui Professor of Economics and chair of the Commencement Committee.
“Dr. Lisa Su is an inspiration to the MIT community for the way she combines exceptional engineering and leadership with meaningful, far-reaching impact in computing and countless other fields,” senior class president Heba Hussein says. “Her journey embodies the spirit of MIT, and the Class of 2026 is incredibly excited to welcome her at Commencement as we step into the world carrying the same MIT values!”
“I am excited to hear from someone that I know we can all learn something from. I think all MIT students respect the ‘lock-in’ that must have been required to achieve all that she has, with AMD and beyond,” says Alice Hall, president of the Undergraduate Association.
“Dr. Su is a world leader in manufacturing technologies and personifies MIT's values. As an alum, she has shared many experiences with current students, and I look forward to hearing about how these experiences shaped her successful career,” says Teddy Warner, president of the Graduate Student Council.
Su has received many honors including two named for MIT alumni: the Global Semiconductor Association’s Dr. Morris Chang Exemplary Leadership Award and the Robert N. Noyce Medal. She was named TIME’s 2024 CEO of the Year and has been recognized as one of TIME’s 100 Most Influential People and Fortune's Most Powerful People in Business. She received the 2024 Bower Award for Business Leadership and the Distinguished Leadership Award from the Committee for Economic Development (CED). Su is a member of the American Academy of Arts and Sciences and the National Academy of Engineering.
Su joins notable recent MIT Commencement speakers including science communicator Hank Green (2025); inventor and entrepreneur Noubar Afeyan (2024); YouTuber and inventor Mark Rober (2023); Director-General of the World Trade Organization Ngozi Okonjo-Iweala (2022); lawyer and social justice activist Bryan Stevenson (2021); and retired U.S. Navy four-star admiral William McRaven (2020).
Capturing carbon dioxide from industrial plants is an important strategy in the efforts to reduce the impact of global climate change. It’s used in many industries, including the production of petrochemicals, cement, and fertilizers.
MIT chemical engineers have now discovered a simple way to make carbon capture more efficient and affordable, by adding a common chemical compound to capture solutions. The innovation could cut costs significantly and enable the technology to run on waste heat or even sunlight, instead of energy-intensive heating.
Their new approach uses a chemical called tris — short for tris(hydroxymethyl)aminomethane — to stabilize the pH of the solution used to capture CO2, allowing the system to absorb more of the gas at relatively low temperature. The system can release CO2 at just 60 degrees Celsius (140 degrees Fahrenheit) — a dramatic improvement over conventional methods, which require temperatures exceeding 120 C to release captured carbon.
“It’s something that could be implemented almost immediately in fairly standard types of equipment,” says T. Alan Hatton, the Ralph Landau Professor of Chemical Engineering Practice at MIT and the senior author of the study.
Youhong (Nancy) Guo, a recent MIT postdoc who is now an assistant professor of applied physical sciences at the University of North Carolina at Chapel Hill, is the lead author of the paper, which appears today in Nature Chemical Engineering.
More efficient capture
Using current technologies, around 0.1 percent of global carbon emissions is captured and either stored underground or converted into other products.
The most widely used carbon-capture method involves running waste gases through a solution that contains chemical compounds called amines. These solutions have a high pH, which allows them to absorb CO2, an acidic gas. In addition to traditional amines, basic compounds called carbonates, which are inexpensive and readily available, can also capture acidic CO2 gas. However, as CO2 is absorbed, the pH of the solution drops quickly, limiting the CO2 uptake capacity.
The most energy-intensive step comes once the CO2 is absorbed, because both amine and carbonate solutions must be heated to above 120 C to release the captured carbon. This regeneration step consumes enormous amounts of energy.
To make carbon capture by carbonates more efficient, the MIT team added tris into a potassium carbonate solution. This chemical, commonly used in lab experiments and found in some cosmetics and the Covid-19 mRNA vaccines, acts as a pH buffer — a solution that helps prevent the pH from changing.
When added to a carbonate solution, positively charged tris balances the negative charge of the bicarbonate ions formed when CO2 is absorbed. This stabilizes the pH, allowing the solution to absorb triple the amount of CO2.
As another advantage, tris is highly sensitive to temperature changes. When the solution full of CO2 is heated just slightly, to about 60 C, tris quickly releases protons, causing the pH to drop and the captured CO2 to bubble out.
“At room temperature, the solution can absorb more CO2, and with mild heating it can release the CO2. There is an instant pH change when we heat up the solution a little bit,” Guo says.
“Potassium carbonate is one of the holy grail solvents for carbon capture due to its high chemical stability, low cost, and negligible emissions,” says David Heldebrant, an associate professor of chemical engineering and bioengineering at Washington State University, who was not involved in the study. “I believe this electrochemical tris-promoted potassium carbonate solvent system has a lot of promise for the field of carbon capture, especially since the researchers have been able to improve on the energetics by regenerating at atmospheric pressure, as compared to vacuum-assisted regeneration, which is normally done.”
A simple swap
To demonstrate their approach, the researchers built a continuous-flow reactor for carbon capture. First, gases containing CO2 are bubbled through a reservoir containing carbonate and tris, which absorbs the CO2. That solution then is pumped into a CO2 regeneration module, which is heated to about 60 C to release a pure stream of CO2.
Once the CO2 is released, the carbonate solution is cooled and returned to the reservoir for another round of CO2 absorption and regeneration.
Because the system can operate at relatively low temperatures, there is more flexibility in where the energy could come from, such as solar panels, electricity, or waste heat already generated by industrial plants.
Swapping in carbonate-tris solutions to replace conventional amines should be straightforward for industrial facilities, the researchers say. “One of the nice things about this is its simplicity, in terms of overall design. It’s a drop-in approach that allows you to readily change over from one kind of solution to another,” Hatton says.
When carbon is captured from industrial plants, some of it can be diverted into the manufacture of other useful products, but most of it will likely end up being stored in underground geological formations, Hatton says.
“You can only use a small fraction of the captured CO2 for producing chemicals before you saturate the market,” he says.
Guo is now exploring whether other additives could make the carbon capture process even more efficient by speeding up CO2 absorption rates.
The authors acknowledge Eni S.p.A. for the fruitful discussions under the MIT–Eni research framework agreement.
New materials could boost the energy efficiency of microelectronicsBy stacking multiple active components based on new materials on the back end of a computer chip, this new approach reduces the amount of energy wasted during computation.MIT researchers have developed a new fabrication method that could enable the production of more energy efficient electronics by stacking multiple functional components on top of one existing circuit.
In traditional circuits, logic devices that perform computation, like transistors, and memory devices that store data are built as separate components, forcing data to travel back and forth between them, which wastes energy.
This new electronics integration platform allows scientists to fabricate transistors and memory devices in one compact stack on a semiconductor chip. This eliminates much of that wasted energy while boosting the speed of computation.
Key to this advance is a newly developed material with unique properties and a more precise fabrication approach that reduces the number of defects in the material. This allows the researchers to make extremely tiny transistors with built-in memory that can perform faster than state-of-the-art devices while consuming less electricity than similar transistors.
By improving the energy efficiency of electronic devices, this new approach could help reduce the burgeoning electricity consumption of computation, especially for demanding applications like generative AI, deep learning, and computer vision tasks.
“We have to minimize the amount of energy we use for AI and other data-centric computation in the future because it is simply not sustainable. We will need new technology like this integration platform to continue that progress,” says Yanjie Shao, an MIT postdoc and lead author of two papers on these new transistors.
The new technique is described in two papers (one invited) that were presented at the IEEE International Electron Devices Meeting. Shao is joined on the papers by senior authors Jesús del Alamo, the Donner Professor of Engineering in the MIT Department of Electrical Engineering and Computer Science (EECS); Dimitri Antoniadis, the Ray and Maria Stata Professor of Electrical Engineering and Computer Science at MIT; as well as others at MIT, the University of Waterloo, and Samsung Electronics.
Flipping the problem
Standard CMOS (complementary metal-oxide semiconductor) chips traditionally have a front end, where the active components like transistors and capacitors are fabricated, and a back end that includes wires called interconnects and other metal bonds that connect components of the chip.
But some energy is lost when data travel between these bonds, and slight misalignments can hamper performance. Stacking active components would reduce the distance data must travel and improve a chip’s energy efficiency.
Typically, it is difficult to stack silicon transistors on a CMOS chip because the high temperature required to fabricate additional devices on the front end would destroy the existing transistors underneath.
The MIT researchers turned this problem on its head, developing an integration technique to stack active components on the back end of the chip instead.
“If we can use this back-end platform to put in additional active layers of transistors, not just interconnects, that would make the integration density of the chip much higher and improve its energy efficiency,” Shao explains.
The researchers accomplished this using a new material, amorphous indium oxide, as the active channel layer of their back-end transistor. The active channel layer is where the transistor’s essential functions take place.
Due to the unique properties of indium oxide, they can “grow” an extremely thin layer of this material at a temperature of only about 150 degrees Celsius on the back end of an existing circuit without damaging the device on the front end.
Perfecting the process
They carefully optimized the fabrication process, which minimizes the number of defects in a layer of indium oxide material that is only about 2 nanometers thick.
A few defects, known as oxygen vacancies, are necessary for the transistor to switch on, but with too many defects it won’t work properly. This optimized fabrication process allows the researchers to produce an extremely tiny transistor that operates rapidly and cleanly, eliminating much of the additional energy required to switch a transistor between off and on.
Building on this approach, they also fabricated back-end transistors with integrated memory that are only about 20 nanometers in size. To do this, they added a layer of material called ferroelectric hafnium-zirconium-oxide as the memory component.
These compact memory transistors demonstrated switching speeds of only 10 nanoseconds, hitting the limit of the team’s measurement instruments. This switching also requires much lower voltage than similar devices, reducing electricity consumption.
And because the memory transistors are so tiny, the researchers can use them as a platform to study the fundamental physics of individual units of ferroelectric hafnium-zirconium-oxide.
“If we can better understand the physics, we can use this material for many new applications. The energy it uses is very minimal, and it gives us a lot of flexibility in how we can design devices. It really could open up many new avenues for the future,” Shao says.
The researchers also worked with a team at the University of Waterloo to develop a model of the performance of the back-end transistors, which is an important step before the devices can be integrated into larger circuits and electronic systems.
In the future, they want to build upon these demonstrations by integrating back-end memory transistors onto a single circuit. They also want to enhance the performance of the transistors and study how to more finely control the properties of ferroelectric hafnium-zirconium-oxide.
“Now, we can build a platform of versatile electronics on the back end of a chip that enable us to achieve high energy efficiency and many different functionalities in very small devices. We have a good device architecture and material to work with, but we need to keep innovating to uncover the ultimate performance limits,” Shao says.
This work is supported, in part, by Semiconductor Research Corporation (SRC) and Intel. Fabrication was carried out at the MIT Microsystems Technology Laboratories and MIT.nano facilities.
Vine-inspired robotic gripper gently lifts heavy and fragile objectsThe new design could be adapted to assist the elderly, sort warehouse products, or unload heavy cargo.In the horticultural world, some vines are especially grabby. As they grow, the woody tendrils can wrap around obstacles with enough force to pull down entire fences and trees.
Inspired by vines’ twisty tenacity, engineers at MIT and Stanford University have developed a robotic gripper that can snake around and lift a variety of objects, including a glass vase and a watermelon, offering a gentler approach compared to conventional gripper designs. A larger version of the robo-tendrils can also safely lift a human out of bed.
The new bot consists of a pressurized box, positioned near the target object, from which long, vine-like tubes inflate and grow, like socks being turned inside out. As they extend, the vines twist and coil around the object before continuing back toward the box, where they are automatically clamped in place and mechanically wound back up to gently lift the object in a soft, sling-like grasp.
The researchers demonstrated that the vine robot can safely and stably lift a variety of heavy and fragile objects. The robot can also squeeze through tight quarters and push through clutter to reach and grasp a desired object.
The team envisions that this type of robot gripper could be used in a wide range of scenarios, from agricultural harvesting to loading and unloading heavy cargo. In the near term, the group is exploring applications in eldercare settings, where soft inflatable robotic vines could help to gently lift a person out of bed.
“Transferring a person out of bed is one of the most physically strenuous tasks that a caregiver carries out,” says Kentaro Barhydt, a PhD candidate in MIT’s Department of Mechanical Engineering. “This kind of robot can help relieve the caretaker, and can be gentler and more comfortable for the patient.”
Barhydt, along with his co-first author from Stanford, O. Godson Osele, and their colleagues, present the new robotic design today in the journal Science Advances. The study’s co-authors are Harry Asada, the Ford Professor of Engineering at MIT, and Allison Okamura, the Richard W. Weiland Professor of Engineering at Stanford University, along with Sreela Kodali and Cosmia du Pasquier at Stanford University, and former MIT graduate student Chase Hartquist, now at the University of Florida, Gainesville.
Open and closed
The team’s Stanford collaborators, led by Okamura, pioneered the development of soft, vine-inspired robots that grow outward from their tips. These designs are largely built from thin yet sturdy pneumatic tubes that grow and inflate with controlled air pressure. As they grow, the tubes can twist, bend, and snake their way through the environment, and squeeze through tight and cluttered spaces.
Researchers have mostly explored vine robots for use in safety inspections and search and rescue operations. But at MIT, Barhydt and Asada, whose group has developed robotic aides for the elderly, wondered whether such vine-inspired robots could address certain challenges in eldercare — specifically, the challenge of safely lifting a person out of bed. Often in nursing and rehabilitation settings, this transfer process is done with a patient lift, operated by a caretaker who must first physically move a patient onto their side, then back onto a hammock-like sheet. The caretaker straps the sheet around the patient and hooks it onto the mechanical lift, which then can gently hoist the patient out of bed, similar to suspending a hammock or sling.
The MIT and Stanford team imagined that as an alternative, a vine-like robot could gently snake under and around a patient to create its own sort of sling, without a caretaker having to physically maneuver the patient. But in order to lift the sling, the researchers realized they would have to add an element that was missing in existing vine robot designs: Essentially, they would have to close the loop.
Most vine-inspired robots are designed as “open-loop” systems, meaning they act as open-ended strings that can extend and bend in different configurations, but they are not designed to secure themselves to anything to form a closed loop. If a vine robot could be made to transform from an open loop to a closed loop, Barhydt surmised that it could make itself into a sling around the object and pull itself up, along with whatever, or whomever, it might hold.
For their new study, Barhydt, Osele, and their colleagues outline the design for a new vine-inspired robotic gripper that combines both open- and closed-loop actions. In an open-loop configuration, a robotic vine can grow and twist around an object to create a firm grasp. It can even burrow under a human lying on a bed. Once a grasp is made, the vine can continue to grow back toward and attach to its source, creating a closed loop that can then be retracted to retrieve the object.
“People might assume that in order to grab something, you just reach out and grab it,” Barhydt says. “But there are different stages, such as positioning and holding. By transforming between open and closed loops, we can achieve new levels of performance by leveraging the advantages of both forms for their respective stages.”
Gentle suspension
As a demonstration of their new open- and closed-loop concept, the team built a large-scale robotic system designed to safely lift a person up from a bed. The system comprises a set of pressurized boxes attached on either end of an overhead bar. An air pump inside the boxes slowly inflates and unfurls thin vine-like tubes that extend down toward the head and foot of a bed. The air pressure can be controlled to gently work the tubes under and around a person, before stretching back up to their respective boxes. The vines then thread through a clamping mechanism that secures the vines to each box. A winch winds the vines back up toward the boxes, gently lifting the person up in the process.
“Heavy but fragile objects, such as a human body, are difficult to grasp with the robotic hands that are available today,” Asada says. “We have developed a vine-like, growing robot gripper that can wrap around an object and suspend it gently and securely.”
"There’s an entire design space we hope this work inspires our colleagues to continue to explore,” says co-lead author Osele. “I especially look forward to the implications for patient transfer applications in health care.”
“I am very excited about future work to use robots like these for physically assisting people with mobility challenges,” adds co-author Okamura. “Soft robots can be relatively safe, low-cost, and optimally designed for specific human needs, in contrast to other approaches like humanoid robots.”
While the team’s design was motivated by challenges in eldercare, the researchers realized the new design could also be adapted to perform other grasping tasks. In addition to their large-scale system, they have built a smaller version that can attach to a commercial robotic arm. With this version, the team has shown that the vine robot can grasp and lift a variety of heavy and fragile objects, including a watermelon, a glass vase, a kettle bell, a stack of metal rods, and a playground ball. The vines can also snake through a cluttered bin to pull out a desired object.
“We think this kind of robot design can be adapted to many applications,” Barhydt says. “We are also thinking about applying this to heavy industry, and things like automating the operation of cranes at ports and warehouses.”
This work was supported, in part, by the National Science Foundation and the Ford Foundation.
When it comes to language, context mattersMIT researchers identified three cognitive skills that we use to infer what someone really means.In everyday conversation, it’s critical to understand not just the words that are spoken, but the context in which they are said. If it’s pouring rain and someone remarks on the “lovely weather,” you won’t understand their meaning unless you realize that they’re being sarcastic.
Making inferences about what someone really means when it doesn’t match the literal meaning of their words is a skill known as pragmatic language ability. This includes not only interpreting sarcasm but also understanding metaphors and white lies, among many other conversational subtleties.
“Pragmatics is trying to reason about why somebody might say something, and what is the message they’re trying to convey given that they put it in this particular way,” says Evelina Fedorenko, an MIT associate professor of brain and cognitive sciences and a member of MIT’s McGovern Institute for Brain Research.
New research from Fedorenko and her colleagues has revealed that these abilities can be grouped together based on what types of inferences they require. In a study of 800 people, the researchers identified three clusters of pragmatic skills that are based on the same kinds of inferences and may have similar underlying neural processes.
One of these clusters includes inferences that are based on our knowledge of social conventions and rules. Another depends on knowledge of how the physical world works, while the last requires the ability to interpret differences in tone, which can indicate emphasis or emotion.
Fedorenko and Edward Gibson, an MIT professor of brain and cognitive sciences, are the senior authors of the study, which appears today in the Proceedings of the National Academy of Sciences. The paper’s lead authors are Sammy Floyd, a former MIT postdoc who is now an assistant professor of psychology at Sarah Lawrence College, and Olessia Jouravlev, a former MIT postdoc who is now an associate professor of cognitive science at Carleton University.
The importance of context
Much past research on how people understand language has focused on processing the literal meanings of words and how they fit together. To really understand what someone is saying, however, we need to interpret those meanings based on context.
“Language is about getting meanings across, and that often requires taking into account many different kinds of information — such as the social context, the visual context, or the present topic of the conversation,” Fedorenko says.
As one example, the phrase “people are leaving” can mean different things depending on the context, Gibson points out. If it’s late at night and someone asks you how a party is going, you may say “people are leaving,” to convey that the party is ending and everyone’s going home.
“However, if it’s early, and I say ‘people are leaving,’ then the implication is that the party isn’t very good,” Gibson says. “When you say a sentence, there’s a literal meaning to it, but how you interpret that literal meaning depends on the context.”
About 10 years ago, with support from the Simons Center for the Social Brain at MIT, Fedorenko and Gibson decided to explore whether it might be possible to precisely distinguish the types of processing that go into pragmatic language skills.
One way that neuroscientists can approach a question like this is to use functional magnetic resonance imaging (fMRI) to scan the brains of participants as they perform different tasks. This allows them to link brain activity in different locations to different functions. However, the tasks that the researchers designed for this study didn’t easily lend themselves to being performed in a scanner, so they took an alternative approach.
This approach, known as “individual differences,” involves studying a large number of people as they perform a variety of tasks. This technique allows researchers to determine whether the same underlying brain processes may be responsible for performance on different tasks.
To do this, the researchers evaluate whether each participant tends to perform similarly on certain groups of tasks. For example, some people might perform well on tasks that require an understanding of social conventions, such as interpreting indirect requests and irony. The same people might do only so-so on tasks that require understanding how the physical world works, and poorly on tasks that require distinguishing meanings based on changes in intonation — the melody of speech. This would suggest that separate brain processes are being recruited for each set of tasks.
The first phase of the study was led by Jouravlev, who assembled existing tasks that require pragmatic skills and created many more, for a total of 20. These included tasks that require people to understand humor and sarcasm, as well as tasks where changes in intonation can affect the meaning of a sentence. For example, someone who says “I wanted blue and black socks,” with emphasis on the word “black,” is implying that the black socks were forgotten.
“People really find ways to communicate creatively and indirectly and non-literally, and this battery of tasks captures that,” Floyd says.
Components of pragmatic ability
The researchers recruited study participants from an online crowdsourcing platform to perform the tasks, which took about eight hours to complete. From this first set of 400 participants, the researchers found that the tasks formed three clusters, related to social context, general knowledge of the world, and intonation. To test the robustness of the findings, the researchers continued the study with another set of 400 participants, with this second half run by Floyd after Jouravlev had left MIT.
With the second set of participants, the researchers found that tasks clustered into the same three groups. They also confirmed that differences in general intelligence, or in auditory processing ability (which is important for the processing of intonation), did not affect the outcomes that they observed.
In future work, the researchers hope to use brain imaging to explore whether the pragmatic components they identified are correlated with activity in different brain regions. Previous work has found that brain imaging often mirrors the distinctions identified in individual difference studies, but can also help link the relevant abilities to specific neural systems, such as the core language system or the theory of mind system.
This set of tests could also be used to study people with autism, who sometimes have difficulty understanding certain social cues. Such studies could determine more precisely the nature and extent of these difficulties. Another possibility could be studying people who were raised in different cultures, which may have different norms around speaking directly or indirectly.
“In Russian, which happens to be my native language, people are more direct. So perhaps there might be some differences in how native speakers of Russian process indirect requests compared to speakers of English,” Jouravlev says.
The research was funded by the Simons Center for the Social Brain at MIT, the National Institutes of Health, and the National Science Foundation.
MIT takes manufacturing education across the countryThe new TechAMP program teaches production principles to workers, helping them advance their careers and identify savings at their firms.MIT has long bolstered U.S. manufacturing by developing key innovations and production technologies, and training entrepreneurs. This fall, the Institute introduced a new tool for U.S. manufacturing: an education program for workers, held at collaborating institutions, which teaches core principles of production, helping employees and firms alike.
The new effort, the Technologist Advanced Manufacturing Program, or TechAMP, developed with U.S. Department of Defense funding, features a mix of in-person lab instruction at participating institutions, online lectures by MIT faculty and staff, and interactive simulations. There are also capstone projects, in which employees study manufacturing issues with the aim of saving their firms money.
Ultimately, TechAMP is a 12-month certificate program aimed at making the concept of the accredited “technologist” a vital part of the manufacturing enterprise. That could help workers advance in their careers. And it could help firms develop a more skilled workforce.
“We think there’s a gap between the traditional worker categories of engineer and technician, and this technologist training fills it,” says John Liu, a principal research scientist in MIT’s Department of Mechanical Engineering and principal investigator of the TechAMP program. “We’re very interested in creating new career pathways and allowing the manufacturing workforce to have a different kind of perspective. We want to formalize the path to becoming a technologist.”
Liu, who is also the principal investigator of the MIT Learning Engineering and Practice Group (LEAP), adds that the MIT program “is a pathway to leadership. No longer should a technician just think about one piece of equipment. They can think about the whole system, the whole operation, and help with decision-making.”
TechAMP launched this fall, in collaboration with multiple institutions, including the University of Massachusetts at Lowell, Cape Cod Community College, Ohio State University, the Community College of Rhode Island, the Connecticut Center for Advanced Technology, and the Berkshire Innovation Center in Pittsfield, Massachusetts. More than 70 people are in the initial cohort of students.
“MIT has embraced the idea that we’re reaching this new type of learner,” says Julie Diop, executive director of MIT’s Initiative for New Manufacturing (INM). TechAMP forms a key part of the education arm of that initiative, a campus-wide effort to reinvigorate U.S. manufacturing that was announced in May 2025. INM also collaborates with several industry firms embracing innovative approaches to manufacturing.
“Through TechAMP and other programs, we’re excited to reach beyond MIT’s traditional realm of manufacturing education and collaborate with companies of all sizes alongside our community college partners,” says John Hart, the Class of 1922 Professor of Mechanical Engineering, head of the Department of Mechanical Engineering at MIT, and faculty co-director of INM. “We hope that the program equips manufacturing technologists to be innovators and problem-solvers in their organizations, and to effectively deploy new technologies that can improve manufacturing productivity.”
INM is one of the key Institute-wide initiatives prioritized by MIT President Sally A. Kornbluth.
“Helping America build a future of new manufacturing is a perfect job for MIT,” Kornbluth said at the INM launch event in May. She continued: “I’m convinced that there is no more important work we can do to meet the moment and serve the nation now.”
A “confidence booster” for workers
TechAMP has been supported by two Department of Defense grants enabling the program’s development. MIT scholars collaborated with colleagues at Clemson University and Ohio State University to develop a number of the interactive simulations used in the course.
The course work is based around a “hub-and-spoke” model that includes segments on core principles of manufacturing — that’s the hub — as well as six areas, or spokes, where companies have advised MIT that workers need more training.
The four parts of the hub comprise manufacturing process controls and their statistical analysis; understanding manufacturing systems, including workflow and efficiency; leadership skills; and operations management, from factory analysis to supply chain issues. These are also the core issues studied in MIT’s online micromaster’s certificate in manufacturing.
The six spokes may change or expand over time but currently consist of mechatronics, automation programming, robotics, machining, digital manufacturing, and design and manufacturing fundamentals.
Having the TechAMP curriculum revolve around concepts common to all manufacturing industries helps technologists-in-training better understand how their companies are trying to function and how their own work relates to those principles.
“The hub concepts are what defines manufacturing,” Liu says. “We need to teach this undervalued set of principles to the workforce, including people without university degrees. If we do that, it means they have a timeless set of ideas. We can adapt ourselves to add industries like biomanufacturing, but we’re starting with the fundamentals.”
Students say they are enjoying the program.
“It’s been a confidence booster,” says Nicole Swan, an employee at the manufacturing firm Proterial, who is taking the TechAMP class at the Community College of Rhode Island campus in Westerly, Rhode Island. “This has really shown me so many different opportunities [for] what I could do in the future, and different avenues that are available.”
Direct value capture possible for firms
The TechAMP certificate program also involves a capstone project, in which the students try to analyze issues or challenges within their own firms. Ideally, if those projects lead to savings or add value, that could make it well worthwhile for manufacturing companies to pay for their students to attend the TechAMP program — which is about 10 to 14 hours of work per week, for the year.
“That could be a form of impact — direct value capture for the firm,” Diop says.
Some firms are already pleased with the development of TechAMP.
“There are so many manufacturing jobs that don’t need a four-year degree, but do require a very high skill level and good communications skills,” says Michael Trotta, CEO of Crystal Engineering, a versatile, 45-employee manufacturer in Newburyport, Massachusetts, whose products range from medical devices to aerospace and defense items. “I see TechAMP as a next logical step in developing a sustainable workforce."
Trotta and three of his employees worked with MIT on the TechAMP project last spring, studying the curriculum material and providing feedback about it to the program leaders, in an effort to make the coursework as useful as possible.
"What we want workers to do is progress to a point where they become that technologist making not $20 an hour, but $40 or $50 an hour, because they have that skill set to run a lot more than just one piece of the process,” Trotta explains. “They’re able to communicate effectively with the engineers, with operations, to identify strengths and weaknesses, to help the firm drive success."
And while the position of “technologist” may not yet be in every manufacturer’s vocabulary yet, the MIT program leaders think it makes eminent sense, as a way of further equipping workers who are currently regarded as technicians or machinists.
By analogy, Diop observes, “The role of nurse practitioner bridges the gap between nurse and doctor, and has changed how medicine is delivered.” Manufacturing, she adds, “has had a reputation for dead-end jobs, but if MIT can help break that image by providing a real pathway, I think that would be meaningful, especially for those without university degrees.”
Intriguingly — as shown by research from Ben Armstrong, executive director and a research scientist at MIT’s Industrial Performance Center — about 10 to 15 percent of titled engineers in manufacturing industries do not have engineering degrees, either. For that portion of the workforce as well, more formal training and credentials may prove useful over time.
TechAMP is new, evolving — and likely to be expanding soon. Diop and Liu are in talks with interested education networks in multiple manufacturing-heavy states, to see if they would like to partner with MIT. There is also new interest from more manufacturers, including some of the partners in MIT’s Initiative for New Manufacturing. Given that the initiative just launched in May, TechAMP has hit the ground running.
“There’s been a lot of excitement so far, we think,” Liu says. “And it’s coming from organizations and people who are eager to learn more.”
Pompeii offers insights into ancient Roman building technologyMIT researchers analyzed a recently discovered ancient construction site to shed new light on a material that has endured for thousands of years.Concrete was the foundation of the ancient Roman empire. It enabled Rome’s storied architectural revolution as well as the construction of buildings, bridges, and aqueducts, many of which are still used some 2,000 years after their creation.
In 2023, MIT Associate Professor Admir Masic and his collaborators published a paper describing the manufacturing process that gave Roman concrete its longevity: Lime fragments were mixed with volcanic ash and other dry ingredients before the addition of water. Once water is added to this dry mix, heat is produced. As the concrete sets, this “hot-mixing” process traps and preserves the highly reactive lime as small, white, gravel-like features. When cracks form in the concrete, the lime clasts redissolve and fill the cracks, giving the concrete self-healing properties.
There was only one problem: The process Masic’s team described was different from the one described by the famed ancient Roman architect Vitruvius. Vitruvius literally wrote the book on ancient architecture. His highly influential work, “De architectura,” written in the 1st century B.C.E., is the first known book on architectural theory. In it, Vitruvius says that Romans added water to lime to create a paste-like material before mixing it with other ingredients.
“Having a lot of respect for Vitruvius, it was difficult to suggest that his description may be inaccurate,” Masic says. “The writings of Vitruvius played a critical role in stimulating my interest in ancient Roman architecture, and the results from my research contradicted these important historical texts.”
Now, Masic and his collaborators have confirmed that hot-mixing was indeed used by the Romans, a conclusion he reached by studying a newly discovered ancient construction site in Pompeii that was exquisitely preserved by the volcanic eruption of Mount Vesuvius in the year 79 C.E. They also characterized the volcanic ash material the Romans mixed with the lime, finding a surprisingly diverse array of reactive minerals that further added to the concrete’s ability to repair itself many years after these monumental structures were built.
“There is the historic importance of this material, and then there is the scientific and technological importance of understanding it,” Masic explains. “This material can heal itself over thousands of years, it is reactive, and it is highly dynamic. It has survived earthquakes and volcanoes. It has endured under the sea and survived degradation from the elements. We don’t want to completely copy Roman concrete today. We just want to translate a few sentences from this book of knowledge into our modern construction practices.”
The findings are described today in Nature Communications. Joining Masic on the paper are first authors Ellie Vaserman ’25 and Principal Research Scientist James Weaver, along with Associate Professor Kristin Bergmann, PhD candidate Claire Hayhow, and six other Italian collaborators.
Uncovering ancient secrets
Masic has spent close to a decade studying the chemical composition of the concrete that allowed Rome’s famous structures to endure for so much longer than their modern counterparts. His 2023 paper analyzed the material’s chemical composition to deduce how it was made.
That paper used samples from a city wall in Priverno in southwest Italy, which was conquered by the Romans in the 4th century B.C.E. But there was a question as to whether this wall was representative of other concrete structures built throughout the Roman empire.
The recent discovery by archaeologists of an active ancient construction site in Pompeii (complete with raw material piles and tools) therefore offered an unprecedented opportunity.
For the study, the researchers analyzed samples from these pre-mixed dry material piles, a wall that was in the process of being built, completed buttress and structural walls, and mortar repairs in an existing wall.
“We were blessed to be able to open this time capsule of a construction site and find piles of material ready to be used for the wall,” Masic says. “With this paper, we wanted to clearly define a technology and associate it with the Roman period in the year 79 C.E.”
The site offered the clearest evidence yet that the Romans used hot-mixing in concrete production. Not only did the concrete samples contain the lime clasts described in Masic’s previous paper, but the team also discovered intact quicklime fragments pre-mixed with other ingredients in a dry raw material pile, a critical first step in the preparation of hot-mixed concrete.
Bergman, an associate professor of earth and planetary sciences, helped develop tools for differentiating the materials at the site.
“Through these stable isotope studies, we could follow these critical carbonation reactions over time, allowing us to distinguish hot-mixed lime from the slaked lime originally described by Vitruvius,” Masic says. “These results revealed that the Romans prepared their binding material by taking calcined limestone (quicklime), grinding them to a certain size, mixing it dry with volcanic ash, and then eventually adding water to create a cementing matrix.”
The researchers also analyzed the volcanic ingredients in the cement, including a type of volcanic ash called pumice. They found that the pumice particles chemically reacted with the surrounding pore solution over time, creating new mineral deposits that further strengthened the concrete.
Rewriting history
Masic says the archaeologists listed as co-authors on the paper were indispensable to the study. When Masic first entered the Pompeii site, as he inspected the perfectly preserved work area, tears came to his eyes.
“I expected to see Roman workers walking between the piles with their tools,” Masic says. “It was so vivid, you felt like you were transported in time. So yes, I got emotional looking at a pile of dirt. The archaeologists made some jokes.”
Masic notes that calcium is a key component in both ancient and modern concretes, so understanding how it reacts over time holds lessons for understanding dynamic processes in modern cement as well. Towards these efforts, Masic has also started a company, DMAT, that uses lessons from ancient Roman concrete to create long-lasting modern concretes.
“This is relevant because Roman cement is durable, it heals itself, and it’s a dynamic system,” Masic says. “The way these pores in volcanic ingredients can be filled through recrystallization is a dream process we want to translate into our modern materials. We want materials that regenerate themselves.”
As for Vitruvius, Masic guesses that he may have been misinterpreted. He points out that Vitruvius also mentions latent heat during the cement mixing process, which could suggest hot-mixing after all.
The work was supported, in part, by the MIT Research Support Commmittee (RSC) and the MIT Concrete Sustainability Hub.
Prognostic tool could help clinicians identify high-risk cancer patientsUsing a versatile problem-solving framework, researchers show how early relapse in lymphoma patients influences their chance for survival.Aggressive T-cell lymphoma is a rare and devastating form of blood cancer with a very low five-year survival rate. Patients often relapse after receiving initial therapy, making it especially challenging for clinicians to keep this destructive disease in check.
In a new study, researchers from MIT, in collaboration with researchers involved in the PETAL consortium at Massachusetts General Hospital, identified a practical and powerful prognostic marker that could help clinicians identify high-risk patients early, and potentially tailor treatment strategies to improve survival.
The team found that, when patients relapse within 12 months of initial therapy, their chances of survival decline dramatically. For these patients, targeted therapies might improve their chances for survival, compared to traditional chemotherapy, the researchers say.
According to their analysis, which used data collected from thousands of patients all over the world, the finding holds true across patient subgroups, regardless of the patient’s initial therapy or their score in a commonly used prognostic index.
A causal inference framework called Synthetic Survival Controls (SSC), developed as part of MIT graduate student Jessy (Xinyi) Han’s thesis, was central to this analysis. This versatile framework helps to answer “when-if” questions — to estimate how the timing of outcomes would shift under different interventions — while overcoming the limitations of inconsistent and biased data.
The identification of novel risk groups could guide clinicians as they select therapies to improve overall survival. For instance, a clinician might prioritize early-phase clinical trials over canonical therapies for this cohort of patients. The results could inform inclusion criteria for some clinical trials, according to the researchers.
The causal inference framework for survival analysis can also be applied more broadly. For instance, the MIT researchers have used it in areas like criminal justice to study how structural factors drive recidivism.
“Often we don’t only care about what will happen, but when the target event will happen. These when-if problems have remained under the radar for a long time, but they are common in a lot of domains. We’ve shown here that, to answer these questions with data, you need domain experts to provide insight and good causal inference methods to close the loop,” says Devavrat Shah, the Andrew and Erna Viterbi Professor in Electrical Engineering and Computer Science at MIT, a member of Institute for Data, Systems and Society (IDSS) and of the Laboratory for Information and Decision Systems (LIDS), and co-author of the study.
Shah is joined on the paper by many co-authors, including Han, who is co-advised by Shah and Fotini Christia, the Ford International Professor of the Social Sciences in the Department of Political Science and director of IDSS; and corresponding authors Mark N. Sorial, a clinical pharmacist and investigator at the Dana-Farber Cancer Institute, and Salvia Jain, a clinician-investigator at the Massachusetts General Hospital Cancer Center, founder of the global PETAL consortium, and an assistant professor of medicine at Harvard Medical School. The research appears today in the journal Blood.
Estimating outcomes
The MIT researchers have spent the past few years developing the Synthetic Survival Control causal inference framework, which enables them to answer complex “when-if” questions when using available data is statistically challenging. Their approach estimates when a target event happens if a certain intervention is used.
In this paper, the researchers investigated an aggressive cancer called nodal mature T-cell lymphoma, and whether a certain prognostic marker led to worse outcomes. The marker, TTR12, signifies that a patient relapsed within 12 months of initial therapy.
They applied their framework to estimate when a patient will die if they have TTR12, and how their survival trajectory would be different if they do not have this prognostic marker.
“No experiment can answer that question because we are asking about two outcomes for the same patient. We have to borrow information from other patients to estimate, counterfactually, what a patient’s survival outcome would have been,” Han explains.
Answering these types of questions is notoriously difficult due to biases in the available observational data. Plus, patient data gathered from an international cohort bring their own unique challenges. For instance, a clinical dataset often contains some historical data about a patient, but at some point the patient may stop treatment, leading to incomplete records.
In addition, if a patient receives a specific treatment, that might impact how long they will survive, adding to the complexity of the data. Plus, for each patient, the researchers only observe one outcome on how long the patient survives — limiting the amount of data available.
Such issues lead to suboptimal performance of many classical methods.
The Synthetic Survival Control framework can overcome these challenges. Even though the researchers don’t know all the details for each patient, their method stitches information from multiple other patients together in such a way that it can estimate survival outcomes.
Importantly, their method is robust to specific modeling assumptions, making it broadly applicable in practice.
The power of prognostication
The researchers’ analysis revealed that TTR12 patients consistently had much greater risk of death within five years of initial therapy than patients without the marker. This was true no matter the initial therapy the patients received or which subgroup they fell into.
“This tells us that early relapse is a very important prognosis. This acts as a signal to clinicians so they can think about tailored therapies for these patients that can overcome resistance in second-line or third-line,” Han says.
Moving forward, the researchers are looking to expand this analysis to include high-dimensional genomics data. This information could be used to develop bespoke treatments that can avoid relapse within 12 months.
“Based on our work, there is already a risk calculation tool being used by clinicians. With more information, we can make it a richer tool that can provide more prognostic details,” Shah says.
They are also applying the framework to other domains.
For instance, in a paper recently presented at the Conference on Neural Information Processing Systems, the researchers identified a dramatic difference in the recidivism rate among prisoners of different races that begins about seven months after release. A possible explanation is the different access to long-term support by different racial groups. They are also investigating individuals’ decisions to leave insurance companies, while exploring other domains where the framework could generate actionable insights.
“Partnering with domain experts is crucial because we want to demonstrate that our methods are of value in the real world. We hope these tools can be used to positively impact individuals across society,” Han says.
This work was funded, in part, by Daiichi Sankyo, Secure Bio, Inc., Acrotech Biopharma, Kyowa Kirin, the Center for Lymphoma Research, the National Cancer Institute, Massachusetts General Hospital, the Reid Fund for Lymphoma Research, the American Cancer Society, and the Scarlet Foundation.
NIH Director Jay Bhattacharya visits MITIn a conversation with Rep. Jake Auchincloss, Bhattacharya focused on the agency’s policy goals and funding practices.National Institutes of Health (NIH) Director Jay Bhattacharya visited MIT on Friday, engaging in a wide-ranging discussion about policy issues and research aims at an event also featuring Rep. Jake Auchincloss MBA ’16 of Massachusetts.
The forum consisted of a dialogue between Auchincloss and Bhattacharya, followed by a question-and-answer session with an audience that included researchers from the greater Boston area. The event was part of a daylong series of stops Bhattacharya and Auchincloss made around Boston, a world-leading hub of biomedical research.
“I was joking with Dr. Bhattacharya that when the NIH director comes to Massachusetts, he gets treated like a celebrity, because we do science, and we take science very seriously here,” Auchincloss quipped at the outset.
Bhattacharya said he was “delighted” to be visiting, and credited the thousands of scientists who participate in peer review for the NIH. “The reason why the NIH succeeds is the willingness and engagement of the scientific community,” he said.
In response to an audience question, Bhattacharya also outlined his overall vision of the NIH’s portfolio of projects.
“You both need investments in ideas that are not tested, just to see if something works. You don’t know in advance,” he said. “And at the same time, you need an ecosystem that tests those ideas rigorously and winnows those ideas to the ones that actually work, that are replicable. A successful portfolio will have both elements in it.”
MIT President Sally A. Kornbluth gave opening remarks at the event, welcoming Bhattacharya and Auchincloss to campus and noting that the Institute’s earliest known NIH grant on record dates to 1948. In recent decades, biomedical research at MIT has boomed, expanding across a wide range of frontier fields.
Indeed, Kornbluth noted, MIT’s federally funded research projects during U.S. President Trump’s first term include a method for making anesthesia safer, especially for children and the elderly; a new type of expanding heart valve for children that eliminates the need for repeated surgeries; and a noninvasive Alzheimer’s treatment using sound and light stimulation, which is currently in clinical trials.
“Today, researchers across our campus pursue pioneering science on behalf of the American people, with profoundly important results,” Kornbluth said.
“The hospitals, universities, startups, investors, and companies represented here today have made greater Boston an extraordinary magnet for talent,” Kornbluth added. “Both as a force for progress in human health and an engine of economic growth, this community of talent is a precious national asset. We look forward to working with Dr. Bhattacharya to build on its strengths.”
The discussion occurred amid uncertainty about future science funding levels and pending changes in the NIH’s grant-review processes. The NIH has announced a “unified strategy” for reviewing grant applications that may lead to more direct involvement in grant decisions by directors of the 27 NIH institutes and centers, along with other changes that could shift the types of awards being made.
Auchincloss asked multiple questions about the ongoing NIH changes; about 10 audience members from a variety of institutions also posed a range of questions to Bhattacharya, often about the new grant-review process and the aims of the changes.
“The unified funding strategy is a way to allow institute direcors to look at the full range of scoring, including scores on innovation, and pick projects that look like they are promising,” Bhattacharya said in response to one of Auchincloss’ queries.
One audience member also emphasized concerns about the long-term effects of funding uncertainties on younger scientists in the U.S.
“The future success of the American biomedical enterprise depends on us training the next generation of scientists,” Bhattacharya acknowledged.
Bhattacharya is the 18th director of the NIH, having been confirmed by the U.S. Senate in March. He has served as a faculty member at Stanford University, where he received his BA, MA, MD, and PhD, and is currently a professor emeritus. During his career, Bhattacharya’s work has often examined the economics of health care, though his research has ranged broadly across topics, in over 170 published papers. He has also served as director of the Center on the Demography and Economics of Health and Aging at Stanford University.
Auchincloss is in his third term as the U.S. Representative to Congress from the 4th district in Massachusetts, having first been elected in 2020. He is also a major in the Marine Corps Reserve, and received his MBA from the MIT Sloan School of Management.
Ian Waitz, MIT’s vice president for research, concluded the session with a note of thanks to Auchincloss and Bhattacharya for their “visit to the greater Boston ecosystem which has done so much for so many and contributed obviously to the NIH mission that you articulated.” He added: “We have such a marvelous history in this region in making such great gains for health and longevity, and we’re here to do more to partner with you.”
When companies “go green,” air quality impacts can vary dramaticallyCutting air travel and purchasing renewable energy can lead to different effects on overall air quality, even while achieving the same CO2 reduction, new research shows.Many organizations are taking actions to shrink their carbon footprint, such as purchasing electricity from renewable sources or reducing air travel.
Both actions would cut greenhouse gas emissions, but which offers greater societal benefits?
In a first step toward answering that question, MIT researchers found that even if each activity reduces the same amount of carbon dioxide emissions, the broader air quality impacts can be quite different.
They used a multifaceted modeling approach to quantify the air quality impacts of each activity, using data from three organizations. Their results indicate that air travel causes about three times more damage to air quality than comparable electricity purchases.
Exposure to major air pollutants, including ground-level ozone and fine particulate matter, can lead to cardiovascular and respiratory disease, and even premature death.
In addition, air quality impacts can vary dramatically across different regions. The study shows that air quality effects differ sharply across space because each decarbonization action influences pollution at a different scale. For example, for organizations in the northeast U.S., the air quality impacts of energy use affect the region, but the impacts of air travel are felt globally. This is because associated pollutants are emitted at higher altitudes.
Ultimately, the researchers hope this work highlights how organizations can prioritize climate actions to provide the greatest near-term benefits to people’s health.
“If we are trying to get to net zero emissions, that trajectory could have very different implications for a lot of other things we care about, like air quality and health impacts. Here we’ve shown that, for the same net zero goal, you can have even more societal benefits if you figure out a smart way to structure your reductions,” says Noelle Selin, a professor in the MIT Institute for Data, Systems, and Society (IDSS) and the Department of Earth, Atmospheric and Planetary Sciences (EAPS); director of the Center for Sustainability Science and Strategy; and senior author of the study.
Selin is joined on the paper by lead author Yuang (Albert) Chen, an MIT graduate student; Florian Allroggen, a research scientist in the MIT Department of Aeronautics and Astronautics; Sebastian D. Eastham, an associate professor in the Department of Aeronautics at Imperial College of London; Evan Gibney, an MIT graduate student; and William Clark, the Harvey Brooks Research Professor of International Science at Harvard University. The research was published Friday in Environmental Research Letters.
A quantification quandary
Climate scientists often focus on the air quality benefits of national or regional policies because the aggregate impacts are more straightforward to model.
Organizations’ efforts to “go green” are much harder to quantify because they exist within larger societal systems and are impacted by these national policies.
To tackle this challenging problem, the MIT researchers used data from two universities and one company in the greater Boston area. They studied whether organizational actions that remove the same amount of CO2 from the atmosphere would have an equivalent benefit on improving air quality.
“From a climate standpoint, CO2 has a global impact because it mixes through the atmosphere, no matter where it is emitted. But air quality impacts are driven by co-pollutants that act locally, so where those emissions occur really matters,” Chen says.
For instance, burning fossil fuels leads to emissions of nitrogen oxides and sulfur dioxide along with CO2. These co-pollutants react with chemicals in the atmosphere to form fine particulate matter and ground-level ozone, which is a primary component of smog.
Different fossil fuels cause varying amounts of co-pollutant emissions. In addition, local factors like weather and existing emissions affect the formation of smog and fine particulate matter. The impacts of these pollutants also depend on the local population distribution and overall health.
“You can’t just assume that all CO2-reduction strategies will have equivalent near-term impacts on sustainability. You have to consider all the other emissions that go along with that CO2,” Selin says.
The researchers used a systems-level approach that involved connecting multiple models. They fed the organizational energy consumption and flight data into this systems-level model to examine local and regional air quality impacts.
Their approach incorporated many interconnected elements, such as power plant emissions data, statistical linkages between air quality and mortality outcomes, and aviation emissions associated with specific flight routes. They fed those data into an atmospheric chemistry transport model to calculate air quality and climate impacts for each activity.
The sheer breadth of the system created many challenges.
“We had to do multiple sensitivity analyses to make sure the overall pipeline was working,” Chen says.
Analyzing air quality
At the end, the researchers monetized air quality impacts to compare them with the climate impacts in a consistent way. Monetized climate impacts of CO2 emissions based on prior literature are about $170 per ton (expressed in 2015 dollars), representing the financial cost of damages caused by climate change.
Using the same method as used to monetize the impact of CO2, the researchers calculated that air quality damages associated with electricity purchases are an additional $88 per ton of CO2, while the damages from air travel are an additional $265 per ton.
This highlights how the air quality impacts of a ton of emitted CO2 depend strongly on where and how the emissions are produced.
“A real surprise was how much aviation impacted places that were really far from these organizations. Not only were flights more damaging, but the pattern of damage, in terms of who is harmed by air pollution from that activity, is very different than who is harmed by energy systems,” Selin says.
Most airplane emissions occur at high altitudes, where differences in atmospheric chemistry and transport can amplify their air quality impacts. These emissions are also carried across continents by atmospheric winds, affecting people thousands of miles from their source.
Nations like India and China face outsized air quality impacts from such emissions due to the higher level of existing ground-level emissions, which exacerbates the formation of fine particulate matter and smog.
The researchers also conducted a deeper analysis of short-haul flights. Their results showed that regional flights have a relatively larger impact on local air quality than longer domestic flights.
“If an organization is thinking about how to benefit the neighborhoods in their backyard, then reducing short-haul flights could be a strategy with real benefits,” Selin says.
Even in electricity purchases, the researchers found that location matters.
For instance, fine particulate matter emissions from power plants caused by one university are in a densely populated region, while emissions caused by the corporation fall over less populated areas.
Due to these population differences, the university’s emissions resulted in 16 percent more estimated premature deaths than those of the corporation, even though the climate impacts are identical.
“These results show that, if organizations want to achieve net zero emissions while promoting sustainability, which unit of CO2 gets removed first really matters a lot,” Chen says.
In the future, the researchers want to quantify the air quality and climate impacts of train travel, to see whether replacing short-haul flights with train trips could provide benefits.
They also want to explore the air quality impacts of other energy sources in the U.S., such as data centers.
This research was funded, in part, by Biogen, Inc., the Italian Ministry for Environment, Land, and Sea, and the MIT Center for Sustainability Science and Strategy.
Paula Hammond named dean of the School of EngineeringA chemical engineer who now serves as executive vice provost, Hammond will succeed Anantha Chandrakasan.Paula Hammond ’84, PhD ’93, an Institute Professor and MIT’s executive vice provost, has been named dean of MIT’s School of Engineering, effective Jan. 16. She will succeed Anantha Chandrakasan, the Vannevar Bush Professor of Electrical Engineering and Computer Science, who was appointed MIT’s provost in July.
Hammond, who was head of the Department of Chemical Engineering from 2015 to 2023, has also served as MIT’s vice provost for faculty. She will be the first woman to hold the role of dean of MIT’s School of Engineering.
“From the rigor and creativity of her scientific work to her outstanding record of service to the Institute, Paula Hammond represents the very best of MIT,” says MIT President Sally Kornbluth. “Wise, thoughtful, down-to-earth, deeply curious, and steeped in MIT’s culture and values, Paula will be a highly effective leader for the School of Engineering. I’m delighted she accepted this new challenge.”
Hammond, who is also a member of MIT’s Koch Institute for Integrative Cancer Research, has earned many accolades for her work developing polymers and nanomaterials that can be used for applications including drug delivery, regenerative medicine, noninvasive imaging, and battery technology.
Chandrakasan announced Hammond’s appointment today in an email to the MIT community, writing, “Ever since enrolling at MIT as an undergraduate, Paula has built a remarkable record of accomplishment in scholarship, teaching, and service. Faculty, staff, and students across the Institute praise her wisdom, selflessness, and kindness, especially when it comes to enabling others’ professional growth and success.”
“Paula is a scholar of extraordinary distinction. It is hard to overstate the value of the broad contributions she has made in her field, which have significantly expanded the frontiers of knowledge,” Chandrakasan told MIT News. “Any one of her many achievements could stand as the cornerstone of an outstanding academic career. In addition, her investment in mentoring the next generation of scholars and building community is unparalleled.”
Chandrakasan also thanked Professor Maria Yang, who has served as the school’s interim dean in recent months. “In a testament to her own longstanding contributions to the School of Engineering, Maria took on the deanship even while maintaining leadership roles with the Ideation Lab, D-Lab, and Morningside Academy for Design. For her excellent service and leadership, Maria deserves our deep appreciation,” he wrote to the community.
Building a sense of community
Throughout her career at MIT, Hammond has helped to create a supportive environment in which faculty and students can do their best work. As vice provost for faculty, a role Hammond assumed in 2023, she developed and oversaw new efforts to improve faculty recruitment and retention, mentoring, and professional development. Earlier this year, she took on additional responsibilities as executive vice provost, providing guidance and oversight for a number of Institute-wide initiatives.
As head of the Department of Chemical Engineering, Hammond worked to strengthen the department’s sense of community and initiated a strategic planning process that led to more collaborative research between faculty members. Under her leadership, the department also launched a major review of its undergraduate curriculum and introduced more flexibility into the requirements for a chemical engineering degree.
Another major priority was ensuring that faculty had the support they needed to pursue new research goals. To help achieve that, she established and raised funds for a series of Faculty Research Innovation Fund grants for mid-career faculty who wanted to explore fresh directions.
“I really enjoyed enabling faculty to explore new areas, finding ways to resource them, making sure that they had the right mentoring early in their career and the ‘wind beneath their wings’ that they needed to get where they wanted to go,” she says. “That, to me, was extremely fulfilling.”
Before taking on her official administrative roles, Hammond served the Institute through her work chairing committees that contributed landmark reports on gender and race at MIT: the Initiative for Faculty Race and Diversity and the Academic and Organizational Relationships Working Group.
In her new role as dean, Hammond plans to begin by consulting with faculty across the School of Engineering to learn more about their needs.
“I like to start with conversations,” she says. “I’m very excited about the idea of visiting each of the departments, finding out what’s on the minds of the faculty, and figuring out how we can meaningfully address their needs and continue to build and grow an excellent engineering program.”
One of her goals is to promote greater cross-disciplinarity in MIT’s curriculum, in part by encouraging and providing resources for faculty to develop more courses that bridge multiple departments.
“There are some barriers that exist between departments, because we all need to teach our core requirements,” she says. “I am very interested in collaborating with departments to think about how we can lower barriers to allow faculty to co-teach, or to perhaps look at different course structures that allow us to teach a core component and then have it branch to a more specialized component.”
She also hopes to guide MIT’s engineering departments in finding ways to incorporate artificial intelligence into their curriculum, and to give students greater opportunity for relevant hands-on experiences in engineering.
“I am particularly excited to build from the strong cross-disciplinary efforts and the key strategic initiatives that Anantha launched during his time as dean,” Hammond says. “I believe we have incredible opportunities to build off these critical areas at the interfaces of science, engineering, the humanities, arts, design, and policy, and to create new emergent fields. MIT should be the leader in providing educational foundations that prepare our students for a highly interdisciplinary and AI-enabled world, and a setting that enables our researchers and scholars to solve the most difficult and urgent problems of the world.”
A pioneer in nanotechnology
Hammond grew up in Detroit, where her father was a PhD biochemist who ran the health laboratories for the city of Detroit. Her mother founded a nursing school at Wayne County Community College, and both parents encouraged her interest in science. As an undergraduate at MIT, she majored in chemical engineering with a focus on polymer chemistry.
After graduating in 1984, Hammond spent two years working as a process engineer at Motorola, then earned a master’s degree in chemical engineering from Georgia Tech. She realized that she wanted to pursue a career in academia, and returned to MIT to earn a PhD in polymer science technology. After finishing her degree in 1993, she spent a year and a half as a postdoc at Harvard University before joining the MIT faculty in 1995.
She became a full professor in 2006, and in 2021, she was named an Institute Professor, the highest honor bestowed by MIT. In 2010, Hammond joined MIT’s Koch Institute for Integrative Cancer Research, where she leads a lab that is developing novel nanomaterials a variety of applications, with a primary focus on treatments and diagnostics for ovarian cancer.
Early in her career, Hammond developed a technique for generating functional thin-film materials by stacking layers of charged polymeric materials. This approach can be used to build polymers with highly controlled architectures by alternately exposing a surface to positively and negatively charged particles.
She has used this layer-by-layer assembly technique to build ultrathin batteries, fuel cell electrodes, and drug delivery nanoparticles that can be specifically targeted to cancer cells. These particles can be tailored to carry chemotherapy drugs such as cisplatin, immunotherapy agents, or nucleic acids such as messenger RNA.
In recognition of her pioneering research, Hammond was awarded the 2024 National Medal of Technology and Innovation. She was also the 2023-24 recipient of MIT’s Killian Award, which honors extraordinary professional achievements by an MIT faculty member. Her many other awards include the Benjamin Franklin Medal in Chemistry in 2024, the ACS Award in Polymer Science in 2018, the American Institute of Chemical Engineers Charles M. A. Stine Award in Materials Engineering and Science in 2013, and the Ovarian Cancer Research Program Teal Innovator Award in 2013.
Hammond has also been honored for her dedication to teaching and mentoring. As a reflection of her excellence in those areas, she was awarded the Irwin Sizer Award for Significant Improvements to MIT Education, the Henry Hill Lecturer Award in 2002, and the Junior Bose Faculty Award in 2000. She also co-chaired the recent Ad Hoc Committee on Faculty Advising and Mentoring, and has been selected as a “Committed to Caring” honoree for her work mentoring students and postdocs in her research group.
Hammond has served on the President’s Council of Advisors on Science and Technology, as well as the U.S. Secretary of Energy Scientific Advisory Board, the NIH Center for Scientific Review Advisory Council, and the Board of Directors of the American Institute of Chemical Engineers. Additionally, she is one of a small group of scientists who have been elected to the National Academies of Engineering, Sciences, and Medicine.
MIT goes quantumInstitute to launch new quantum initiative aimed at advancing the most significant practical applications in science, technology, industry and national security.Everyone is talking about new quantum technologies, but what exactly is quantum and why are scientists, engineers and technologists so excited by the potential for this new field? On Monday, December 8, MIT will launch the MIT Quantum Initiative (or QMIT), an Institute-wide effort to apply quantum breakthroughs to the most consequential challenges in science, technology, industry, and national security.
The interdisciplinary endeavor, the newest of MIT President Sally Kornbluth’s strategic initiatives, will bring together MIT researchers and domain experts from a range of industries to identify and tackle practical challenges wherever quantum solutions could achieve the greatest impact. In collaboration with MIT Lincoln Laboratory, industry leaders and end users from all domains, researchers from across the traditional quantum disciplines will work to identify and advance the most significant practical applications in science, technology, industry and national security.
The QMIT launch event will feature:
More information on QMIT can be found here and the full agenda can be found here.
Robots that spare warehouse workers the heavy liftingFounded by MIT alumni, the Pickle Robot Company has developed machines that can autonomously load and unload trucks inside warehouses and logistic centers.There are some jobs human bodies just weren’t meant to do. Unloading trucks and shipping containers is a repetitive, grueling task — and a big reason warehouse injury rates are more than twice the national average.
The Pickle Robot Company wants its machines to do the heavy lifting. The company’s one-armed robots autonomously unload trailers, picking up boxes weighing up to 50 pounds and placing them onto onboard conveyor belts for warehouses of all types.
The company name, an homage to The Apple Computer Company, hints at the ambitions of founders AJ Meyer ’09, Ariana Eisenstein ’15, SM ’16, and Dan Paluska ’97, SM ’00. The founders want to make the company the technology leader for supply chain automation.
The company’s unloading robots combine generative AI and machine-learning algorithms with sensors, cameras, and machine-vision software to navigate new environments on day one and improve performance over time. Much of the company’s hardware is adapted from industrial partners. You may recognize the arm, for instance, from car manufacturing lines — though you may not have seen it in bright pickle-green.
The company is already working with customers like UPS, Ryobi Tools, and Yusen Logistics to take a load off warehouse workers, freeing them to solve other supply chain bottlenecks in the process.
“Humans are really good edge-case problem solvers, and robots are not,” Paluska says. “How can the robot, which is really good at the brute force, repetitive tasks, interact with humans to solve more problems? Human bodies and minds are so adaptable, the way we sense and respond to the environment is so adaptable, and robots aren’t going to replace that anytime soon. But there’s so much drudgery we can get rid of.”
Finding problems for robots
Meyer and Eisenstein majored in computer science and electrical engineering at MIT, but they didn’t work together until after graduation, when Meyer started the technology consultancy Leaf Labs, which specializes in building embedded computer systems for things like robots, cars, and satellites.
“A bunch of friends from MIT ran that shop,” Meyer recalls, noting it’s still running today. “Ari worked there, Dan consulted there, and we worked on some big projects. We were the primary software and digital design team behind Project Ara, a smartphone for Google, and we worked on a bunch of interesting government projects. It was really a lifestyle company for MIT kids. But 10 years go by, and we thought, ‘We didn’t get into this to do consulting. We got into this to do robots.’”
When Meyer graduated in 2009, problems like robot dexterity seemed insurmountable. By 2018, the rise of algorithmic approaches like neural networks had brought huge advances to robotic manipulation and navigation.
To figure out what problem to solve with robots, the founders talked to people in industries as diverse as agriculture, food prep, and hospitality. At some point, they started visiting logistics warehouses, bringing a stopwatch to see how long it took workers to complete different tasks.
“In 2018, we went to a UPS warehouse and watched 15 guys unloading trucks during a winter night shift,” Meyer recalls. “We spoke to everyone, and not a single person had worked there for more than 90 days. We asked, ‘Why not?’ They laughed at us. They said, ‘Have you tried to do this job before?’”
It turns out warehouse turnover is one of the industry’s biggest problems, limiting productivity as managers constantly grapple with hiring, onboarding, and training.
The founders raised a seed funding round and built robots that could sort boxes because it was an easier problem that allowed them to work with technology like grippers and barcode scanners. Their robots eventually worked, but the company wasn’t growing fast enough to be profitable. Worse yet, the founders were having trouble raising money.
“We were desperately low on funds,” Meyer recalls. “So we thought, ‘Why spend our last dollar on a warm-up task?’”
With money dwindling, the founders built a proof-of-concept robot that could unload trucks reliably for about 20 seconds at a time and posted a video of it on YouTube. Hundreds of potential customers reached out. The interest was enough to get investors back on board to keep the company alive.
The company piloted its first unloading system for a year with a customer in the desert of California, sparing human workers from unloading shipping containers that can reach temperatures up to 130 degrees in the summer. It has since scaled deployments with multiple customers and gained traction among third-party logistics centers across the U.S.
The company’s robotic arm is made by the German industrial robotics giant KUKA. The robots are mounted on a custom mobile base with an onboard computing systems so they can navigate to docks and adjust their positions inside trailers autonomously while lifting. The end of each arm features a suction gripper that clings to packages and moves them to the onboard conveyor belt.
The company’s robots can pick up boxes ranging in size from 5-inch cubes to 24-by-30 inch boxes. The robots can unload anywhere from 400 to 1,500 cases per hour depending on size and weight. The company fine tunes pre-trained generative AI models and uses a number of smaller models to ensure the robot runs smoothly in every setting.
The company is also developing a software platform it can integrate with third-party hardware, from humanoid robots to autonomous forklifts.
“Our immediate product roadmap is load and unload,” Meyer says. “But we’re also hoping to connect these third-party platforms. Other companies are also trying to connect robots. What does it mean for the robot unloading a truck to talk to the robot palletizing, or for the forklift to talk to the inventory drone? Can they do the job faster? I think there’s a big network coming in which we need to orchestrate the robots and the automation across the entire supply chain, from the mines to the factories to your front door.”
“Why not us?”
The Pickle Robot Company employs about 130 people in its office in Charlestown, Massachusetts, where a standard — if green — office gives way to a warehouse where its robots can be seen loading boxes onto conveyor belts alongside human workers and manufacturing lines.
This summer, Pickle will be ramping up production of a new version of its system, with further plans to begin designing a two-armed robot sometime after that.
“My supervisor at Leaf Labs once told me ‘No one knows what they’re doing, so why not us?’” Eisenstein says. “I carry that with me all the time. I’ve been very lucky to be able to work with so many talented, experienced people in my career. They all bring their own skill sets and understanding. That’s a massive opportunity — and it’s the only way something as hard as what we’re doing is going to work.”
Moving forward, the company sees many other robot-shaped problems for its machines.
“We didn’t start out by saying, ‘Let’s load and unload a truck,’” Meyers says. “We said, ‘What does it take to make a great robot business?’ Unloading trucks is the first chapter. Now we’ve built a platform to make the next robot that helps with more jobs, starting in logistics but then ultimately in manufacturing, retail, and hopefully the entire supply chain.”
What’s the best way to expand the US electricity grid?A study by MIT researchers illuminates choices about reliability, cost, and emissions.Growing energy demand means the U.S. will almost certainly have to expand its electricity grid in coming years. What’s the best way to do this? A new study by MIT researchers examines legislation introduced in Congress and identifies relative tradeoffs involving reliability, cost, and emissions, depending on the proposed approach.
The researchers evaluated two policy approaches to expanding the U.S. electricity grid: One would concentrate on regions with more renewable energy sources, and the other would create more interconnections across the country. For instance, some of the best untapped wind-power resources in the U.S. lie in the center of the country, so one type of grid expansion would situate relatively more grid infrastructure in those regions. Alternatively, the other scenario involves building more infrastructure everywhere in roughly equal measure, which the researchers call the “prescriptive” approach. How does each pencil out?
After extensive modeling, the researchers found that a grid expansion could make improvements on all fronts, with each approach offering different advantages. A more geographically unbalanced grid buildout would be 1.13 percent less expensive, and would reduce carbon emissions by 3.65 percent compared to the prescriptive approach. And yet, the prescriptive approach, with more national interconnection, would significantly reduce power outages due to extreme weather, among other things.
“There’s a tradeoff between the two things that are most on policymakers’ minds: cost and reliability,” says Christopher Knittel, an economist at the MIT Sloan School of Management, who helped direct the research. “This study makes it more clear that the more prescriptive approach ends up being better in the face of extreme weather and outages.”
The paper, “Implications of Policy-Driven Transmission Expansion on Costs, Emissions and Reliability in the United States,” is published today in Nature Energy.
The authors are Juan Ramon L. Senga, a postdoc in the MIT Center for Energy and Environmental Policy Research; Audun Botterud, a principal research scientist in the MIT Laboratory for Information and Decision Systems; John E. Parson, the deputy director for research at MIT’s Center for Energy and Environmental Policy Research; Drew Story, the managing director at MIT’s Policy Lab; and Knittel, who is the George P. Schultz Professor at MIT Sloan, and associate dean for climate and sustainability at MIT.
The new study is a product of the MIT Climate Policy Center, housed within MIT Sloan and committed to bipartisan research on energy issues. The center is also part of the Climate Project at MIT, founded in 2024 as a high-level Institute effort to develop practical climate solutions.
In this case, the project was developed from work the researchers did with federal lawmakers who have introduced legislation aimed at bolstering and expanding the U.S. electric grid. One of these bills, the BIG WIRES Act, co-sponsored by Sen. John Hickenlooper of Colorado and Rep. Scott Peters of California, would require each transmission region in the U.S. to be able to send at least 30 percent of its peak load to other regions by 2035.
That would represent a substantial change for a national transmission scenario where grids have largely been developed regionally, without an enormous amount of national oversight.
“The U.S. grid is aging and it needs an upgrade,” Senga says. “Implementing these kinds of policies is an important step for us to get to that future where we improve the grid, lower costs, lower emissions, and improve reliability. Some progress is better than none, and in this case, it would be important.”
To conduct the study, the researchers looked at how policies like the BIG WIRES Act would affect energy distribution. The scholars used a model of energy generation developed at the MIT Energy Initiative — the model is called “Gen X” — and examined the changes proposed by the legislation.
With a 30 percent level of interregional connectivity, the study estimates, the number of outages due to extreme cold would drop by 39 percent, for instance, a substantial increase in reliability. That would help avoid scenarios such as the one Texas experienced in 2021, when winter storms damaged distribution capacity.
“Reliability is what we find to be most salient to policymakers,” Senga says.
On the other hand, as the paper details, a future grid that is “optimized” with more transmission capacity near geographic spots of new energy generation would be less expensive.
“On the cost side, this kind of optimized system looks better,” Senga says.
A more geographically imbalanced grid would also have a greater impact on reducing emissions. Globally, the levelized cost of wind and solar dropped by 89 percent and 69 percent, respectively, from 2010 to 2022, meaning that incorporating less-expensive renewables into the grid would help with both cost and emissions.
“On the emissions side, a priori it’s not clear the optimized system would do better, but it does,” Knittel says. “That’s probably tied to cost, in the sense that it’s building more transmission links to where the good, cheap renewable resources are, because they’re cheap. Emissions fall when you let the optimizing action take place.”
To be sure, these two differing approaches to grid expansion are not the only paths forward. The study also examines a hybrid approach, which involves both national interconnectivity requirements and local buildouts based around new power sources on top of that. Still, the model does show that there may be some tradeoffs lawmakers will want to consider when developing and considering future grid legislation.
“You can find a balance between these factors, where you’re still going to still have an increase in reliability while also getting the cost and emission reductions,” Senga observes.
For his part, Knittel emphasizes that working with legislation as the basis for academic studies, while not generally common, can be productive for everyone involved. Scholars get to apply their research tools and models to real-world scenarios, and policymakers get a sophisticated evaluation of how their proposals would work.
“Compared to the typical academic path to publication, this is different, but at the Climate Policy Center, we’re already doing this kind of research,” Knittel says.
A smarter way for large language models to think about hard problemsThis new technique enables LLMs to dynamically adjust the amount of computation they use for reasoning, based on the difficulty of the question.To make large language models (LLMs) more accurate when answering harder questions, researchers can let the model spend more time thinking about potential solutions.
But common approaches that give LLMs this capability set a fixed computational budget for every problem, regardless of how complex it is. This means the LLM might waste computational resources on simpler questions or be unable to tackle intricate problems that require more reasoning.
To address this, MIT researchers developed a smarter way to allocate computational effort as the LLM solves a problem. Their method enables the model to dynamically adjust its computational budget based on the difficulty of the question and the likelihood that each partial solution will lead to the correct answer.
The researchers found that their new approach enabled LLMs to use as little as one-half the computation as existing methods, while achieving comparable accuracy on a range of questions with varying difficulties. In addition, their method allows smaller, less resource-intensive LLMs to perform as well as or even better than larger models on complex problems.
By improving the reliability and efficiency of LLMs, especially when they tackle complex reasoning tasks, this technique could reduce the energy consumption of generative AI systems and enable the use of LLMs in more high-stakes and time-sensitive applications.
“The computational cost of inference has quickly become a major bottleneck for frontier model providers, and they are actively trying to find ways to improve computational efficiency per user queries. For instance, the recent GPT-5.1 release highlights the efficacy of the ‘adaptive reasoning’ approach our paper proposes. By endowing the models with the ability to know what they don’t know, we can enable them to spend more compute on the hardest problems and most promising solution paths, and use far fewer tokens on easy ones. That makes reasoning both more reliable and far more efficient,” says Navid Azizan, the Alfred H. and Jean M. Hayes Career Development Assistant Professor in the Department of Mechanical Engineering and the Institute for Data, Systems, and Society (IDSS), a principal investigator of the Laboratory for Information and Decision Systems (LIDS), and the senior author of a paper on this technique.
Azizan is joined on the paper by lead author Young-Jin Park, a LIDS/MechE graduate student; Kristjan Greenewald, a research scientist in the MIT-IBM Watson AI Lab; Kaveh Alim, an IDSS graduate student; and Hao Wang, a research scientist at the MIT-IBM Watson AI Lab and the Red Hat AI Innovation Team. The research is being presented this week at the Conference on Neural Information Processing Systems.
Computation for contemplation
A recent approach called inference-time scaling lets a large language model take more time to reason about difficult problems.
Using inference-time scaling, the LLM might generate multiple solution attempts at once or explore different reasoning paths, then choose the best ones to pursue from those candidates.
A separate model, known as a process reward model (PRM), scores each potential solution or reasoning path. The LLM uses these scores to identify the most promising ones.
Typical inference-time scaling approaches assign a fixed amount of computation for the LLM to break the problem down and reason about the steps.
Instead, the researchers’ method, known as instance-adaptive scaling, dynamically adjusts the number of potential solutions or reasoning steps based on how likely they are to succeed, as the model wrestles with the problem.
“This is how humans solve problems. We come up with some partial solutions and then decide, should I go further with any of these, or stop and revise, or even go back to my previous step and continue solving the problem from there?” Wang explains.
To do this, the framework uses the PRM to estimate the difficulty of the question, helping the LLM assess how much computational budget to utilize for generating and reasoning about potential solutions.
At every step in the model’s reasoning process, the PRM looks at the question and partial answers and evaluates how promising each one is for getting to the right solution. If the LLM is more confident, it can reduce the number of potential solutions or reasoning trajectories to pursue, saving computational resources.
But the researchers found that existing PRMs often overestimate the model’s probability of success.
Overcoming overconfidence
“If we were to just trust current PRMs, which often overestimate the chance of success, our system would reduce the computational budget too aggressively. So we first had to find a way to better calibrate PRMs to make inference-time scaling more efficient and reliable,” Park says.
The researchers introduced a calibration method that enables PRMs to generate a range of probability scores rather than a single value. In this way, the PRM creates more reliable uncertainty estimates that better reflect the true probability of success.
With a well-calibrated PRM, their instance-adaptive scaling framework can use the probability scores to effectively reduce computation while maintaining the accuracy of the model’s outputs.
When they compared their method to standard inference-time scaling approaches on a series of mathematical reasoning tasks, it utilized less computation to solve each problem while achieving similar accuracy.
“The beauty of our approach is that this adaptation happens on the fly, as the problem is being solved, rather than happening all at once at the beginning of the process,” says Greenewald.
In the future, the researchers are interested in applying this technique to other applications, such as code generation and AI agents. They are also planning to explore additional uses for their PRM calibration method, like for reinforcement learning and fine-tuning.
“Human employees learn on the job — some CEOs even started as interns — but today’s agents remain largely static pieces of probabilistic software. Work like this paper is an important step toward changing that: helping agents understand what they don’t know and building mechanisms for continual self-improvement. These capabilities are essential if we want agents that can operate safely, adapt to new situations, and deliver consistent results at scale,” says Akash Srivastava, director and chief architect of Core AI at IBM Software, who was not involved with this work.
This work was funded, in part, by the MIT-IBM Watson AI Lab, the MIT-Amazon Science Hub, the MIT-Google Program for Computing Innovation, and MathWorks.
MIT engineers design an aerial microrobot that can fly as fast as a bumblebeeWith insect-like speed and agility, the tiny robot could someday aid in search-and-rescue missions.In the future, tiny flying robots could be deployed to aid in the search for survivors trapped beneath the rubble after a devastating earthquake. Like real insects, these robots could flit through tight spaces larger robots can’t reach, while simultaneously dodging stationary obstacles and pieces of falling rubble.
So far, aerial microrobots have only been able to fly slowly along smooth trajectories, far from the swift, agile flight of real insects — until now.
MIT researchers have demonstrated aerial microrobots that can fly with speed and agility that is comparable to their biological counterparts. A collaborative team designed a new AI-based controller for the robotic bug that enabled it to follow gymnastic flight paths, such as executing continuous body flips.
With a two-part control scheme that combines high performance with computational efficiency, the robot’s speed and acceleration increased by about 450 percent and 250 percent, respectively, compared to the researchers’ best previous demonstrations.
The speedy robot was agile enough to complete 10 consecutive somersaults in 11 seconds, even when wind disturbances threatened to push it off course.
“We want to be able to use these robots in scenarios that more traditional quad copter robots would have trouble flying into, but that insects could navigate. Now, with our bioinspired control framework, the flight performance of our robot is comparable to insects in terms of speed, acceleration, and the pitching angle. This is quite an exciting step toward that future goal,” says Kevin Chen, an associate professor in the Department of Electrical Engineering and Computer Science (EECS), head of the Soft and Micro Robotics Laboratory within the Research Laboratory of Electronics (RLE), and co-senior author of a paper on the robot.
Chen is joined on the paper by co-lead authors Yi-Hsuan Hsiao, an EECS MIT graduate student; Andrea Tagliabue PhD ’24; and Owen Matteson, a graduate student in the Department of Aeronautics and Astronautics (AeroAstro); as well as EECS graduate student Suhan Kim; Tong Zhao MEng ’23; and co-senior author Jonathan P. How, the Ford Professor of Engineering in the Department of Aeronautics and Astronautics and a principal investigator in the Laboratory for Information and Decision Systems (LIDS). The research appears today in Science Advances.
An AI controller
Chen’s group has been building robotic insects for more than five years.
They recently developed a more durable version of their tiny robot, a microcassette-sized device that weighs less than a paperclip. The new version utilizes larger, flapping wings that enable more agile movements. They are powered by a set of squishy artificial muscles that flap the wings at an extremely fast rate.
But the controller — the “brain” of the robot that determines its position and tells it where to fly — was hand-tuned by a human, limiting the robot’s performance.
For the robot to fly quickly and aggressively like a real insect, it needed a more robust controller that could account for uncertainty and perform complex optimizations quickly.
Such a controller would be too computationally intensive to be deployed in real time, especially with the complicated aerodynamics of the lightweight robot.
To overcome this challenge, Chen’s group joined forces with How’s team and, together, they crafted a two-step, AI-driven control scheme that provides the robustness necessary for complex, rapid maneuvers, and the computational efficiency needed for real-time deployment.
“The hardware advances pushed the controller so there was more we could do on the software side, but at the same time, as the controller developed, there was more they could do with the hardware. As Kevin’s team demonstrates new capabilities, we demonstrate that we can utilize them,” How says.
For the first step, the team built what is known as a model-predictive controller. This type of powerful controller uses a dynamic, mathematical model to predict the behavior of the robot and plan the optimal series of actions to safely follow a trajectory.
While computationally intensive, it can plan challenging maneuvers like aerial somersaults, rapid turns, and aggressive body tilting. This high-performance planner is also designed to consider constraints on the force and torque the robot could apply, which is essential for avoiding collisions.
For instance, to perform multiple flips in a row, the robot would need to decelerate in such a way that its initial conditions are exactly right for doing the flip again.
“If small errors creep in, and you try to repeat that flip 10 times with those small errors, the robot will just crash. We need to have robust flight control,” How says.
They use this expert planner to train a “policy” based on a deep-learning model, to control the robot in real time, through a process called imitation learning. A policy is the robot’s decision-making engine, which tells the robot where and how to fly.
Essentially, the imitation-learning process compresses the powerful controller into a computationally efficient AI model that can run very fast.
The key was having a smart way to create just enough training data, which would teach the policy everything it needs to know for aggressive maneuvers.
“The robust training method is the secret sauce of this technique,” How explains.
The AI-driven policy takes robot positions as inputs and outputs control commands in real time, such as thrust force and torques.
Insect-like performance
In their experiments, this two-step approach enabled the insect-scale robot to fly 447 percent faster while exhibiting a 255 percent increase in acceleration. The robot was able to complete 10 somersaults in 11 seconds, and the tiny robot never strayed more than 4 or 5 centimeters off its planned trajectory.
“This work demonstrates that soft and microrobots, traditionally limited in speed, can now leverage advanced control algorithms to achieve agility approaching that of natural insects and larger robots, opening up new opportunities for multimodal locomotion,” says Hsiao.
The researchers were also able to demonstrate saccade movement, which occurs when insects pitch very aggressively, fly rapidly to a certain position, and then pitch the other way to stop. This rapid acceleration and deceleration help insects localize themselves and see clearly.
“This bio-mimicking flight behavior could help us in the future when we start putting cameras and sensors on board the robot,” Chen says.
Adding sensors and cameras so the microrobots can fly outdoors, without being attached to a complex motion capture system, will be a major area of future work.
The researchers also want to study how onboard sensors could help the robots avoid colliding with one another or coordinate navigation.
“For the micro-robotics community, I hope this paper signals a paradigm shift by showing that we can develop a new control architecture that is high-performing and efficient at the same time,” says Chen.
“This work is especially impressive because these robots still perform precise flips and fast turns despite the large uncertainties that come from relatively large fabrication tolerances in small-scale manufacturing, wind gusts of more than 1 meter per second, and even its power tether wrapping around the robot as it performs repeated flips,” says Sarah Bergbreiter, a professor of mechanical engineering at Carnegie Mellon University, who was not involved with this work.
“Although the controller currently runs on an external computer rather than onboard the robot, the authors demonstrate that similar, but less precise, control policies may be feasible even with the more limited computation available on an insect-scale robot. This is exciting because it points toward future insect-scale robots with agility approaching that of their biological counterparts,” she adds.
This research is funded, in part, by the National Science Foundation (NSF), the Office of Naval Research, Air Force Office of Scientific Research, MathWorks, and the Zakhartchenko Fellowship.