Google.org announced on Sept. 15 that the MIT Transit Lab is a recipient of $2.1 million in funding — one of only 15 projects selected in the worldwide Google.org Impact Challenge: AI for Government Innovation. The funding from Google’s philanthropic arm will support NGOs, social enterprises, and academic institutions as they integrate artificial intelligence-powered solutions across topics like health, resilience, and economy.
The Transit Lab’s winning project, the Public Transit Intelligence Hub (PTIQ), aims to unify public transportation agencies’ real-time monitoring, operations control, and passenger communication systems into a single centralized AI-orchestrated platform that will allow transit control center staff to make better-informed, on-the-spot decisions, and provide riders with more immediate and accurate information.
The control centers of public transportation agencies are similar in appearance to the portrayal of NASA mission control in movies: rooms filled with employees monitoring dozens of radio feeds and computer screens relaying real-time camera data about stations and their operations, transit vehicle locations, riders, traffic, and road conditions. Unfortunately, the information coming in is fragmented, rather than integrated into a centralized system with overall awareness of the network’s conditions. This system creates an intense work environment for the transit staff making operations and communications decisions that can affect thousands of passengers relying on transit to get them where they need to go.
“Public transportation agencies are required to make decisions around the clock regarding real-time operations, control, and passenger communication,” says Awad Abdelhalim, associate director of the Transit Lab, and PTIQ co-principal investigator, project director, and technical lead. “Our goal isn't to automate those decisions, but to make sure the people making them have the best information possible. By unifying and streamlining data and information flow from fragmented and siloed internal systems, PTIQ will improve the experience of both riders and the transit workforce.”
Jinhua Zhao, the MIT Class of 1941 Professor of City and Transportation, head of the MIT Department of Urban Studies and Planning, and founder and director of the MIT Mobility Initiative (MMI), is the other co-principal investigator on the project. The PTIQ program manager is MIT Lecturer Jim Aloisi, who directs the Transit Research Consortium, which will also work on the project. That consortium is comprised of researchers from the Transit Lab, MMI, and Northeastern University, where Professor Haris Koutsopoulos takes the lead.
In addition to providing funding for the three-year project, Google.org will provide pro bono support from its own engineers and AI product experts.
"AI holds incredible potential to transform public services, but there is often a gap between promise and practice,” says Maggie Johnson, global head of Google.org. “By equipping the 15 selected organizations with funding and pro bono support from Google's own AI experts, we are empowering the people closest to the problem to show what is truly possible. Together, we can ensure that AI makes a profound, positive difference in the everyday lives of communities worldwide."
The project will build on the group’s decades of experience in applied-research collaborations with transit agencies in major metropolitan areas throughout the world. PTIQ’s decision support interface for control center staff will integrate predictive models, optimization engines, and large language model-based contextual reasoning. But ultimately the decision-making based on that information will be left to transit staff, who can better balance the trade-offs of making one decision over another in these often incredibly complex situations.
“The hard part of integrating AI in transit is not the technology; it’s the institution,” Zhao says. “AI is evaluated on benchmarks. Public transit is assessed in the control center and on the streets. Over decades of work with transit agencies in Washington, D.C., Chicago, London, Boston, Tokyo, and Hong Kong, we have learned to ask a different question. Not whether AI can do this, but whether it can work in the organization and whether the staff trust it. PTIQ is designed to ground AI in the institutional reality and behavioral nuances of a transit agency, and bring machine intelligence and human judgment into one place.”
“Currently the evaluation of AI models relies heavily on deterministic, objective tasks, such as solving mathematical equations or generating code,” Abdelhalim explains. “However, the vast majority of real-world operational tasks — like delivering public transit services — are highly dynamic, multi-stakeholder, and lack a single correct objective answer. These complex spatiotemporal environments are the ultimate testbed for evaluating what AI systems can add to society.”
PTIQ aims to transform the transit workforce experience, the transit rider experience, and the overall ability of transit agencies to efficiently respond to disruptions and unexpected events.
“We expect that PTIQ will take what is largely a siloed environment and connect it in ways that provide powerful benefits for the agency workforce and its riders,” says Aloisi, who is also a former secretary of transportation for the Commonwealth of Massachusetts. “[Doing this by] improving response time, reducing platform and bus stop crowding, providing riders with higher quality and timely information, and supporting agency staff — from dispatchers to vehicle operators and communications staff — with high-quality, reliable, real-time information and solution sets.”
This game-playing AI is the new champ at Stratego Able to defeat top-ranked human players and more efficient than other models, the new system could help decision-makers in military maneuvers or business negotiations.A new AI system that excels at challenging games with hidden information could someday help human decision-makers select ideal strategies to outfox opponents in complicated situations like military maneuvers.
Using advances in machine-learning, researchers from MIT, Carnegie Mellon University, New York University, and Stanford University developed an AI that defeated top-ranked human players of the board wargame Stratego by a large margin — something no AI system had been able to achieve.
Stratego, a two-player game of imperfect information, in which the opponent’s piece identities remain hidden, is often used as a benchmark to test the strategic thinking abilities of powerful AI models.
To build their model, the researchers combined efficient training algorithms with new techniques tailored for calculated decision-making in hidden information settings.
The AI system achieved greater performance at Stratego than the next best models, while being far cheaper and less computationally demanding to train. The system also outperformed top human players in other strategic games with different rules and designs, demonstrating how it can be generalized for a variety of use-cases.
The AI system could be adapted to help humans tackle many real-world problems with hidden information, such as business negotiations or cybersecurity.
“In the kind of imperfect information tasks you would face in reality, you often don’t have the luxury of enumerating through all the possibilities. There are just too many. Having AI algorithms that are general purpose and can provably perform this challenging task so well is a big step forward,” says Gabriele Farina, an assistant professor in the Department of Electrical Engineering and Computer Science (EECS), principal investigator at the Laboratory for Information and Decision Systems (LIDS), and senior author of a paper on this AI system.
He is joined on the paper by lead author Samuel Sokota, a graduate student at Carnegie Mellon; Eugene Vinitsky, an assistant professor at NYU; Zico Kolter, a professor at Carnegie Mellon; Hengyuan Hu, a graduate student at Stanford; and Zhiyuan Fan, an EECS graduate student at MIT. The research appears today in Nature.
Hidden information
The world is full of imperfect information problems.
In these interactions, some parties possess information others do not. For instance, traders in financial markets may not know the rationale behind the trades of others, while military forces likely don’t have full knowledge of enemy positions.
With hidden information, the decisions parties make, as well as the decisions they choose not to make, are intertwined in such a way that it is extremely difficult to determine the best steps to take next.
“The more you bluff, the more your opponent expects it, and the less each bluff is worth. It’s not obvious how to reason about that,” Sokota explains. “It’s very different from a setting like chess, where the best move is still the best move no matter how often you’ve played it.”
Stratego is often used to model imperfect information situations. In this board wargame, which resembles military chess, players arrange 40 pieces on their side of a board and then move pieces across the board to capture their opponent’s flag.
But the identity of all pieces remains secret until they collide, and then the lower-ranking piece is eliminated.
The possible piece configurations number more than 10 to the 66th power — an exponentially greater number than in chess — making Stratego extremely difficult for an AI system to play well.
Past efforts, such as Google’s DeepMind, relied on sophisticated operations that were computationally demanding and costly. But even with millions of dollars in training costs, these models were still not strong enough to beat top human Stratego players.
“With Stratego, there is an explosion of possible universes you might have to deal with. AI techniques that were developed for games like poker definitely could not scale in this setting,” Farina says.
The MIT researchers set out to develop a full AI system that could achieve superhuman performance for less cost, which they called Ataraxos (a Greek word used to describe one who is unbothered or free from anxiety).
A two-pronged approach
To build Ataraxos, the researchers trained the model using a technique called self-play reinforcement learning. The model plays against itself many times to learn a strong “blueprint strategy” of how to excel at Stratego.
They designed especially efficient algorithms, which enabled Ataraxos to learn much faster than prior methods while ensuring it didn’t get stuck trying to predict every possible move. This reduces training costs and boosts performance.
“Our system reaches strictly higher playing strength than DeepNash (DeepMind’s system) while using less than one hundredth of the training examples and less than one thirtieth of the self-play games, indicating a massive improvement in efficiency,” says Farina.
During a game, Ataraxos uses the blueprint strategy as a starting point to set up the board and begin thinking about its next moves at each round of play.
But before acting, it refines its choices on the fly using a technique called decision-time planning. The system employs a generative model that uses probabilities to estimate the likely identities of the opponent’s hidden pieces, then evaluates future choices before selecting the next move.
“Rather than just guessing blindly, we use decision-time planning to find the most plausible state of the board. Using this generative model allows us to really zoom in on the specific board and opponent we are facing,” Farina says.
The innovative use of this generative model for decision-time planning was the missing piece that enabled Ataraxos to achieve superhuman performance.
Ataraxos beat the strongest Stratego player in the world by a record margin of 15-1-4 and achieved a 39-2 record against top human players at the Stratego world championship. “Ataraxos is good at calculating risk in a way that humans are not. A human might start freaking out if their most valuable piece is exposed, but the bot can be surprisingly composed. It doesn’t overcorrect and give away its secrets,” Farina says.
The researchers also adapted Ataraxos for other imperfect information games, including Barrage Stratego (a faster-paced variant with fewer pieces), Hanabi (a cooperative card game with many players), and Dou dizhu (a game in which two players cooperate against a third).
The system achieved superhuman performance in each instance, demonstrating the generality of this method.
In the future, the researchers want to build interpretability measures into Ataraxos so the system can explain its decision-making in a way that a human could understand.
“Humans must have the final say in whether a recommendation is followed, so before adoption can happen, we need a way to audit the model’s decisions. We still have a long way to go, but I hope these algorithms can be the foundation for a lot more work to come,” Farina says.
This research is funded, in part, by the Office of Naval Research, the New York University Department of Civil and Urban Engineering, the C2SMART Center, the National Science Foundation, and a Schmidt Sciences AI2050 Early Career Fellowship.
Lung cancers can use two different mechanisms to evade KRAS-inhibiting drugsSome tumor cells develop resistance by amplifying the KRAS gene, while others change their tumor type, MIT researchers have found.About 25 percent of lung adenocarcinomas have mutations of the gene KRAS, which drives uncontrolled cell growth. In recent years, the FDA has approved two KRAS inhibitors to treat patients with KRAS mutations. While these drugs can work well initially, tumors almost always develop resistance to them.
Usually, resistance emerges because cells reactivate KRAS activity, through mutations that prevent drug binding or by increasing KRAS expression that overpowers the effects of the inhibitor. However, in a new study, MIT researchers have modeled an alternative mechanism that cancer cells can use to become resistant to KRAS inhibition.
The researchers found that in some cases, lung tumors undergo transformation from adenocarcinoma to squamous cell carcinoma. Both of these tumor types are commonly found in the lungs, but they are thought to arise from different cells and have different genetic profiles.
When this transition occurs, tumor cells no longer require KRAS, and appear to turn on alternative signaling pathways that help them continue to grow. Ongoing work to identify those pathways may reveal targets for new drugs that could help prevent resistance to KRAS inhibitors.
“The main takeaway is that there seem to be different routes of resistance to KRAS inhibitors, and so we need to be thinking about how we can address this,” says Carrie Rodriguez, an MIT graduate student and one of the lead authors of the paper.
Nicolas Mathey-Andrews PhD ’25 is also a lead author of the study, which appears today in the journal Nature Genetics. The paper’s senior author is Tyler Jacks, the David H. Koch Professor of Biology and a member of MIT’s Koch Institute for Integrative Cancer Research.
Tissue transformation
The two FDA-approved KRAS inhibitors both target a mutation called KRAS-G12C. These drugs are approved only for use in patients whose tumors have failed to respond to other drugs, and these patients usually have cancer that has spread beyond the lungs.
KRAS inhibitors are effective in about 35 percent of the patients who receive them. However, in those cases, the tumors almost always end up becoming resistant by generating additional copies of the KRAS gene or finding other ways to turn on the MAP kinase signaling pathway, which is usually triggered by KRAS and stimulates cell growth.
“Resistance to targeted therapies is a very serious problem,” Rodriguez says. “Sometimes these KRAS inhibitors can hold cancers at bay, but most cases do end up relapsing.”
A 2021 study from researchers at Dana-Farber Cancer Institute, which analyzed tumors from 17 non-small cell lung cancer patients treated with KRAS-G12C inhibition, identified secondary resistance mutations in a majority of patients. In two of these patients, however, the researchers found that tumors transformed from adenocarcinomas to squamous cell carcinomas, but they did not harbor obvious resistance mutations.
Both adenocarcinomas and squamous cell carcinomas are classified as non-small cell lung cancers (NSCLCs), which are the most common type of primary lung cancer. Adenocarcinomas, the most common type of NSCLCs, often originate from the surfactant-producing cells that line the lungs, while squamous cell carcinomas originate in the cells that line the central airways of the lungs.
Mutations of KRAS are found much more frequently in adenocarcinomas than in squamous cell carcinomas
In this study, the researchers set out to model the factors that might drive the transition from adenocarcinomas to squamous cell carcinomas. To do that, they engineered a mouse lung cancer model to express the mutation that is targeted by the FDA-approved KRAS inhibitors.
Following treatment with a KRAS-G12C inhibitor, tumors with genetic loss of Nkx2-1, which normally helps maintain alveolar epithelial identity, were able to undergo adeno-to-squamous transition. Turning on a transcription factor called DeltaNp63, which is overactive in many squamous cell carcinomas, also made this transition more likely. Another transcription factor known as SOX2 also helped stimulate the transition, but this gene could not initiate the transition on its own.
Paths to resistance
Tumors that underwent these tissue transformations did not acquire the mutations that typically boost KRAS expression in adenocarcinomas. Instead, KRAS signaling was shut off. The researchers hypothesize that these cells may turn on another signaling pathway that helps them to continue growing.
“There seem to be several different routes where you can get to squamous transformation, either through loss of lung-lineage-defining transcription factors, or overexpression of these squamous master regulators, SOX2 or DeltaNp63. Those resistant squamous tumors no longer respond to KRAS inhibition because they shut off the signaling or at least dampen it significantly,” Rodriguez says.
The researchers are now further exploring what happens to tumor cells as they transition to a squamous state, in hopes of identifying vulnerabilities that could be targeted with new drugs.
“Fundamentally this is a transition that’s poorly understood, and we were happy to see that we were able to model it,” Mathey-Andrews says. “Future directions that have an eye toward translation will utilize those models to understand the process and conditions by which histologic transformation occurs, and then also nominate potential targets downstream.”
The research was funded, in part, by the Koch Institute Support (core) Grant from the National Cancer Institute, a Ruth Kirschstein National Service Research Award, the National Institute of General Medical Sciences, and the Ludwig Center at MIT.
Climate Action Learning Lab bridges research and policy for effective climate solutionsJ-PAL North America’s Learning Lab supported a second cohort of U.S. government and nonprofit organizations in building and using rigorous evidence to advance effective decarbonization and adaptation strategies.J-PAL North America, a regional office of MIT’s Abdul Latif Jameel Poverty Action Lab (J-PAL), convened the second cohort of the Climate Action Learning Lab this spring with 17 climate leaders from four U.S. government agencies and nonprofit organizations. Participants then engaged in four months of programming designed to strengthen their skills in generating and using evidence, applying research insights to their own programs, and identifying promising policy-relevant interventions for evaluation.
The Climate Action Learning Lab first emerged in 2025 as a response to an urgent need for rigorous research on programs that seek to improve resilience to climate-related hazards and support the transition to a low-carbon economy. By helping participants identify interventions and develop evaluation plans, the Learning Lab aims to generate evidence about which approaches are most effective, and for whom.
“We have a unique opportunity to embed rigorous evaluation into promising programs as they are implemented in order to accurately measure their impacts on emissions reductions,” says Peter Christensen, scientific advisor of the J-PAL North America Environment, Energy, and Climate Change Sector. “By developing rigorous evaluations, Learning Lab participants can better understand the behavioral mechanisms that drive program impacts and cost-effectiveness, and build an evidence base to inform more effective policymaking.”
Following the success of last year’s Climate Action Learning Lab, which led to multiple research collaborations and the launch of two randomized evaluations, J-PAL North America recruited a second cohort of leaders representing four organizations: the City of Boston’s Sustainability Office, the Hawaii Climate Change Mitigation and Adaptation Commission, the Oregon Department of Environmental Quality, and the Electrification Coalition.
From May through August, the cohort engaged in a set of offerings including training on impact evaluation, learning how to formulate research questions, and assessing the generalizability of the existing evidence to their own contexts. Participants had the opportunity to explore J-PAL resources, including the recently released Climate Action Evidence Review, which synthesizes existing evidence and highlights important gaps where more research is critical to inform effective, equitable climate action.
“It was exciting to learn where the gaps in research are and where we have an opportunity to lead. The experience reinforced that we are addressing issues that have not been widely studied, and having access to researchers’ expertise was incredibly valuable,” says Ana Paola De La Vega, from the City of Boston’s Environment Department. Throughout the Learning Lab, the city explored a potential evaluation of its Boston Energy Saver program to better understand its impacts on energy cost savings and energy efficiency incentive uptake among small businesses.
Members of the Climate Action Learning Lab put theory into practice through personalized strategy sessions, where they examined potential programs for evaluation. Researchers from the J-PAL network joined select sessions to advise organizations on which programs to prioritize, considering factors such as research feasibility and existing evidence gaps. Each participating organization selected a target program and explored potential randomization approaches.
“The Climate Action Learning Lab provided our team with a valuable opportunity to catalog our projects and better understand what makes a program ready for evaluation. It also helped us identify which initiatives are the strongest candidates for rigorous evaluation and how to prioritize them,” says Leah Laramee, Hawaii climate change mitigation and adaptation coordinator. During the Learning Lab, the team assessed three potential programs for evaluation and selected a rebate finder that connects residents with climate-related programs, with a focus on understanding its impact on program uptake, particularly among vulnerable communities.
In August, J-PAL North America hosted a virtual summit to celebrate Learning Lab participants as emerging champions for evidence in the climate space. During the event, cohort members presented their priority research questions and strategic evaluation plans and received feedback from researchers and peers. These presentations highlighted the progress made throughout the engagement and provided an opportunity to discuss next steps for advancing organizations’ evaluation plans beyond the Learning Lab.
“Overall, the Learning Lab has provided our team with a strong foundation to think critically about our own programming when applying for grants, setting up new projects, and determining how to assess impact from the beginning. This knowledge could ultimately help us determine what approaches the Electrification Coalition can take in future policies and programs,” says Ashley Blackwell, deputy director at the Electrification Coalition.
Although formal Learning Lab programming has concluded, J-PAL North America will continue supporting organizations interested in launching a randomized evaluation through partnership development with researchers and potential funding opportunities. This Learning Lab cohort will join J-PAL North America’s Climate Action Community of Practice, alongside longtime partners and participants from the inaugural Learning Lab cohort. Together, Community of Practice members will continue to exchange ideas, build connections, and explore evidence-informed approaches to mitigation and adaptation strategies.
To learn more about J-PAL North America’s work in the energy, environment, and climate change sector, including our full range of activities, resources, and partnership opportunities, visit the Evidence for Climate Action Project webpage.
Powered by muscle cells, a paper-thin robot swims through watery mazeMIT engineers’ new aquabot offers a way to design small, efficient “biohybrid” robots.Swimming can take a lot of muscle. But as MIT engineers have found, even a single layer of muscle cells can power through water if designed right.
In a paper appearing today in the journal Advanced Functional Materials, the team presents a design for a thin, muscle-powered swimming robot. The “skeleton” of the aquabot is made from a film of gel that is about the length and width of a stick of gum. The two halves of the gel form the “fins” of the bot. Each fin is covered with a layer of live muscle cells that is much thinner than a single strand of hair. The cells are genetically engineered to twitch in response to light.
When the researchers shine light on one fin, the muscles on its surface twitch in response, causing the whole fin to flap with enough force to pull the robot through water. By flashing light on one fin or the other, at various intervals, they can control the swimming robot’s direction and speed.
The engineers showed that the paper-thin bot could swim and swivel through a simple watery maze. At its fastest, the robot can swim a distance of about four times its body length in one minute. That’s a snail’s pace compared to Olympic swimmers, who can cover up to 65 body lengths per minute. But the bot could hold its own against more leisurely swimmers like the cow shark, which explores the ocean at about the same rate.
“It takes a lot of force to move through water versus air,” says study author Ritu Raman, associate professor of mechanical engineering at MIT. “The robot’s quite strong, given its size.”
The new robot is the first example of a very thin, two-dimensional, muscle-powered robot capable of locomotion.
“Currently, biohybrid robots from our group and others’ are built from bulky, 3D chunks of lab-grown skeletal muscle that require millions of cells to fabricate,” says Raman, who notes that thinner, less bulky designs such as the team’s new bot could be cheaper to build and could move more efficiently. “We believe that biohybrid robots powered by living muscle could one day perform delicate jobs like exploring environments too fragile or unpredictable for conventional hardware, because living tissue is soft, responsive to its surroundings, and can heal itself.”
The study’s MIT co-authors are first author Maheera Bawa, Arielle Berman, Laura Schwendeman, Ferdows Afghah, and Seanbiron Johnson.
Maximizing movement
Last year, Raman’s group developed an iris-inspired disk of artificial muscle tissue. They stamped a disk of gel with a pattern of concentric and radial grooves, and deposited live muscle cells onto the gel’s surface. The cells formed a thin layer that grew along the grooves, and when stimulated with light, the cells moved in patterns that stretched and squeezed the disk, similar to how a human iris dilates and constricts the eye’s pupil.
That work was the first to demonstrate that muscle cells could be grown in a very thin layer, and in complex patterns that when stimulated could move in multiple, controllable directions.
“People hadn’t seen this muscle architecture engineered from scratch before,” Raman says. “And the cells were moving in multiple directions. But they only moved about 100 microns. From a robotics perspective, their movements were tiny.”
In their new work, the team aimed to maximize muscle movements to produce more force — enough, say, to power a swimming robot. The key, they found, was to optimize the skeleton on which the cells grow.
In their previous iris-inspired design, they grew muscle cells on fibrin, which is a type of ultrasoft gel that the team realized can quickly shrivel in response to the forces generated by the muscles. To better support cells and maximize their force, the researchers focused on tuning the underlying gel by changing three properties: the gel’s composition, its stiffness, and the size and shape of the grooves that are stamped into it.
“For engineering any type of tissue, it’s known that these are knobs you can tune,” Raman says. “And we wanted to optimize all these parameters to support live muscle cells.”
Tuning a skeleton
To find an optimal “skeleton” on which to grow muscle cells, the team experimented with multiple formulations of gel, of different stiffnesses, and stamped with grooves of different geometries. For instance, one groove type resembled a skinny square trough, where another was more of a long curved valley. They found that when they deposited muscles onto each type of grooved gel, cells settled into alignment in grooves that were more square than curved. More aligned cells tend to fuse into fibers that then form a stronger, more coordinated muscle tissue. Square grooves, they found, were the way to go.
Instead of using fibrin, they tried gelatin methacrylate (GelMA), a material that is often used in tissue engineering. They made different recipes of GelMA to create skeletons of different stiffnesses and observed how muscle cells grew when deposited on the gel’s surface. They found that cells grew in better alignment, and produced the most force, on stiffer gels.
The team also varied the gel thickness and found that a half-millimeter-thin film of GelMa offered good support for a single layer of muscle cells. The film was light enough that the cells were able to stick to the gel when they contracted, rather than peeling away.
Finally, the team “exercised” the muscles, using a training routine of flashing lights to strengthen the muscles.
With the pumped-up cells and the optimized gel, the team designed a thin, two-finned robot, comprising the gel, stamped on both sides with square-bottomed grooves and lined with muscle cells. The cells fused into fibers, eventually forming a strong, aligned muscle tissue.
“You can think of the robot as having two independent muscles,” Raman says. “If we shine a light on just one, only that muscle moves. If shining on both, they both flap.”
The researchers submerged the robot in a large petri dish of water and manually maneuvered a light source over the bot. The robot followed the light, flapping its fins in response to navigate through a maze that the team placed in the dish.
The current design is relatively basic as far as its form. The researchers intended first to show that the bot could produce enough force to swim.
“Our next goal is to optimize the body design to enable faster swimming,” Raman says. “But even at slow swim speeds, one could imagine a muscle-powered swimmer being used for purposes like environmental monitoring in aquatic environments.”
This research was supported, in part, by the Office of Naval Research.
The effects of an “algorithmic monoculture” depend on the detailsIn a study focusing on hiring decisions, MIT researchers found the use of a single algorithm by many firms could benefit job seekers in certain situations.AI tools are increasingly replacing human judgements in some settings. For instance, resume screening algorithms are often used in hiring, where they may improve efficiency and consistency in decision-making.
But some scholars have raised concerns that the adoption of automated systems could eventually result in one algorithm being used to make all decisions in a particular industry. They worry so-called algorithmic monoculture could have negative consequences.
For example, in hiring, the thinking goes that algorithmic monoculture might result in systematic exclusion — a situation in which a job candidate rejected by one firm’s algorithm would likely also be rejected by every other firm’s algorithm.
However, MIT researchers now argue that algorithmic monoculture may not always be as bad as some scientists have suggested.
They systematically evaluated major objections to algorithmic monoculture, including systematic exclusion, and concluded this and many other arguments either fail or aren’t decisive against all forms of monoculture.
Instead, they mathematically prove that monoculture tends to create informational echo chambers that can hinder exploration. In hiring, this could make it less likely that the best candidates would get jobs — however, bundling various hiring algorithms into a single “ensemble” can overcome this limitation, the researchers show. This could sometimes enable monoculture to perform as well as, if not better than, a polyculture where different firms use different algorithms.
“A trend toward algorithmic monoculture is a realistic scenario, and a really important issue that is being brought about by the use of AI, but it is hard to say in the abstract whether monoculture would be a bad thing. It depends on the details, like the domain we are talking about and the accuracy of the algorithm itself,” says study co-author Brian Hedden, a professor in the Department of Linguistics and Philosophy, who holds an MIT Schwarzman College of Computing shared position with the Department of Electrical Engineering and Computer Science (EECS) and is also a principal investigator in the Laboratory for Information and Decision Systems (LIDS).
Hedden is joined on the paper by co-author Manish Raghavan, the Drew Houston (2005) Career Development Professor at the MIT Sloan School of Management and in EECS, as well as a LIDS principal investigator. The research appears in Philosophical Perspectives.
The move toward monoculture
Algorithmic monoculture, in which all decisions across a certain domain are made using the same algorithm, is not a new phenomenon.
For instance, lending decisions were once made by independent bankers at individual banks, but now all bankers use the same information based on a borrower’s standardized credit scores, which are derived from the Fair Isaac Corporation (FICO) algorithm.
Similarly, a handful of resume screening algorithms are commonly used by many Fortune 500 companies.
“The worry is that, as more people use AI and algorithms to get information and make decisions, there is more of a vehicle for this kind of correlation to occur,” Raghavan says.
To better understand this issue, he and Hedden joined forces to systematically assess the promises and pitfalls of algorithmic monoculture. They focused on hiring, but their approach could apply to other domains, such as lending. (They note, however, that other domains, like generative AI content creation or AI-guided scientific research, may work differently, and that monoculture in some of these domains may be more problematic.)
The researchers began by exploring one common objection to algorithmic monoculture: that reliance on the same algorithm will systematically exclude certain people from opportunities.
This could occur in hiring because, if one firm screens out an individual’s resume, that applicant will likely face the same bad luck at each firm.
But after systematically evaluating this argument using a series of models that capture multiple situations, the researchers argue it isn’t compelling since the overall number of people hired is not affected by the fact that firms use the same algorithm.
Rather, algorithmic monoculture could improve bargaining power of job candidates.
“All the jobs get filled and the same number of people have jobs, but the firms are fighting over the same pool of candidates, which actually drives up wages,” Raghavan says.
They also explored objections related to agency. For instance, if a job candidate applies for a job and their resume is forwarded to every firm using the hiring algorithm, the candidate never gets a chance to adjust their resume to improve their chances.
“This seems like a good objection to bad forms of monoculture. But if you have a monoculture where you get to revise your resume and resubmit your materials, then this doesn’t hold up,” Hedden says.
On the flip side, monoculture could enable individuals to game the system. For instance, if having one’s resume in a certain format leads to a better outcome, job candidates could simply reformat their resumes to improve their chances.
“But it is not obvious that having one algorithm would incentivize this kind of gaming more than having a bunch of different algorithms used by different firms,” Hedden says. “In the latter scenario, you might just target a couple of firms’ algorithms and try to game them, giving yourself a bit of advantage with a few employers.”
The wisdom of crowds
They also considered a less-explored objection: that monoculture can increase homogenization of information.
Based on the “wisdom of crowds,” a theory from social psychology, a diverse group of independent decision makers can outperform a single person, Hedden explains.
In hiring, this means that having firms with diverse hiring algorithms can lead to a higher-quality pool of new hires.
Algorithmic monoculture could also cause candidates with the same characteristics and credentials to be hired every time by every firm. This may prevent firms from discovering candidates who may be better alternatives.
“Monoculture might inhibit the amount of discovery that happens overall. It is not clear if that is a bad thing, but it is definitely a worry when we think about designing AI for applications like science, art, or writing,” Raghavan says.
This problem could be mitigated by building randomness into a monocultural platform, which could induce a higher level of exploration, he adds.
In addition, the performance of monoculture depends on the algorithm. If a single algorithm is much more accurate than the many algorithms used by different firms, monoculture may be better system.
One way to boost performance may be to package multiple firms’ hiring algorithms into one “ensemble algorithm” that could assign each job candidate a score based on the average.
By conducting a series of simulations of different hiring situations, the researchers confirmed that such an “ensemble algorithm” could sometimes outperform the use of multiple algorithms.
However, it remains to be explored how feasible this kind of algorithmic “ensembling” would be in practice, Hedden says.
“A lot of the answers around the promises and pitfalls of algorithmic monoculture are going to be contextual. Even from a research perspective, there is still a lot of work to be done to figure out how we can approach these concerns from an empirical perspective,” Raghavan says.
Ultimately, the researchers hope this work inspires additional research about the long-term consequences of algorithmic monoculture, as well as studies that focus on the real-world complexities involved in a complex system like a job market.
Who we become when we talk to machinesProfessor Sherry Turkle’s new book, “Artificial Intimacy,” offers a withering critique of chatbots and the antisocial dynamics she believes they encourage.Brian, a middle-aged financial consultant, spends his day sitting in front of three screens. Two of them involve his job. The third features a chatbot, which he has given a woman’s name and frequently uses. Brian spent years on the road for work earlier in his career, has never married, and recently broke up with a woman who said he was emotionally unavailable. What did Brian do, in response? He asked the chatbot if the woman had a point.
“It’s an extraordinary moment,” writes MIT Professor Sherry Turkle, who interviewed Brian (not his real name) while conducting her research for her new book about chatbots. “Brian asks an object with no emotions to tell him if he is emotionally withholding: ‘Speak to me about what you cannot experience.’ As soon as he asks the program to talk about intimacy, he’s asking it to punch above its weight.”
And yet, this kind of thing seems to be happening a lot today.
“People think the empathy of a machine is what empathy is, then turn away from the people in their lives because they’re not empathetic enough,” Turkle says. “We’re getting ourselves in a position where human beings are too much work, right at the moment when we have never needed other people more.”
After all, what is a chatbot? It’s a computer program predicting the most plausible next string of text in a conversation, based on massive amounts of data fed into it.
“What a chatbot does is offer pretend empathy,” Turkle says. “After it tells you how much it loves you and how much it understands you, it doesn’t care if you kill yourself or cook some pasta.”
Sadly, chatbots have in fact been associated with high-profile cases of teen suicide as well, sometimes after teens get drawn into extensive dialogues with chat tools.
Turkle explores this terrain in a new book, “Artificial Intimacy: Who We Become When We Talk to Machines,” published today by Little, Brown and Company. After surveying evidence and conducting new research, she emphatically concludes that chatbot use, while it may often feel like a short-term salve, is broadly detrimental in terms of human development and social connectivity.
“We’re doing ourselves a tremendous disservice at every moment in the life cycle,” says Turkle, the Abby Rockefeller Mauzé Professor of the Social Studies of Science and Technology at MIT.
The inner history of technology
A sociologist and clinical psychologist by training, Turkle is a longtime faculty member in MIT’s Program in Science, Technology, and Society. In books such as “The Second Self” (1984), “Life on the Screen” (1997), and “Alone Together” (2011), she has evaluated the interplay of technology, psychology, and personal identity. In “Reclaiming Conversation” (2015), she documented the costs of texting and using social media.
“I feel the story I’m telling is the inner history of technology,” Turkle says. “Not just what it does, but what it does to people.”
Turkle structures “Artificial Intimacy” around the stages of a human life and explores the implications of chatbots for each one. In her interviews with children, Turkle finds a persistent blurring of the line between chatbots, people, and other devices.
One 8-year-old uses the same phone to talk to their grandparents and to ChatGPT, regarding them all as “things you reach on your phone.” A weary graduate-student mother who uses a chatbot for bedtime stories says her daughter thinks the chatbot is “a person in the phone, absolutely.”
In this sense, chatbots may be interfering with even the most basic childhood processes of distinguishing people from inanimate objects. Turkle finds many additional problems with the use of chatbots as ever-present entertainment for children, noting that a certain amount of time alone helps the development of imagination and inner resources.
“Children can’t learn trust from a device that not only lies but doesn’t know when it lies,” Turkle writes. “They can’t develop the capacity for solitude that enables both a sense of self and the capacity for mutuality.”
All told, in affecting the ability of children to develop, the dangers of chatbots are “existential,” Turkle believes.
Facing reality, but understanding the appeal
Adults don’t fare much better when they use chatbots heavily, Turkle says. “Artificial Intimacy” explores case after case of grown-ups who become dependent on chatbots as well: people going through divorces or estrangements who want dialogue, students looking for advice about applying to college or graduate school, workers who enlist ChatGPT to do assignments, and more. They start using chatbots, keep using chatbots, and before long seem less interested in human interaction, and less capable of it.
“Once people are involved with a connection with a robot, they start to think that it’s alive, that it cares about them, that it loves them,” Turkle says.
That means people can lose or fail to build their own capacities for new thought, and opt out of dealing with the real world in all its maddening-but-affirming complexity.
“We’re de-skilling ourselves as relational beings,” Turkle says. “We’re also de-skilling ourselves in work. We’re de-skilling ourselves in personal relationships. It’s across the board.” And speaking of a practice multiple people in the book have attempted, she says, “When we build chatbot avatars of dead relatives to keep them alive, we can lose our ability to mourn.”
We are not, in her estimation, doing the hard work of figuring other people out, seeing things from different points of view, and putting in the effort to build on those things and make society better.
“We’re starting to define being human as not doing the work,” Turkle says.
For all of that, a considerable amount of “Artificial Intimacy” involves understanding why people engage with chatbots. After all, as Turkle writes in the book, “Chatbots always agree with us and affirm us. They always offer us their full, undivided attention.” And once that happens, things seem to just go from there.
People, meanwhile, can be prickly, demanding, and moody. As Turkle says: “People say they prefer the chatbot because their husband or wife says, ‘Dear, you took out the garbage, but also do the dishes, and clean up the kitchen while you’re at it.’ And a chatbot just says, ‘Oh, you’re so wonderful.’”
She adds: “This technology is offering something people really want, which is to feel less vulnerable. And it offers it over and over again. You don’t want to have to ask somebody out? Don’t want to offer condolences? At every opportunity, technology says, ‘Why don’t you do this thing that’s less hard.’”
And as Turkle acknowledges in the book, there is a shortage of services such as mental health care providers in the U.S., where only about half of people have access to one, according to a federal government study she cites. Chatbots are helping to fill this void, for better or worse.
Don’t fear the friction
Turkle also notes that the age of social media has likely led people to have fewer in-person friendships and interactions, a problem that chatbots are now aiming to address.
“You take away people’s capacities, then you offer technology as the cure for the problems technology caused in the first place,” Turkle says.
In light of all this, given Turkle’s dim view of chatbots amid the spread of AI, what is actually to be done to restore human interaction? For starters, Turkle thinks, we need to face up to the idea that life is not frictionless — and that’s okay.
“Everything in the life cycle is about facing up to friction and fears and stress and tension, and understanding that friction is not a bad thing,” Turkle emphasizes. Developing the capacity to overcome difficulties is an essential part of life. In trying to sidestep the hard work of being social beings, she thinks, personal technology is enfeebling us.
Beyond that, Turkle envisions pushback against chatbots similar to the movement against, say, having phones in schools or letting young people use social media.
“I hope my book is part of a larger and larger movement,” Turkle says. “I don’t want to be alone. I want to be part of a movement pushing back.”
Other writers in this domain have praised “Artificial Intimacy.” Journalist Nicholas Carr, author of “The Shallows,” has stated it “will help you avoid the profound but often hidden threats AI poses to you and your relationships.” Psychologist Jonathan Haidt of New York University, author of “The Anxious Generation,” has stated that Turkle’s “groundbreaking research and beautiful writing make her the most qualified member of Team Humanity to call us back to our senses, and to each other.”
For her part, Turkle says, “I wanted to write a book that college students would read, that high school seniors, juniors would be able to read, that parents would pick up and not be intimidated by, that teachers would read.”
And “Artificial Intimacy” offers a recurring question for those readers.
“If not a richer life in the real,” Turkle writes, “what’s our endgame?” The purpose of life, she underlines, is not to avoid it, but to tackle it head on.
“It’s one thing if you say, my teen is texting too much,” Turkle says. “It’s very different if your 2-year-old is thinking a plushy toy with a chatbot inside is their best friend. Because you are getting into the intimate infrastructure of what makes a person develop. Social media came for our attention. Chatbots come for our capacity for attachment. That’s toxic on another level. What is the endgame? That the baby will prefer chatbots to people who are much more complicated and hard? Is that who we want to be?”
Pressurized experiments could help wind farms generate more powerA new way of simulating wind turbines in the field shows how tweaking turbine operation could unlock tens of thousands of dollars per turbine every year.The world needs more wind energy. But anyone designing new wind turbines or trying to squeeze more power out of existing ones faces a stiff challenge testing new approaches. That’s because the atmosphere is a tough place for a controlled experiment.
Some researchers use wind tunnels to conduct tests, but scaled-down wind turbines in traditional wind tunnels can differ widely from conditions in the field. (Wind turbines are the largest rotating machines ever made.) The problem hampers not only development of better wind turbines, but also our understanding of basic questions like how much power to expect from a turbine when winds change direction.
In a new open access paper published in PNAS Nexus, researchers closed the gap between experiments in the field and the lab by using a wind tunnel that features high pressurization to simulate the flow physics in the atmosphere. With this approach, the researchers determined how the alignment of the turbine and its tip speed relative to the wind influence the power it generates, offering new insights into how to get more power from existing wind farms.
They also used the approach to validate a computationally lightweight model that engineers can use to test different turbine designs and wind farm control strategies.
Together, the researchers estimate that optimizing the turbine alignment relative to wind, the blade pitch angles, which control the airfoil’s angle of attack, and the tip speed relative to the wind could potentially result in tens of thousands of dollars per turbine every year in additional revenue.
“The immediate impact of this study is that we’ve now both improved and validated models that go into wind turbine control protocols for existing farms,” says Michael Howland, MIT’s Jeffrey Cheah Career Development Professor. “The bigger, medium-term impact, with a much larger upside, is this new experimental paradigm to rapidly prototype, validate simulation models, and test hypotheses about better designs and control strategies much faster than has been possible before.”
Joining Howland on the paper are first author John Kurelek, an assistant professor at Queen’s University; MIT PhD candidates Ilan Upfal and Kirby Heck; Queen’s University postdoc Supun Pieris; Penn State University researcher Alexander Piqué; and Princeton University Professor Marcus Hultmark.
Answers in the wind
Howland has spent years developing models to simulate wind farm performance and developing new techniques to increase their power output. In 2022, he showed that accounting for the wake of individual turbines when controlling the entire wind farm could significantly increase power output.
But that work required his research team to first conduct a lengthy field experiment that temporarily resulted in lowering a real wind farm’s power output by intentionally misaligning turbines from the wind for months to better understand their performance in misalignment.
“Wind energy is a uniquely challenging problem to study experimentally,” Howland says. “We want to test the effect of a certain change in isolation, but wind farms operate in chaotic, turbulent environments where the weather is constantly evolving. Wind turbines have to react to weather conditions that we have no control over, and that introduces complexities in identifying the impact of the imposed change we are studying. The field sits at this unique intersection between environmental flow, mechanics, aerodynamics, and meteorology.”
The difficulty of running experiments at real wind farms has left researchers and engineers unsure of how changes in the alignment between the wind and turbine or factors like the turbine’s tip speed relative to the wind change power output.
In fact, the researchers say many predictive models people use are built on the assumption that turbines are always perfectly perpendicular to the wind. That’s rarely the case in the real world, even with modern turbines that gradually adjust their angle in response to the wind’s rapid directional changes.
“People have been debating which models are best for understanding the output from these wind farms, but if you have nothing to compare them against, it’s very difficult to advance the field,” Hultmark says. “This paper tries to do both of those things.”
Hultmark’s research lab at Princeton has pioneered the study of scaled-down wind turbines in pressurized wind tunnels, which, as previous studies have shown, better reproduce large-scale turbines in the atmosphere because pressure makes air more dense, resulting in more inertia within the scaled laboratory environment. For the new study, the researchers used a turbine measuring 15 centimeters in diameter at varying pressures of up to 240 atmospheres.
“By pressurizing the chamber, we’re testing a turbine that is, all else being equal, 15 to 20 meters in diameter, with the ability to go up to 35 meters in diameter,” lead-author Kurelek explains. “That’s because we’re increasing the density by a factor of 100 to 220 times,”
Kurelek sent the dimensions of the wind tunnel and wind turbine setup to Howland, who used them to calculate the aerodynamics, forces, and power production using a newly developed unified wind turbine model, which builds on previous work that developed a more general aerodynamic theory for wind turbines. The new model enables the researchers to simulate wind turbine performance across operating conditions without relying on empirical corrections that have historically been used in wind power models.
The researchers then ran a series of experiments in the tunnel over the course of several weeks, testing the turbine’s performance at different wind alignments and with different control strategies, to isolate how each factor affects performance.
They found power output could be significantly increased by adjusting the turbine’s tip speed based on its misalignment angle with the wind — a control strategy that is rarely employed in wind farms today but could offer a way to boost performance with minimal added costs.
“The big output of the experiments was clearly showing that new power maximums can be achieved when the turbine becomes misaligned with the wind through only changes to the tip speed,” Kurelek says.
Scaling the approach
The study served as validation for Howland’s model, which is fast enough to be run by engineers designing and operating wind turbines around the world using regular laptop computers.
“What we really want to know is if the turbines are always operating in some degree of misalignment with the wind, how should we control the turbine to get the maximum achievable power production?” Howland explains. “Our unified momentum model was able to make predictions of how to do this control a few years ago, and this is the first time we’e able to experimentally validate that model.”
Howland says validating models is only one part of the paper’s potential impact.
“This study also shows the huge opportunity to perform these high-throughput, controlled experiments in the pressurized facilities that Marcus and John work with, enabling us to achieve the right physics but in a time efficient and low-cost manner,” Howland says. “Right now, there’s a massive gap between idealized theoretical and simulation models and full-scale testing in extremely complicated field environments. Nothing is filling that gap except for these pressurized experiments. I hope this can be an enabler to investigate a huge range of unanswered wind energy questions in controlled environments.”
The work was supported in part by the Natural Sciences and Engineering Research Council of Canada; the National Science Foundation; and the MIT-GE Vernova Alliance.
New formulation helps RNA vaccines withstand high temperaturesMIT engineers have found a way to stabilize the lipid nanoparticles used to deliver RNA vaccines, which could allow the vaccines to be more widely distributed.RNA vaccines, which have been proven effective against Covid-19, are now being developed for many other diseases, including cancer. One of the drawbacks to these vaccines is that they require ultracold storage, but researchers from MIT have found a promising way to overcome that limitation.
With help from an AI algorithm, the researchers tweaked the formulation surrounding the lipid nanoparticles that are typically used to deliver mRNA vaccines, making the vaccines more heat-resistant. Using this approach, they formulated vaccines that could remain stable even when stored at room temperature for up to a year, or at nearly 100 degrees Fahrenheit for two months.
When Covid-19 vaccines carried by these particles were administered to mice, they generated just as strong an immune response as an RNA Covid-19 vaccine similar to one developed by Moderna. By using the AI algorithm to predict the optimal formulations for the particles, the researchers were able to cut down the number of experiments they needed to do, which rapidly sped up the development process.
“The real beauty of this algorithm is that we can use it with small data sets,” says Ana Jaklenec, a principal investigator in MIT’s Koch Institute for Integrative Cancer Research. “It’s really hard to run thousands of experiments, so this algorithm allows us to more easily achieve formulations with features that we want — in this case, stability.”
Jaklenec and Robert Langer, the David H. Koch Institute Professor, are the senior authors of the paper, which appears today in Nature Biotechnology. Graduate student Jinbi Tian and postdoc Khanh Tran are the lead authors of the paper.
Stable vaccines
RNA is a highly fragile molecule, so researchers stabilize it with lipid nanoparticles (LNPs) that protect the RNA from degradation and help it get into cells. However, these RNA-LNP vaccines still need to be kept cold (-20 to -80 degrees Celsius), which makes it difficult to ship them to regions that don’t have cold-storage facilities available.
Making these vaccines more heat-tolerant would not only enable them to be distributed more widely, but could also help researchers develop new vaccines that could be administered through novel methods such as microneedle patches. These patches contain hundreds of vaccine-filled microneedles, which dissolve when the patch is applied to the skin, releasing the vaccine.
To create more stable RNA vaccines, researchers have experimented with adding a variety of excipients — sugars, salts, or polymers — to the LNPs. Jaklenec and Langer recently developed polymer-stabilized LNPs that can withstand higher temperatures, but those LNPs were slightly different from the FDA-approved formulations that were used for the Moderna and Pfizer Covid-19 vaccines.
In their new paper, the researchers wanted to see if they could find a way to make those FDA-approved formulations more stable at high temperatures.
They began by reusing some of the excipients that had worked in their earlier efforts, but they were “really getting stuck,” Jaklenec says. “We were trying to use and screen excipients that we’ve previously used successfully to stabilize LNPs, but it just wasn’t working. It was really frustrating for the team.”
To speed up their progress, the researchers decided to try a machine-learning approach. Working with researchers at MIT’s Computer Science and Artificial Intelligence Lab (CSAIL), they developed an algorithm that can make predictions based on very small datasets.
“We’d used our algorithms for various automated experimental design applications before, but never on a biological problem like vaccine stability,” says Mina Konaković Luković, an assistant professor of electrical engineering and computer science in MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL), who is also an author of the paper. “It was surprising to see how quickly the algorithm converged on a stable formulation — getting there in just a handful of iterations, rather than the exhaustive search that would normally be required.”
The researchers used this algorithm to analyze nearly 50 FDA-approved excipients. For each excipient, the researchers first measured how well it stabilized RNA when incorporated into an LNP. They used these particles to deliver mRNA encoding a protein called firefly luciferase, which produces bioluminescence, into cells. By measuring how much light was emitted by the cells, the researchers could determine how effectively each excipient protected the mRNA.
The researchers chose five of the most promising excipients and used their AI algorithm to predict ratios of those excipients that would best stabilize LNPs similar to those used by Moderna. Based on those predictions, the researchers tested two formulations at a time in cells, fed those results back into the algorithm, and generated more predictions. After several rounds, they chose one formulation that appeared promising enough to test in animal studies.
This process took only a few weeks, much less than it would have taken without guidance from the AI algorithm.
“Before we implemented the AI algorithm, we spent several months testing different combinations and also doing the prescreening of all the excipients that we could find, but nothing would get us to 100 percent stability,” Tran says.
Robust immune responses
To test the heat resistance of their new LNP formulation, the researchers used the particles to package Covid-19 mRNA antigens, then dehydrated them using a process called vacuum drying. These particles were then stored at 37 degrees Celsius (98 degrees Fahrenheit) for two months, or at room temperature for one year. Mice that were vaccinated with these particles, even after long-term storage, showed equivalent immune responses to mice that received vaccines carried by LNPs similar to the original Moderna formulation.
The researchers also used their new heat-resistant formulation to create solid microneedle patches that could deliver a SARS-CoV-2 antigen. These patches generated an immune response similar to that produced by the injectable RNA vaccines.
“Our approach broadens the application of not only mRNA vaccines, but also therapeutics or advanced drug-delivery platforms like controlled-release particles or microneedle patches, which requires the formulation to either be in solid state or to be stable at higher temperature,” Tian says.
The researchers also showed that they could use their algorithm to stabilize other LNP formulations, including one similar to those used by Pfizer to deliver its Covid-19 vaccine. This formulation uses the same excipients as the one the MIT team developed for the Moderna LNP, but in a different ratio. For each LNP, once a heat-resistant formulation has been developed, it could be adapted to deliver any type of mRNA payload, the researchers say.
The research was, in part, funded by the Gates Foundation.
MIT students gain a humanist lens on technical innovation in Tulsa, OklahomaThe PKG Center for Social Impact expands Code.Tulsa experiential learning program.When MIT mechanical engineering student Daphne Wang arrived for her internship at the Muscogee Creek Nation Department of Health in Tulsa, Oklahoma last summer, she expected to be writing code. To her surprise, she found herself analyzing tribal history and the implications for technical innovation.
“I learned so much that I think should be required curriculum for every single person in this country,” says Wang. “I think tech for good is genuinely getting out into communities and learning about people who aren't you, creating worldly perspectives that you ultimately can take into everything else that you do.”
Wang and fellow intern Lucy Sun, who is majoring in artificial intelligence and decision making, spent the summer supporting the development of the Muscogee Nation's first Pregnancy Risk Assessment Monitoring System (PRAMS) survey to capture maternal health data specific to Muscogee women. The project required completing literature reviews, analyzing datasets, and drafting survey questions, while considering issues of data sovereignty and governance structures specific to the Muscogee.
“It was this change of pace — 180 [degrees] from MIT, completely,” Wang reflects. At MIT, she says, course instructors routinely prepare students for big technical challenges, but there are fewer opportunities to “work with communities, [learn] how to think about the cultural and historical dimensions of the work, or how to consider the people who will be affected.”
Wang’s supervisor, epidemiologist Breanna McNaughton-Long, was effusive about Wang and Sun’s engagement. “They were instrumental. They did so much work that I don't think we would have been able to do as quickly,” she says. “And they brought this sense that we were doing something that mattered.”
Experiential learning at the confluence of humanities and engineering
Wang was one of 10 MIT undergraduates to participate in the PKG Center for Social Impact’s 2026 Code.Tulsa program. Now in its second year, Code.Tulsa is made possible by support from the Patrick J. McGovern Foundation and the George Kaiser Family Foundation.
Students live at the University of Tulsa for the summer. They intern with the Muscogee and Cherokee nations, as well as local nonprofits Black Tech Street and Urban Coders Guild, completing AI, data science, and other technical projects.
The PKG Center’s assistant dean for community-based programs, Vippy Yee, complements students’ professional experience with education on the historical and cultural significance of tech-based development in the Tulsa region from the perspective of local leaders.
“As with all PKG Center programming, our aim is to help students integrate an engineer’s approach to problem-solving with a humanist lens on the nature of social challenges, and by extension interventions,” says Alison Badgett, the PKG Center’s director.
“Getting to speak to people who were either very educated on the issues or have experienced them has been a massive help in reshaping the way that I think about social issues,” says Chenise Harper, an electrical engineering with computing major who interned with the Urban Coders Guild.
Harper puts this dynamic candidly: “I hated history, but I learned a lot about why it is useful for making social change and how to go about researching it. I now feel a lot more confident that I can make an impact.”
A student’s vision for increasing STEM access
Code.Tulsa was the brainchild of sophomore Jack Carson, an electrical engineering and computer science (EECS) student who approached the PKG Center with the idea for Code.Tulsa as an incoming first-year student. Carson, who is from Tulsa and a member of the Cherokee Nation, saw firsthand that rural Native students who could benefit greatly from STEM education were unlikely to have access to it. Carson proposed developing a weeklong STEM camp for members of federally recognized tribes held at the University of Tulsa, with he and Code.Tulsa interns serving as instructors.
Carson devised a nomination system to attract promising high school students, selecting 25 campers from 10 tribes out of 160 applications representing 25 Native nations.
To develop the curriculum, Carson enlisted Harvard University student Allie Zong, whom he had met at Campus Preview Weekend. The Tulsa Advanced Sciences Camp (TASC) offers intensive, interactive track time in AI engineering, DNA technology, physics, and chemistry and energy. This is complemented by philosophical workshops to help students think more ambitiously and deliberately about what they can and should achieve in the near and long term. As Zong explains, “We teach them not knowledge, but curiosity, and the skills to teach themselves."
The TASC experience “kind of propelled me to self-study calculus,” says Alyssa Theofanidis, a rising high school senior from Houston who is a citizen of the Cherokee Nation. Theofanidis participated in the camp’s first year, returning this summer as a teaching assistant. Like many TASC campers, Theofanidis is eager to use her developing STEM expertise to benefit her Native community.
TASC “got us to think 1,000 times more ambitiously about the impact we could have,” said another camper, who was inspired by guest speakers “like the nuclear fusion person at the top of their field,” referring to physicist Alexandra LeViness of MIT spinout Commonwealth Fusion Systems, who helped develop TASC’s chemistry and energy track. Campers were also inspired by “the different worldviews” of MIT interns. “I thought, maybe this is what MIT looks like,” said one camper, with several expressing the intent to apply to MIT as a result of the camp.
Cherokee Nation Principal Chief Chuck Hoskin Jr. also delivered remarks at TASC, encouraging students as future leaders to take a public interest in technology.
“Technology can be used for good, or it can be used for harm. Your generation has the opportunity to bend that arc toward something good,” Hoskin said. “It's a very special relationship that the Cherokee Nation has with MIT. As we reach out a hand in friendship, we have a hand reaching back. We are thankful for Cherokee citizen Jack Carson, a former secretary for the Cherokee Nation tribal youth council, for his leadership role in organizing this effort.”
Making a positive long-term social impact
Like TASC campers, Code.Tulsa interns came away from the experience motivated to make a positive impact. While most MIT students won’t go on to full-time professional roles traditionally associated with social impact, PKG Center programming like Code.Tulsa helps students recognize they can promote the public interest no matter their career. As Elvis Chipiro, a junior in computer science and engineering, reflected after interning with the Cherokee Nation, “Social impact is not separate from mainstream technology; rather, it is embedded in the choices engineers make every day … Ultimately, meaningful social change is not driven by technology alone, but by people willing to design systems with empathy, responsibility, and inclusion at the center.”
For others, Code.Tulsa helps them reconnect with a sense of public purpose. “Remembering that … I could use my MIT education to help others was a big reason I applied to MIT in the first place,” says Harper. “But I forgot my own mission in the stress of school. Code.Tulsa really re-opened my eyes to why I am here.”
A new technique could accelerate the development of RNA therapiesMIT chemical engineers found a way to rapidly produce lipid nanoparticles of varying sizes, which could make it easier to develop new vaccines and therapeutics.RNA vaccines and other nucleic acid therapeutics are typically packaged within fatty molecules known as lipid nanoparticles (LNPs). MIT researchers have now come up with a way to produce these particles much more quickly, and with more precise control over their size and shape.
This new process, which can be run automatically without any human intervention, could greatly speed up the development of new RNA and DNA therapeutics, the researchers say.
“This method can help you determine what are the parameters that will generate specific size and shape attributes, before you take those particles and see which one will perform best,” says Cedric Devos, an MIT postdoc and one of the lead authors of the study. “It could be a quite powerful development tool.”
Current methods for designing new lipid nanoparticles often require time-consuming trial-and-error experiments, with limited investigation of desired particle size and shape. Tuning the size and shape of LNPs can open the possibility of targeting different organs and tissues.
“The size and shape of LNPs could not be reliably controlled by any previous production method. The problem may appear simple at first glance, but in reality it requires a deep understanding of lipid nanoparticle assembly,” says Allan Myerson, a professor of the practice in MIT’s Department of Chemical Engineering and the senior author of the new study.
MIT postdocs Aniket Udepurkar and Peter Sagmeister are also lead authors of the paper, which appears today in ACS Nano.
More precise control
Vaccines based on mRNA work by delivering instructions to cells to produce a harmless version of a viral protein, which prompts the immune system to generate a response. However, if mRNA is injected on its own, it will be quickly broken down in the body.
“These are really a revolutionary type of therapeutics, but they need some kind of delivery vehicle to bring them to the right cells in the body,” Devos says.
For the mRNA Covid-19 vaccines and other mRNA therapeutics, scientists have used lipid nanoparticles for that packaging. LNPs usually consist of four components — an ionizable lipid, a phospholipid, cholesterol, and a lipid attached to a molecule of polyethylene glycol (PEG), which helps to stabilize the LNP.
To make the particles, two streams of fluid are mixed together at high speed. One consists of lipid molecules suspended in ethanol, and the other contains mRNA dissolved in an acidic buffer.
Those solutions aren’t mixed at equal flow rates, however. Instead, there is about three times more of the mRNA solution than the lipid solution. This unequal ratio helps promote the formation of lipid nanoparticles containing mRNA, but it doesn’t offer precise control over the size or shapes of the particles.
In a study published last year in ACS Nano, the MIT team showed that they could enable much better control of particle size by breaking the mixing process down into two steps.
In the first step, mRNA and lipids are mixed together at equal flow rates. Then, after a short delay, more of the buffer is added, which halts the growth of the particles. Longer delays produce larger particles.
“This gives you the ability to play around with the residence time, which is the time it takes between the first mixer and the second mixer. If you keep that residence time really long, it means your particles will grow a lot. If you keep it really short, you can keep them really small,” Devos says. “It gives you a lever over lipid nanoparticle manufacturing that wasn't available before.”
In that study, the researchers also showed that they could alter the shape of the particles. By changing the concentration of the buffer that they add in the second step, they were able to transform the particles from spheres to elongated particles that resemble avocados.
Both of these interventions — changing the delay residence time and changing the buffer composition — allow the researchers to control particle size and shape without otherwise altering the composition of the LNPs.
An automatic process
In the new ACS Nano paper, the researchers developed a way to automate the two-step mixing process. They also incorporated a commercially available dynamic light scattering device that can measure the sizes of the particles as they are formed.
The project also highlights the impact of MIT’s Undergraduate Research Opportunities Program (UROP). “Through this program, applied mathematics and computer science undergraduates Joy Ren, Sofiya Chubich, and Dylan Nguyen gained hands-on experience, learning how advanced software engineering can be integrated with chemical engineering to develop an automated platform for LNP process development,” Sagmeister says.
With this automated system, the researchers can specify a particle size, and the system will generate that size. It will also measure the resulting particles to make sure they’re the right size, and if not, adjust the delay time and other factors to steer them to the right size.
“The first paper really unlocked the new methodology to make lipid nanoparticles, to truly engineer them by size and shape,” Sagmeister says. “With the second study, we automate the whole process.”
The system can also produce particles of different shapes, but measuring those shapes has to be done outside of the automated system.
Using this approach, the researchers were able to investigate how changing the inputs to the system affects the size and shapes of the particles, on a much faster timescale than currently possible. The researchers then used the data they gathered from these experiments to train a machine-learning model that can predict the combination of factors that will generate a particular size or shape.
With this method, it could be much easier for developers of RNA therapeutics to generate different sizes of particles to test them for a particular application. Controlling the size of a lipid nanoparticle is critical because the particle’s size determines where in the body it is most likely to end up.
“If you make an LNP-based therapeutic with a target size of 150 nanometers, and one that is 70 nanometers, and everything else is the same, they will behave very differently,” Devos says.
The researchers have filed for a patent on their technology and are now working to commercialize it through a new company called BIZON Labs. Since receiving initial support through the Martin Trust Center for MIT Entrepreneurship’s Researcher 2 Entrepreneur (R2E) program, the team has also been accepted into MIT’s flagship accelerator program, delta v. The research was funded by the U.S. Food and Drug Administration and the Koch Institute Support (core) Grant from the National Cancer Institute. The work was carried out, in part, through the use of MIT.nano’s facilities.
Scattering neutrinos to probe the fundamental laws of the universeAs she became integral to an international particle physics experiment, PhD student Faith Reyes found confidence in herself as a scientist.Many people who are successful in STEM fields were lucky to have someone who turned them on to a topic and encouraged their interest. For Faith Reyes, that person was her high school physics teacher, Ms. Bolster.
Whereas Reyes had earlier studied math and science without seeing how those subjects could be applied outside the classroom, her teacher helped her connect those dots and experience the excitement of investigating the physical world. With Ms. Bolster’s help, Reyes started a physics club where students would gather before school and conduct experiments.
“I just sort of fell in love with physics then,” Reyes says. “And luckily, as I began to study it more and more, I found I landed exactly where I wanted to be.”
Reyes has carried that enthusiasm for physics into not only her research but her role as a personal tutor and teaching assistant at MIT, where she works to foster the same love of the subject in first- and second-year undergraduate students.
As an experimental particle physicist and sixth-year PhD student in the Formaggio Group in the Laboratory for Nuclear Science, Reyes studies neutrinos, elementary particles that have vanishingly little mass and rarely interact with other matter. Neutrinos are produced during radioactive decay, including the processes taking place inside nuclear reactors. Because they interact so infrequently, detecting them can be difficult. (We can’t feel them, but neutrinos from the sun are streaming through our bodies every minute.) Their unusual behavior makes them valuable to physicists seeking to understand what lies beyond the Standard Model, the framework that describes many of the fundamental particles and forces in nature.
“The Standard Model is extremely accurate and describes most of everything that we see,” Reyes says. “But it’s not complete.”
Reyes is a member of the Ricochet neutrino experiment, an international collaboration studying neutrinos produced by a nuclear reactor at the Institut Laue-Langevin in Grenoble, France. The experiment seeks to observe coherent elastic neutrino-nucleus scattering, a low-energy interaction in which a neutrino scatters off an atomic nucleus.
Through Ricochet, scientists aim to investigate some properties of these elusive particles, and contribute to, as Reyes puts it, “just fundamentally understanding the world in which we live.”
When looking back at her time in graduate school, Reyes’ path has not always followed the plan she initially envisioned.
When she joined Ricochet, she expected to work on a particular project located at MIT. But a few years into her PhD, it was clear that the project would not be ready within her timeline. Reyes instead shifted her focus to work taking place in France, where she began learning the technical details of the experiment’s detectors.
Her first visit lasted three months. At the time, Ricochet had two detectors, and Reyes spent much of her time performing the routine work required to understand how they operated.
As the experiment expanded to nine detectors and eventually 18, the amount of work required to manage the system grew substantially. Reyes and a colleague recognized that many of the repetitive tasks could be automated.
Together, they developed a software framework that could perform much of the low-level analysis and detector monitoring that Reyes had initially carried out manually.
The project became an important part of her development as a physicist. By working closely with the detectors and helping build tools to manage them, Reyes gained a detailed understanding of the experiment’s operations.
“It’s sort of like you’re building your own stuff to replace yourself,” she says. “Which is nice in a way because you can save yourself a lot of time.”
The opportunity was both validating and humbling. As a graduate student, she had moved from learning the basics of the experiment to helping guide the work of other scientists.
“It felt like my collaborators trusted me, and I had something of value to give to the collaboration,” Reyes says.
The people she has met through MIT and the Ricochet collaboration have been among the most rewarding parts of her graduate experience. Students, mentors, and collaborators have helped her think critically and become a better physicist, she says.
Her increasing leadership responsibilities have also changed how she approaches research.
Earlier in her academic career, Reyes says, she was more comfortable being told what to do than proposing her own scientific ideas. Over time, leading projects and coordinating groups pushed her to become more confident in her judgment.
“I think I was sometimes not really standing up for myself,” she says. “But now I feel more confident in my position and my prowess as a physicist.”
That confidence has become one of the most important lessons of her PhD.
After completing her doctorate, Reyes hopes to continue conducting research. She is considering a postdoctoral position, which would allow her to continue working in physics at another institution.
Her time in France has also influenced her vision of the future. Reyes spent nine months there through the Chateaubriand Fellowship, following two earlier three-month visits. While the latest trip was primarily focused on research, working in the same office as her collaborators made it easier to coordinate across time zones and strengthened her connection to the experiment. She also grew fond of the country’s culture and work-life balance and would even consider living there.
“I fell in love with France and the people,” she says. “And also, the work culture.”
Outside the lab, Reyes enjoys playing video games and crocheting, a hobby she picked up during her time in France. She often crochets while watching movies or television, appreciating the opportunity to work with her hands while thinking about other things.
For a physicist whose work involves investigating some of the universe’s smallest and most elusive particles, the hobby offers a different kind of satisfaction: creating something tangible.
As Reyes moves toward the next stage of her career, she hopes to continue pursuing the questions that first drew her to physics. Her research may help reveal what lies beyond the Standard Model, but her experience at MIT has also shown her how much science depends on collaboration, adaptability, and the confidence to lead.
“I’ve learned a lot of lessons,” Reyes says. “Especially about wrangling people.”
Estimating suicide risk from textA new language-processing tool could help identify the highest-risk individuals from natural language, enabling swifter interventions.When people reach out during a mental health crisis, a top priority for counselors is identifying those with a high risk of suicide. The distressed person’s language holds critical clues, and a new tool developed by scientists at MIT’s McGovern Institute for Brain Research is designed to pick up on and rapidly evaluate those signals.
The language-processing tool was developed by Daniel Low, a former graduate student in Senior Research Scientist Satra Ghosh’s Senseable Intelligence Group who is now a research scientist at the Child Mind Institute, where he leads its AI, Risk, and Contemplative Science Lab, as well as a visiting scholar at Harvard University. It uses a custom-built list of words and phrases linked to 49 suicide risk factors, searching text for these and using them to estimate an individual’s risk.
Ghosh, Low, and colleagues report today in the Journal of Psychopathology and Clinical Science that their tool accurately predicts suicide risk from text conversations with crisis counselors. It is already helping to clarify which suicide risk factors matter most in times of crisis. With more validation, it could help with risk assessment in clinical settings and crisis-support situations.
Identifying key risk factors
Suicide attempts are notoriously difficult to predict. Dozens of risk factors have been linked to suicide, and even trained clinicians struggle to identify who will make an attempt among those who have some form of suicidal ideation. Among the factors that can make suicidal thoughts and behaviors more likely are certain psychiatric symptoms and disorders, like depression, borderline personality disorder, and post-traumatic stress disorder, as well as environmental and social stressors, like poverty, incarceration, discrimination, and loneliness.
“You see all these 50 risk factors, and they're all interacting in ways we don't really understand,” Low says. “Many different pathways could lead to someone feeling they want to escape their internal pain,” he says — and it’s challenging to know whose path will lead to a suicide attempt or death.
Ghosh and Low wanted to understand which risk factors counselors and clinicians should most look out for during a mental health crisis. To do that, they collaborated with the Crisis Text Line, whose trained volunteers provide confidential text-based support to people in distress.
Crisis Text Line, a global mental health nonprofit that provides free, 24/7, confidential mental health support for people in need, provided specialized training and controlled access to this restricted dataset. The researchers analyzed de-identified texts from approximately 16,000 conversations with Crisis Text Line’s volunteer crisis counselors. Based on Crisis Text Line’s assessments, those conversations were grouped into three different risk levels: non-suicidal, suicidal ideation without imminent risk, and imminent risk. It was this imminent risk group — those with a plan for suicide, or who have an intent to die within the next 48 hours — that the researchers most wanted to understand.
“We wanted to know what type of symptoms predict the highest suicide risk,” Low says. This question has been studied before, he says — but typically through epidemiological surveys that ask a person to recall their symptoms and experiences, often after their mental health crisis has passed. In contrast, he says, “Crisis Text Line gives us an opportunity to assess many different symptoms and potential risk factors as people are having the crises.”
Reading between the lines
Before analyzing the crisis line texts, the research team built a suicide-risk lexicon. They turned to artificial intelligence to generate a preliminary list of words and phrases tied to established suicide risk factors, including factors associated with suicidal ideation, suicide attempt, and suicide death. Then they manually reviewed and curated that list. Their final lexicon includes about 60 words or phrases for each of 49 risk factors, with the relevance of each one confirmed by expert clinicians.
Then they trained a machine learning model to search the crisis conversations for words and phrases in their lexicon and use these to predict suicide risk. Because the lexicon links each word or phrase to a specific risk factor, they could use these data to determine which risk factors are most closely tied to imminent risk among people in crisis.
What they found was consistent with patterns found in previous research, although not always intuitive. For example, depression is a well-known risk factor for suicidal ideation, but their model found that mentions of lethal means and substance use were more likely to be expressed by the highest-risk group than depressed mood or fatigue. Expressions of active suicidal ideation and self-injury were also strong predictors. Intermediate predictors included anxiety, post-traumatic stress disorder, and emotional pain.
The predictive model assigns a weight to each risk factor based on its contribution to risk. For example, mentions of lethal means for suicide, like “cut” or “pills,” are weighed heavily, whereas terms related to hopelessness, like “don’t know what to do” or “hopeless,” contribute to a lesser degree. After training their model, the team found they could use it to accurately predict risk severity in new conversations the model had not previously seen.
One limitation of lexicons, the researchers note, is that they do not consider the context of terms, and they can miss terms that are similar to those in the lexicon, but not explicitly included. Large language models have reasoning abilities, and Low and colleagues have developed ways of using large language models to detect suicide risk in other projects. However, they say they often use their lexicon in parallel to guarantee flagging certain terms, as well as to maintain data privacy.
Low stresses that while the team used the power of a large language model to develop its lexicon, its prediction model is a simpler, “lightweight” model. Unlike large language models, which require massive computational power, it can be run easily on a personal computer, reducing both cost and privacy concerns. Just as importantly, it is interpretable: Rather than merely generating a risk estimate like some deep learning models can do more effectively, it tells users how it got there. Words of concern can be flagged so users understand the basis for each assessment and act on that information. They are working on similar explainability approaches with large language models.
That’s critical, because the stakes are so high. “This is such a complex space that having a human in the loop is, I think, going to be critical for a long, long time,” says Ghosh, who is the director of the Open Data in Neuroscience Initiative at the McGovern Institute. Likewise, the researchers add that any predictive model must be thoroughly validated before clinical use, and might need to be continually refined to keep up with changes in language use or target populations.
Because a reliable lexicon opens doors to new ways of understanding mental health, Ghosh and Low are widely sharing not just their suicide risk lexicon, but also the software package they developed to build it. Researchers can use that tool to efficiently build lexicons for other mental health conditions. Meanwhile, Low says, the suicide risk lexicon is already being used to explore how text data from a variety of sources, from social media to electronic health records, might help researchers and clinicians better estimate risk.
Biologists identify a cellular pathway that allows colorectal cancer to metastasizeThey also found that obesity may put patients at higher risk for activation of the pathway. Drugs that block the pathway may help prevent metastasis.Most colon cancer deaths are caused by the spread of tumor cells beyond the colon, usually to the liver. In a new study, MIT biologists identified a cellular pathway necessary for colorectal cancer metastasis.
The pathway they identified, controlled by a protein known as YAP1, is normally involved in tissue repair. When activated in cancer cells, it promotes cell proliferation and migration. The researchers also found that a high-fat diet is more likely to turn on this pathway, through the production of fatty molecules called ceramides.
Drugs that block ceramide production could offer a new way to help prevent metastasis in patients diagnosed with colon cancer, the researchers say.
“We’ve found a pathway that we think is druggable. If we shut down the enzymes that make ceramides, tumor cells can’t switch on this regenerative program, and they largely fail to seed metastases in the liver,” says Omer Yilmaz, director of the MIT Stem Cell Initiative, a professor of biology at MIT and a member of MIT’s Koch Institute for Integrative Cancer Research. He is also a gastrointestinal pathologist and director of translational research in pathology at Beth Israel Deaconess Medical Center.
Yilmaz, Nilay Sethi, an associate professor of medicine at Harvard Medical School and Dana Farber Cancer Institute, and Alpaslan Tasdogan, head of the Institute for Tumor Metabolism and a professor in the Department of Dermatology at University Hospital Essen and the German Cancer Consortium (DKTK), are the senior authors of the study, which appears today in Science. MIT postdocs Swagata Goswami, Qiming Zhang, and Abdullah Burak Yildiz are the paper’s lead authors.
A hijacked pathway
In the United States, colon cancer is usually diagnosed at stage 2 or 3 — before the cancer has spread. However, even after successful surgery, up to a third of these patients will relapse with metastatic disease.
While scientists have identified many genetic mutations that drive the development of colon cancer, it’s unknown exactly what prompts them to spread beyond the colon.
“Many studies have looked for a genetic driver of metastasis and come up empty,” Yilmaz says. “There isn’t a defining mutational signature that separates metastatic cells from the primary tumor, which points to metastasis being driven largely by changes in which genes are switched on and off, rather than by new mutations.”
In this study, the researchers sought to identify epigenetic programs that enable colon cancer cells to metastasize. Using tumor organoids from mouse models of several types of colon cancer and from patients with colorectal cancer, they found that metastatic cells shared one key feature: activation of the YAP1 program.
YAP1 is a protein that works with partner factors to switch on genes related to development, stem cell maintenance, and regeneration. In normal tissue, it is active during fetal development, and after injury, to promote healing.
In the gut, that repair response runs through a rare, fetal-like cell type, which normally appears only briefly to rebuild the intestinal lining after damage. YAP1 has been linked to cancer for years, but the new work shows that diet-derived lipids push tumor cells into this specific regenerative state — and that the state itself is what licenses metastasis.
“The regenerative program that we described is generally observed in the gut when there is severe injury or infection and the gut needs to regenerate. We see the tumor cells hijack this program to drive metastatic progression,” Goswami says.
Activation of this set of genes helps cancer cells to break free from the original tumor site and spread to other locations in the body. For colon cancer, the most common site of metastasis is the liver, followed by the lungs.
In mouse studies, the researchers also found that cancer cells in animals fed a high-fat diet turned on YAP1 to a greater extent than mice fed a healthy diet. A high-fat diet, the researchers found, triggers activation of enzymes that produce ceramides, a type of lipid. Ceramides then release the molecular brake that normally keeps YAP1 inactive, allowing it to move into the nucleus and switch on its target genes.
Preventing metastasis
The researchers showed that genetically targeting YAP1, or the genes involved in ceramide production, markedly reduced the spread of colon cancer to the liver in mice.
To determine if YAP1 is also involved in metastasis in humans, the researchers analyzed RNA sequencing data from patients with colorectal cancer. They found that YAP1 was more active in metastatic cancer cells, and that patients with higher body mass index (BMI) showed higher expression of the genes activated by YAP1 than normal-weight patients. Patients with higher levels of those genes also had lower survival rates.
“We don’t think that the YAP1 program is specific to obesity. It’s just that it becomes accentuated in obesity, and that may account for why obesity is known to drive the progression of colorectal cancer,” Yilmaz says.
They now plan to develop drugs that inhibit two of the enzymes involved in ceramide production, DEGS1 and DEGS2, in hopes that such drugs could help prevent colon cancer metastasis.
The researchers caution that the findings do not yet translate into dietary advice for patients who have already been diagnosed, and that any drug targeting ceramide synthesis will have to clear a high bar for selectivity, since these lipids are also essential in healthy tissues.
The research was funded by the National Institutes of Health/National Cancer Institute, the MIT Stem Cell Initiative, a Koch Institute Frontier grant, and the NRW Junior Research Program.
New cell-collection device could improve early cancer detectionMIT researchers developed a handheld system that gently collects living cells from patient samples to aid cancer testing and development of personalized medicines.One of the main reasons that ovarian cancer is among the deadliest forms of cancer is timing: When doctors catch it early, the five-year survival rate can be north of 90 percent. But when doctors catch it late, in stages 3 or 4, five-year survival is less than half that.
About 20 years ago, researchers studying ovarian cancer discovered that many cases of high-grade serous ovarian cancer, the most common type, originate in the fallopian tubes. Detecting the disease there remains challenging, in part because its precursor lesions can be microscopic and difficult to sample.
Now researchers in the group of MIT Professor Kripa Varanasi, working with colleagues at MIT and Johns Hopkins University, have developed a handheld device capable of gently collecting living cells from specific locations to test for ovarian and many other types of cancer. The researchers believe the technique could one day be used to catch cancers earlier and more effectively. It could also be used to create treatments based on individual patient samples.
In a study describing the system in the journal Device, the researchers showed their system enables targeted sampling of newly excised tissue, and they used it to recover living cells for cultivation and testing. The device holds a small microfluidic channel against the tissue and uses a syringe to drive fluid through the channel, applying a force parallel to the tissue surface to gently detach living cells from tiny sections of tissue.
“We wanted to collect living cells from specific regions of the fallopian tube while leaving the surrounding tissue intact,” says Varanasi, senior author of the study and the Maher A. Elmasri Professor of Mechanical Engineering. “Once we have these living cells, there are many things we can do with them. We can use them for diagnostics, grow them into organoids, and build living models of disease. Ultimately, this could allow us to test how an individual patient’s cells respond to different treatments and help us develop more personalized medicines.”
Joining Varanasi on the paper are co-first authors Domitille Avalle SM ’25, MIT postdoc Bert Vandereydt PhD ’26, and Sean Parks ’20, SM ’24. The other authors are MIT PhD candidate Huaiyao Peng; Rebecca Stone, the Johns Hopkins University School of Medicine Stoddard and O’Neil Professor in Gynecologic Oncology; and Angela Belcher, MIT’s James Mason Crafts Professor and a professor of biological engineering and of materials science and engineering.
Living cells for ovarian cancer research
The discovery that many high-grade serous ovarian cancers originate in the fallopian tubes has opened up new prevention options for women at increased risk, who can have their fallopian tubes removed after childbearing years, largely preserving normal hormone production.
Stone, a gynecologic oncologist at Johns Hopkins University, has long advocated for this procedure for certain women at increased risk of ovarian cancer. Belcher introduced Stone to Varanasi, and the three, together with other collaborators, received funding from Break Through Cancer, a foundation that brings together interdisciplinary teams to tackle some of the most challenging problems in cancer. Their project focuses on developing new approaches for the early detection of ovarian cancer, with the cell-collection technology forming one part of that broader effort.
The researchers began by asking whether they could collect living cells from specific regions of removed fallopian tubes to study the disease’s earliest stages.
"The idea was to see if we could find early signals from precancerous regions of concern,” Varanasi recalls.
The process traditionally involves placing surgically removed fallopian tubes in a chemical preservative and cutting the tissue into sections. The preservative maintains tissue structure, but the cells are no longer alive and cannot be grown in culture. A pathologist then looks for cancerous or precancerous regions in thin sections of the tissue under a microscope.
“It’s very time-consuming and destructive to the cells,” Varanasi says. “We wanted to bring new capabilities to pathology, so we can not only see what these cells look like, but also collect them alive and study how they behave.”
The MIT researchers saw the process firsthand while visiting surgeons in the operating room at Johns Hopkins.
“It inspired us,” Varanasi says. “We do a lot of work on fluid-surface interfaces in my lab, and we realized we could use a fluid instead of a scalpel or brush, because when you flow a fluid it applies shear stress at the interface. We thought it could work because we heard from surgeons that cells in some locations were loose and would come off during routine washing and other procedures.”
“This is exactly the kind of problem that benefits from bringing clinicians and engineers together,” Stone says. “We understand the clinical need, while the MIT team brings a very different perspective from fluid mechanics and engineering. That combination allowed us to approach the problem in a new way.”
The researchers’ new approach uses a 3D-printed microfluidic device that forms a vacuum seal with the tissue. The device confines liquid flow to a small region, where the flowing liquid creates shear stress that gently detaches living cells.
“We came up with this device where one syringe creates a vacuum that holds it against the tissue, and a second syringe pushes liquid through it,” Vandereydt says. “The vacuum creates a seal, so nothing leaks, and then we locally apply what is basically a microfluidic chip on the tissue that gently shears the cells off.”
The researchers showed they could tune the shear stress applied to the tissue and compared their approach to other cell collection workflows. They found the cells collected using their technique remained viable and grew in culture much more readily than cells detached using conventional approaches.
Finally, the researchers tested their device on fresh human fallopian tube samples, which required them to be on call for sample shipments from their collaborators at Johns Hopkins. After experiments, the samples were shipped back for conventional pathology.
“The samples could come at any time. Sometimes, we’d get an email from our collaborators at 11 p.m. saying ‘There are two fallopian tubes coming tomorrow,’” Vandereydt says. “We were able to collect living cells from those fallopian tubes and turn those into organoids, which is important for testing, disease modeling, and eventually developing personalized treatments.”
“We are developing optical approaches to identify suspicious regions of tissue, and this technology could allow us to collect living cells from exactly those locations,” Belcher says. “Being able to first see where the disease may be emerging and then collect those cells for further study could be very powerful.”
From device to diagnostic
The researchers tested the device on different types of cells and found the approach can be tuned to collect cells of all types by applying different levels of shear stress.
“It’s agnostic to the disease,” Vandereydt says. “There are very loosely adherent prostate cancer cells that detach at 1 pascal [of stress], but if you look at bone cancer cells, only a few cells detach under as high as 5 pascals of stress.”
The researchers plan for the early use of their device to involve tissue that has already been removed from the body, as that offers an easier pathway to regulatory approval. But they would also like to see their device used to swab samples inside of patients for easier testing and earlier cancer detection.
“What is exciting about this technology is the ability to collect living cells from a specific area while preserving the tissue for pathology,” Stone says. “In the future, one could imagine integrating it into routine histopathology workflows, creating a powerful new way to study carcinogenesis and fundamental biology directly from human tissue.”
Varanasi credits Break Through Cancer for enabling the project.
“Break Through Cancer brought together people working on not only ovarian cancer but also on pancreatic cancer, brain cancer, leukemia, and other cancers,” Varanasi says. “What we heard again and again is how valuable it would be to have better ways to obtain living cells from specific regions of tissue.”
The researchers hope that by making it possible to collect living cells from precise locations without removing or destroying the surrounding tissue, their approach could eventually help researchers and clinicians identify disease earlier and better understand how it develops.
“If this work can ultimately help women by enabling earlier detection of ovarian cancer, I would find that incredibly fulfilling,” Varanasi says. “That is really what motivates us — taking the science and engineering we develop in the lab and using it to make a difference in people’s lives.”
The work was supported by the Break Through Cancer Foundation.
The promise and peril of using visual AI to study citiesIn their new book, “How AI Sees the City,” the leaders of MIT’s Senseable City Lab examine the technology’s implications for researching urban life.A few months ago, researchers from the MIT Senseable City Lab published a study about pollution in New York City featuring some new methods. For instance: With machine learning, they identified the types of vehicles appearing in 331 traffic cameras in the city, and estimated the emissions coming from each automobile. Given enough cameras, these visual artificial intelligence techniques could monitor emissions with an unprecedented combination of precision and scale.
For that matter, visual AI today can address all kinds of questions for urban planners. Why exactly is traffic snarling? What are the most dangerous aspects of different intersections? Which parts of plazas or parks attract the most people?
Across cities, more images means more data, more insight — and more concerns about privacy and fairness.
“We can treat these digital images as data and quantify features of the city,” says Fábio Duarte, an MIT researcher and co-author of a new book about visual AI and urban studies. “With computer vision techniques, each image is a dataset.” Still, he adds, “We have to be careful about it.”
And while urbanists have long used visual analysis to inform their thinking, now it’s possible to an unprecedented extent.
“Everybody has been observing the urban environment and trying to get some insight,” says Martina Mazzarello, an MIT scholar and a co-author of the new book. “But what if we can do that at a large scale and get some insight everywhere?”
The scholars explore these topics in “How AI Sees the City: Urban Visual Intelligence,” published this month by Routledge. The authors are Duarte, a principal research scientist and associate director of the MIT Senseable City Lab; Mazzarello, a research scientist and lead of MIT Senseable City Lab global initiatives; Carlo Ratti, a professor of the practice and founder and director of the MIT Senseable City Lab; and Fan Zhang, an assistant professor at the Institute of Remote Sensing and GIS at Peking University.
“Great urbanists such as Kevin Lynch and Willian H. Whyte showed us the extraordinary value of ‘looking’ at the city,” Ratti says, referring to two prominent thinkers about city dynamics whose work is described in the book. “Today, visual AI gives us new ways to build on that tradition — allowing us to observe cities at a scale and with a level of detail that was previously impossible.”
New tool, long tradition
“How AI Sees the City” stems from the work of the MIT Senseable City Lab, founded in 2004, which uses data to better understand urban dynamics. As the authors discuss in the book, there is a long history of visual representations that shape the way we think about cities, from Romans building marble maps to the introduction of photography — which produced influential urban images about things like Hausmann’s reshaping of Paris or the crowding of tenements in New York City’s Lower East Side during the 19th century.
More recently, some scholars have used visual studies to better understand city form, including Lynch, a former MIT professor whose 1960 book, “The Image of the City,” influenced many scholars. Whyte, a sociologist famous for his book “The Organization Man,” then became an urbanist closely examining public spaces.
By explicitly placing AI in a continuum with these visual urban studies, the authors are making a point: Powerful as it might be, we can still think of AI primarily as a tool serving human purposes, as we seek to design and refine urban form.
“Kevin Lynch at MIT was only using paper and pen,” Duarte says. “We can now scale up what he was doing, with visual AI, while also looking at many different dimension of cities.”
There are extensive possibilities for applying visual AI to urban planning, ranging from emissions to traffic flow, safety, better imagery of street-level activity and sidewalks, and much more. The book also examines, for instance, urban greenery. While satellite imagery can show us how much tree cover and green spaces cities have, near-ubiquitous images from phones and other sources can also reveal to what extent people glimpse greenery in everyday life, a factor in reported wellness.
“The real promise of visual AI is not simply that computers can look at millions of images,” Zhang says. “It is that we can connect what is visible in those images — streets, buildings, greenery, traffic, public space — with larger questions about how cities function and how people experience them.”
Better image recognition by AI even extends to urban interiors. By using images from 400,000 AirBnB listings across the world, one recent Senseable City study shows that, contrary to some claims, interior design styles are not becoming globally more homogeneous, but reflect significant geographic differences.
“No matter what it is, we can learn from what we can see and then use it as urban designers, planners, policymakers, and citizens,” Mazzarello says. “It can be our eyes, or cameras with computers, but in the end it’s the same methodology, and now we are trying to optimize the ways we can use these tools.”
Promise and pitfalls
If the promise of visual AI for urban studies is vast, the pitfalls are concerning. In “How AI Sees the City,” the authors outline multiple potential problems with the technology, including the intrusiveness of widespread visual surveillance and the potential for bias being reinforced through AI systems.
The installation of ubiquitous cameras can quickly raise concerns about surveillance. London, an early adopter of CCTV, has about 210 cameras per square mile. But eight of the world’s 10 most camera-heavy cities are in China; Shanghai has over 5,000 cameras per square mile. Such surveillance practices have raised controversy in other parts of the world, with debate over the uses of traffic cameras bubbling up in the U.S. this year as well.
In evaluating the potential safety gains from intensive video recording, the authors write, “the benefits must be weighed against the significant erosion of personal freedom and the potential for abuse inherent in a system of constant monitoring.”
Meanwhile, AI systems can reinforce social biases as well, leading to the production of data that reinforce prior perceptions as much as underlying realities — about people, neighborhoods, and whole cities. If AI models are trained on majority population groups, they may not evaluate minority groups the same way.
“We need to teach AI to see, and depending on how you teach it, it will see what what is embedded in the culture,” Duarte says. “AI is not neutral.”
Still, as Mazzarello adds, “our eyes are not neutral, either. Every tool has to be guided in the right way, and trained in the best way.”
Other scholars have praised “How AI Sees the City.” Michael Batty of University College London has called it a “fascinating book” that “shows how we are beginning to interpret the world of urban design, suggesting ways in which we might improve design using urban analytics, AI and large language models.”
Ultimately, though the authors think there is great value in deploying visual AI to learn more about our cities, how they function, and how they might be improved. With caution and independent thinking, progress is possible. Or, as they conclude in the book, “We should explore this wisely, critically, and creatively.”
MIT welcomes David Siegel SM ’86, PhD ’91 as its next Innovation FellowComputer scientist, entrepreneur, and philanthropist will collaborate with the MIT Schwarzman College of Computing to advance AI and scientific discovery.David Siegel SM ’86, PhD ’91, a computer scientist, entrepreneur, and philanthropist, will serve as the next MIT Innovation Fellow during the 2026-27 academic year. Working with the MIT Schwarzman College of Computing, Siegel will explore how artificial intelligence can accelerate scientific discovery at the Institute and beyond.
“From the MIT Schwarzman College of Computing to the MIT Siegel Family Quest for Intelligence, David has been a superb thought partner for me and other Institute leaders on a range of very significant initiatives, so we're delighted to have him join us now as an MIT Innovation Fellow,” says MIT President Sally Kornbluth. “Our community has long benefited from David's exceptional technical insight, entrepreneurial experience, instinct for connecting people, and infectious love for MIT. We look forward to working with him now as he helps us identify new opportunities at the intersection of AI and scientific discovery.”
“MIT has played a foundational role in shaping how I view technology’s potential to address complex challenges,” says Siegel. “I’m thrilled to return to campus as an Innovation Fellow to collaborate with brilliant students, researchers, and faculty at a pivotal juncture in how technology shapes our world.”
A long-standing connection to MIT
Siegel’s relationship with MIT began during his graduate studies, where he earned a master’s degree in 1986 and PhD in 1991, after earning his bachelor’s degree in electrical engineering and computer science from Princeton University in 1983. Immersed in the field during a foundational era for computer science, he worked at the MIT Artificial Intelligence Lab (now the Computer Science and Artificial Intelligence Laboratory) in Professor Tomás Lozano-Pérez’s research group on human-machine interaction, contributing to the development of a pioneering humanlike robotic hand.
Siegel has remained deeply involved with the Institute in the years since. He is a life member of the MIT Corporation, previously served on its Executive Committee, and co-chairs the External Advisory Committee for the MIT Schwarzman College of Computing. Additionally, Siegel was an early champion of the MIT Quest for Intelligence, an Institute-wide initiative studying intelligence in brains and machines, recently renamed the MIT Siegel Family Quest for Intelligence.
Entrepreneurship, philanthropy, and AI leadership
After completing his PhD, Siegel founded several early internet ventures before co-founding Two Sigma in 2001. A leading global investment firm, Two Sigma approaches investing through a data science and engineering lens, echoing Siegel’s experience in the MIT AI Lab. With the scientific method embedded in its culture, the firm uses artificial intelligence, machine learning, and advanced quantitative modeling. Siegel retired from day-to-day management of Two Sigma in 2024; however, he remains co-chair.
Currently, Siegel’s work spans several fields, with a strong emphasis on science, technology, and philanthropy. Through the Siegel Family Endowment, a philanthropic foundation that he established in 2011, Siegel supports leaders, researchers, and organizations that are examining how technological change affects society and how to guide that shift for the public good. The endowment backs organizations such as the Scratch Foundation, Center on Rural Innovation, Khan Academy, Pursuit, and The Aspen Institute.
Recognizing the critical resource gap between academic research labs and frontier AI, Siegel founded the nonprofit Open Athena in 2024. Open Athena equips academic research labs with elite AI talent, data engineering expertise, and computational resources to enable groundbreaking discoveries at scale. The organization is also developing Marin, a 535-billion-parameter foundation model built entirely in public. By sharing every dataset and experiment in real-time, Marin ensures that the science of frontier AI remains a shared public asset for researchers and innovators worldwide. Open Athena works with leading global institutions including MIT and is funded by philanthropic partners including Bloomberg Philanthropies, Google, The Huang Foundation, and Schmidt Sciences.
Siegel actively serves on several governance and advisory boards. He is vice-chair of the Scratch Foundation, which he co-founded in 2013 with MIT Professor Mitch Resnick, a member of the Cornell Tech Council, and a board member of organizations such as Re:Build Manufacturing, Khan Academy, and NYC FIRST Robotics. In 2025, Siegel was appointed to the U.S. Department of Energy’s Office of Science Advisory Committee, providing counsel on complex scientific and technical issues impacting federal scientific research programs.
Outside of philanthropy, Siegel remains actively engaged in the global AI ecosystem as an investor, hands-on advisor, and thought leader. Through his family office Shinrai Management, he focuses on supporting entrepreneurs and investing in high-growth startups, including several founded by MIT students and alumni.
Siegel’s debut book, “When Machines Act: The Promise and Peril of Navigating Our Agentic AI Future,” co-authored with Yale University’s Jeffrey Sonnenfeld and Stephen Henriques, will be published by MIT Press next March, coinciding with his residency as an MIT Innovation Fellow. Drawing on interviews with top tech leaders and off-the-record discussions with over 300 CEOs, the book provides a practical roadmap for autonomous AI, outlining where to deploy it, how to govern it, and which rules truly matter.
“David’s ties to MIT date back to his doctoral research in the AI Lab and have deepened through his many contributions to the Institute, including his significant involvement with the Quest for Intelligence and the MIT Schwarzman College of Computing,” says MIT Provost Anantha Chandrakasan. “His long-standing commitment to MIT, together with his vision for the future of AI and science, makes him an especially fitting Innovation Fellow. We look forward to the contributions he will make and the connections his work will foster across campus."
“For the MIT Schwarzman College of Computing, David’s fellowship is a chance to build on an already strong connection and explore how AI can expand the frontiers of science. Having known David since we were both graduate students at MIT, I’m deeply familiar with his ability to advance AI and its application in various fields,” says Dan Huttenlocher, dean of the MIT Schwarzman College of Computing and the Panasonic Professor of Electrical Engineering and Computer Science. “He understands both the college’s aspirations and the challenges ahead, and his perspective will help us identify concrete paths for research, education, and broader engagement. I look forward to working with him over the coming year.”
A year in residence
MIT Innovation Fellows typically spend a year or more in residence at the Institute. They draw on their experience, expertise, and professional networks to engage with faculty and students, participate in public events, and provide strategic counsel to MIT leaders.
The program has brought luminaries from industry and government to MIT. Most recently, Brian Deese, former White House National Economic Council director, served as an Innovation Fellow. Other fellows have included Virginia M. “Ginny” Rometty, former chair, president, and CEO of IBM; Eric Schmidt, former executive chair of Google’s parent company, Alphabet; the late Ash Carter, former U.S. secretary of defense; and former Massachusetts Governor Deval Patrick.
As an Innovation Fellow, Siegel will help guide the Institute’s focus on leveraging artificial intelligence to support scientific discovery, working closely with the MIT Schwarzman College of Computing and departments across the college to help extend their impact beyond MIT.
“Using AI to accelerate scientific discovery is the ultimate engineering challenge. There is simply no better launchpad in the world for that work than MIT,” says Siegel.
FUNdaMENTALs of precision designPrecision, repeatability, and fun are the focus in mechanical engineering course 2.70 (Fundamentals of Precision Product Design).Repeatability in engineering product design ensures that a manufacturing process performs the same way every time and allows for a working prototype to be transformed into a reliable, safe, consistent, and cost-effective mass-market product. For students in class 2.70 (Fundamentals of Precision Product Design), precision and repeatability are the name of the game.
“[As an engineer], you have an extra responsibility to overlook nothing,” says course instructor Alex Slocum, the Walter M. and A. Hazel May Professor of Mechanical Engineering. “If you miss something, someone could be hurt or die.”
Slocum’s message is serious, but his approach to teaching the material is famously fun — in fact, he prefers the spelling “FUNdaMENTALs” for the first word of the class name. His mother, Mariana Polonsky Slocum, was a mathematics student at MIT. “She taught me, physics doesn't care about your feelings,” he says. “I want [students] to understand that we are governed by the laws of physics, and that is a catalyst for creativity, not a hindrance. It is a hindrance if you forget that.”
Through the course, students learn deterministic design, selection, and assembly of machine elements to create and manufacture robust precision machines, instruments, and systems. They also apply Slocum’s “Functional Requirements, Ergonomics and Environment, Design Parameters, Analysis, References, Risks, Countermeasures” (FRED PARRC, pronounced like “Fred Park”) model, and engage in peer review and evaluation.
“You get a lot of time working on problems that just pop up in engineering. To me, it felt very [representative] of the grad work that I was doing,” says Mariia Smyk, a graduate student in mechanical engineering.
Some students may describe the course as “creative chaos,” but tend to agree that their learning experience is one that drives home the fundamentals.
“It definitely made me more confident knowing that I can look at what I'm designing and be very deliberate in taking steps toward mitigating the risks that anyone would face when they use a product,” says graduate student Adian Salazar. “I feel like I've been able to apply all those really fundamental concepts that I learned in the more theory-heavy classes to real-world machines.”
How the brain keeps its options straight at decision timeMaking a decision requires juggling a set of options without getting them confused or losing track of them. A new MIT study shows how neurons encode information to maximize clarity throughout the process.A new study by neuroscientists in The Picower Institute for Learning and Memory at MIT shows how the brain encodes information throughout the decision-making process to keep options clearly in mind and to ensure that chosen and unchosen options are remembered.
The key, the researchers show in the journal iScience, is that the brain convenes ensembles to produce coordinated patterns of electrical activity that distinctly represent and sort options, both during consideration and after choice.
“It keeps different neural ensembles, different thoughts, distinct from one another, preventing interference between them,” says senior author Earl K. Miller, Picower Professor in MIT’s Department of Brain and Cognitive Sciences.
Lead author Huidi Li, a graduate student in Miller’s lab, says the study results show how the brain responds dynamically to meet the challenge of decision-making.
“The brain doesn’t just hold information statically,” Li says. “Throughout the decision process, the brain flexibly reorganizes information representation to meet the changing task demands.”
Decisions decoded
To conduct the study, Li, Miller, and their team trained two animals to play a game in which they had to look in the direction of one of two indicated targets on a screen, based on which target was assigned the higher reward value. Importantly, the two options were presented and their values were assigned in sequence — first one target, then its value, then the other target and then its value. That way, the brain had to juggle multiple representations for each target — for instance, the order of presentation before the decision, and then chosen-or-not after the decision. Meanwhile, each time the animals played the game, researchers measured the electrical activity of hundreds of neurons in the lateral prefrontal cortex, a surface brain region known for having a key role in linking options, values, and actions in decision-making.
Using “declassifier” algorithms to decode the electrical patterns, the researchers found that the neurons acted in functional ensembles whose collective activity clearly indicated decision-related information, including the distinct target directions and their assigned values. To interpret and compare each ensemble’s patterns, the researchers visualized these “subspaces” geometrically as planes on a 3D graph.
The researchers’ key finding was that before the values were assigned and a decision was made, the neural ensemble patterns consistently represented options based on their order of presentation. For example, on the graphs each “target 1” plane was nicely parallel with the others. Similarly, each “target 2” plane was parallel with its brethren, but the target 2s were more orthogonal, or more perpendicular, with the target 1s, showing that they were represented as entirely distinct from each other.
Then, after the decision, new ensembles provided new representations. Now the “chosen” options, whether they had been presented first or second, had parallel representations. The unchosen targets were also represented as parallel with each other, but as orthogonal from the chosen ones.
Getting one’s neural ducks in a row
In other words, before the decision, the brain convened ensembles of neurons to distinguish targets by their presentation order, and then after the decisions, gathered ensembles to sort them by whether they were chosen or not. This consistent way of representing chosen options, Li and Miller wrote, could aid decision-making by essentially packaging it for downstream circuits responsible for converting the decision into action (in this case, directing the animal’s gaze in the chosen target direction).
“The observed alignment of chosen target representations could allow downstream areas to read out the location of the chosen target with a single decoder, regardless of its initial presentation order,” the authors wrote.
Notably, the researchers also found that round by round of the game, individual neurons could often be recruited in to different ensembles. A neuron that in one round seemed “selective” for option 2 could end up being selective for option 1 the next. The ensembles were therefore not permanent circuits of specialized neurons, but instead were assembled ad hoc among multifunctional neurons.
In other research, Miller has found that the brain uses brain waves to rapidly and flexibly accomplish this goal of ensemble recruitment.
Another clear implication of the data, Miller says, is that the brain maintained distinct memories of each option, whether it was chosen or not. This could be important for assigning credit down the line to facilitate learning. For instance, remembering that choosing target 2 in round 3 earned a reward.
“Our results illustrate the dynamic subspace reorganization supporting option maintenance and selection in economic decisions,” the authors wrote.
In addition to Li and Miller, the paper’s other authors are Nikolaos Chrysanthidis, Scott Brincat, and Jonas Rose.
The U.S. Office of Naval Research, the U.S. Army Research Office, the Freedom Together Foundation, and the National Institutes of Health provided support for the research.
Poitras Center to fuel early careers of 50 young scientists dedicated to psychiatric disorders researchPatricia and James Poitras ’63 provide fellowships for graduate students and postdocs who will shape the future of mental health research.Patricia and James Poitras ’63, longtime MIT supporters, have launched a fellowship program for graduate students and postdocs studying major mental illness, expanding their MIT philanthropy to directly support early-career scientists. The commitment establishes 50 two-year fellowships through the Poitras Center for Psychiatric Disorders Research at MIT’s McGovern Institute for Brain Research. Five fellowships will be awarded every year for the next decade, creating a long-term talent pipeline focused specifically on psychiatric disorders.
The $10 million gift is the latest in a series of philanthropic investments from the Poitras family to strengthen MIT’s capacity to address the growing burden of severe depression and anxiety, bipolar disorder, schizophrenia, and other complex psychiatric conditions. “Pat and Jim have remained steadfast in their decades-long commitment to bold research that can transform mental wellness,” says Robert Desimone, director of the McGovern Institute and head of the Poitras Center. “Their remarkable support of rising talent in the MIT ecosystem is yet another emblem of their commitment to that cause.”
A philanthropic legacy
Many recent mental health discoveries emerging from MIT — from molecular tools that can rewrite DNA to artificial intelligence-powered technologies that can calculate a person’s risk for developing mental illness — were hard to imagine two decades ago. Yet, Patricia and James Poitras envisioned a future where enigmatic mental health conditions could be solved. They understood this future would require not just research, but a fundamental reimagining of how psychiatric research itself is conducted.
In 2007, inspired by meetings with leadership at the McGovern Institute, the Poitras Family gifted $20 million to launch the Poitras Center. By bridging the fields of basic neuroscience, clinical psychiatry, and molecular biology, the center sought to establish a unified blueprint for understanding how psychiatric disorders hijack the mind at every level, from molecular mechanisms to whole brain systems, and guide the creation of novel therapies to better treat them.
Since the center’s establishment, additional investments by the Poitras family have supported research ranging from genome engineering to cognitive neuroscience. These investments have empowered scientists across disciplines to pursue innovative research questions, including how ketamine acts on synaptic communication and why schizophrenia distorts inner speech and reasoning. These efforts have ushered in major breakthroughs in mental health: an AI-powered calculator for predicting bipolar disorder risk in adolescents, molecular carriers that precisely deliver therapies throughout the body, and strategies that use patients’ brain activity patterns to match them with optimal treatments, among other advances.
Expanding support for early career scientists
The Poitras family’s latest gift invests directly in the PhD students and postdocs who will carry the field of psychiatric research forward. It comes at a time when federal funding has grown especially precarious. “To make the greatest impact on the world’s mental health, we recognize that we must not only support transformational research, but also the young people driving its progress,” says James Poitras, who is also chair of the McGovern Institute’s board.
Five McGovern Institute researchers have been selected as the inaugural cohort of Poitras Center Fellows and Graduate Scholars. Their projects span multiple areas in brain research and could reveal a suite of new ways to heal the mind.
The new gift extends the Poitras family’s support of mental health research at MIT to over $100 million. It also marks another step toward a bold vision years in the making.
“Serious brain disorders profoundly affect patients, families, and caregivers,” says Patricia Poitras. “We believe that investing in the next generation of researchers will accelerate powerful discoveries that lead to life-changing treatments and better future for countless patients and families.”
The next application window for Poitras Center fellowships will open in May 2027.
MIT named the nation’s top university by U.S. News for 2026-27The Institute’s undergraduate engineering, computer science, and economics programs are No. 1; its business program is No. 2.U.S. News and World Report has designated MIT as the top school in its annual rankings of the nation’s best universities, announced today.
Among the academic specialties that U.S. News evaluates, MIT’s engineering program continues to lead the rankings of undergraduate engineering programs at a doctoral institution. The Institute’s undergraduate computer science and economics programs also ranked No. 1, and its undergraduate business program ranked No. 2.
U.S. News ranked MIT highly in several other categories: The Institute is No. 1 for undergraduate research and creative projects, No. 2 on the list of most innovative schools, and No. 3 on the list of best value schools.
MIT placed first in five engineering specialties: aerospace/aeronautical/astronautical engineering; chemical engineering; electrical/electronic/communication engineering; materials engineering; and mechanical engineering. It placed second in computer engineering.
Other schools in the top five overall for undergraduate engineering programs are Georgia Tech, Stanford University, the University of California at Berkeley, and Caltech.
In computer science, MIT placed first in three specialties: biocomputing/bioinformatics/biotechnology (tied with Carnegie Mellon University); computer systems (tied with Carnegie Mellon); and theory. It placed second in three other disciplines: artificial intelligence, data analytics/science; and programming languages.
Other schools in the top five overall for undergraduate computer science programs are Carnegie Mellon and Stanford (both tied with MIT at No. 1), as well as UC Berkeley, Georgia Tech, Princeton University, and the University of Illinois at Urbana-Champaign.
In economics, MIT placed first in four specialties: development economics; econometrics; industrial organization (tied with Northwestern University); and microeconomics. It placed second in macroeconomics (tied with UC Berkeley).
Other schools in the top five overall for undergraduate economics programs are Harvard University, Princeton, and University of Chicago (all tied with MIT at No. 1), as well as Stanford, UC Berkeley, and Yale University.
Among undergraduate business specialties, the MIT Sloan School of Management led in three categories: analytics; production/operations management; and quantitative analysis. It placed second in entrepreneurship.
Other undergraduate business programs ranking in the top five include the University of Pennsylvania, UC Berkeley, New York University, and the University of Michigan at Ann Arbor.
Podcast: SHASS’s special sauceEstablished after World War II, the School of the Humanities, Arts, and Social Sciences is an integral part of the MIT experience. Three faculty reflect on the school’s ongoing impact.Following World War II, the MIT faculty convened a committee to assess the Institute’s principles of education and their relevance “in a new era emerging from social upheaval and the disasters of war.” One of the outcomes of this pivotal report was the establishment of the School of Humanities, Arts, and Social Sciences (SHASS). MIT News convened a discussion with three SHASS faculty — David Kaiser, Heather Paxson, and Jonathan Gruber — about what makes the school special and why it’s a core part of the MIT experience. Listen to the conversation or read the transcript below.
Peter Dizikes: Welcome to MIT, everybody. My name is Peter Dizikes and I’m a writer for MIT News. Every year, over 1,000 undergraduates enroll at MIT. Once they’re here, they’ll spend at least a quarter of their time studying a set of core subjects such as music and theater arts, history, anthropology, and economics, linguistics and philosophy, literature, political science. These are all offered within MIT’s School of Humanities, Arts, and Social Sciences, known on campus as SHASS and a core piece of the university.
MIT is 165 years old. This month, SHASS turns 75 and is celebrating its anniversary with a two-day conference, September 24th and 25th. For this MIT News Roundtable, we’re delighted to have three distinguished faculty members from SHASS with us, historian and physicist David Kaiser, anthropologist Heather Paxson, and economist Jonathan Gruber, who are all here to talk about what makes SHASS a special place. Thank you all for joining us.
David Kaiser: Thanks for having us.
Peter Dizikes: If it’s all right, I’d like to just jump in and start by asking each of you a different question about SHASS. Perhaps we could start with you, David. David Kaiser, for our audience, is the Germeshausen Professor of the History of Science and Professor of Physics at MIT. He’s written numerous books about the history of physics and done scientific research focused on inflationary cosmology, the very rapid, very early expansion of our universe. He’s also edited a volume about the history of MIT and is, I think, the lead organizer of the SHASS 75 Conference.
David Kaiser: It has taken a village, but I’ve been lucky to work with a whole group.
Peter Dizikes: Very good. Well, on that note, the note being MIT history, right after World War II, MIT decided that it wanted to form SHASS. Why was that and how has that worked out for us?
David Kaiser: That’s right. So they didn’t decide very rapidly. And again, as people might know, there were some departments that we would now associate with SHASS that preexisted this. Economics, for example, had been taught at MIT as its own department from well before then. But there was this famous — famous for us, famous on campus — something called the “Lewis Report,” which you’ll hear about over and over again this year, I’m sure. And it was actually, I think, a three-year effort. So the group was put together very soon after the end of the second World War, starting in 1946, very soon. And they got together and studied almost everything you can imagine about life and the future at MIT. I mean, like parking lots and how far do the faculty commute, which is on my mind, as well as things like the undergraduate curriculum, dormitories, really every aspect, intellectual, residential, social, and beyond. It’s a really remarkable report and it’s easy to download from the web. It’s really worth reading even, I think, to this day.
But as you rightly know, when they completed the report in 1949, among their most significant recommendations was that MIT should not just have a few departments in humanities and social sciences, but have a concerted effort in what we would now call SHASS. Originally, it was the School of Humanities and Social Sciences. And of course, about 25 or so years ago, 50 years since the founding, we also very proudly added arts to our name.
So the point is the Lewis Committee said, in essence, there are so many striking, dramatic, literally world-changing developments that we can associate with what we might now call STEM, or science and technology, and they had in mind things like the Manhattan Project and nuclear weapons, which had been used to such dramatic effect just not long before they wrote the report. And they were concerned that changes that could be that rapid and that far-reaching simply require an informed leadership, an informed citizenry, more generally, of people who can try to think critically and carefully and kind of contextually and not only understand neutron diffusion, but also understand the flow of people and ideas and cultures and politics and beyond.
They argued not just that SHASS should be founded, it should be, as they said, “A co-equal school to the existing schools.” The report was very clear: This needs to be as central to MIT’s existence and experience as School of Science, School of Engineering, and of course there are other great schools as well. And it really was, there’s too much at stake, changing too rapidly with too far-ranging implications for our students and our faculty and staff and the broader community not to have the toolkit to think about history, governance, economics, culture, identity, human expression — that these were inescapable parts of being an educated member and a responsible member of the new nuclear age.
Peter Dizikes: Surely we still have enough challenges today that that rationale would hold up, we think?
David Kaiser: I think we’re done! No, we haven’t nailed it. There’s a few more things to worry about. And so I think when I say I return to that Lewis Report, I really do because some parts will seem quaint — what were the concerns in 1949 might not always resonate today — but a lot of the concerns sound actually quite contemporary. And with only a little bit of keyword swapping, I think we’ll get to it, I’m sure, in our discussion, no shortage of topics today that are filling a kind of intellectual role that the disruptions of the second World War had played for that earlier generation.
Peter Dizikes: Right. Thank you. Heather, I’d like to toss a question to you as well. Heather Paxson, for our audience, is the William R. Kenan, Jr. Professor of Anthropology at MIT, a former head of the MIT program in anthropology, and she is currently associate dean for faculty in SHASS. You’ve written multiple books, including “The Life of Cheese,” which I can vouch goes very deep into the American psyche. Heather, given that you are dean and I think have a lot of visibility into what’s going on SHASS-wide, in a sense, could you just say a little bit more for us about the breadth of everything that happens in SHASS?
Heather Paxson: Thank you, Peter. So putting the humanities and the arts and the social sciences together in a school is actually quite unusual among our peer institutions and does make for some really fun collaborations and convenings.
So just to give you a little taste of that breadth, just this week yesterday, our colleagues in political science, Adam Berinsky and Charles Stewart, and research that they’re doing in collaboration with Chara Podimata, who is an operations research specialist in the Sloan School of Management. They are using AI to study AI. They did a huge study or are in the midst of a huge study of looking at how AI chatbots are providing information to citizens about elections that may or may not be biased and tailored to the asker and what the effects that will have on our midterms coming up. So very timely, amazing work. That’s social sciences.
In the arts, yesterday I saw our colleague Jay Scheib, who’s the head of Music and Theater Arts. He’s a stage director and he’s just back from Germany where he’s been staging a production of Wagner in Germany. So, really, just a lot of fun stuff.
Peter Dizikes: It is actually amazing the breadth of people circulating around here. Jon, I have a question for you as well on a slightly different note. So Jon Gruber is Ford Professor of Economics at MIT, a former head of the Department of Economics, he’s published over 200 research papers, I think I can say is one of the most influential figures in the expansion of health care access in the U.S. You’re also the only person here right now who’s been an MIT student. You were an undergrad here. Could you just say a few words about what was significant about your student experience, what you took with you from being a student?
Jonathan Gruber: One thing that’s sort of embarrassing is when I started as undergrad here, I was closer to the Lewis Report than we are today. And the Lewis Report was still, in many ways, being implemented when I was undergraduate. I would say SHASS was much more of a second-class citizen then than it is now. It was sort of embarrassing to say one was a SHASS major without saying a double major, but it was really viewed as a service organization, something kids took so they could get on with their courses that mattered.
I really think that’s changed. I think the MIT student body’s changed from when I was here. We’re a much more well-rounded student body. We’re now competing with these Ivy League institutions that we were very separate from when I was a student, and that wouldn’t be possible without SHASS. But I think what’s important to recognize is MIT is no longer a school that just competes with engineering schools. We’re a school that competes with all universities. And the only way to do that is a well-rounded education. Folks aren’t going to come here if they can’t have a well-rounded education, if it’s just a science education. So SHASS has developed to become so much more integral into the life of MIT. The respect level of SHASS, everything has just really improved.
Peter Dizikes: Were there particular classes or courses that jump out in retrospect?
Jonathan Gruber: Well, I think I’m a great story for SHASS in the sense that I came to MIT as someone who’s good at math, but didn’t like math. I was just good at it, but I wasn’t someone who was doing proofs in my basement. I just didn’t find it appealing. But I came to MIT because it was a math-y school and it was the best school I got into and I was good at math. And then I took 14.01, which is our Intro to Economics class, and I was like, “Oh my God, I can use math for something interesting. I can actually take this math I love to answer questions I really want to answer and on topics I really care about in the real world.” And that was just eye-opening to me. I literally can picture standing at the crosswalk at 77 Mass Ave with my then girlfriend telling her how excited I was. I can picture that moment, what 14.01 had opened up for me. So you can imagine it’s incredibly thrilling for me now to get to teach 14.01 and hopefully inspire some of those students the way that I was inspired.
Peter Dizikes: What’s interesting is many people here have slightly indirect paths to what they ended up doing, right? So you didn’t come here expecting for that to happen, but it happened.
Jonathan Gruber: That’s exactly right. I think one thing that’s very important at part of the university education is to open yourself up to learning new things and heading in new directions. One concern I always have about MIT is that students come here too predetermined to do X. I think that’s almost more of a problem here than other universities. I think that’s why SHASS is so important. Because we want to open their minds to the fact that even if they move from science major X to science major Y, along the way they’re exposed to a range of things that allow them to choose what’s going to give them the most fulfilling future, not just what they thought was interesting in high school.
Peter Dizikes: And when I said at the outset that a quarter of the time they’ll be spending on some of these subjects is this is one of the MIT requirements, is that people need eight classes from SHASS during their four years here. So hopefully they do get that kind of exposure.
Jonathan Gruber: That is why we have that requirement and hopefully they take those classes seriously and are open-eyed and can really… I’ll tell you, Peter, one of the things that distresses me most is the number of juniors and seniors I have taking 14.01 saying, “God, I wish I took this freshman year. I would’ve studied more economics.” Which makes me feel good about my class, but a little disappointed that it’s taken that long to find it.
Heather Paxson: Oh, we thought that was just anthropology! They don’t even know how to find econ?
Jonathan Gruber: Exactly.
Peter Dizikes: Well, stepping back for one second. In daily life, what is special about being at SHASS? Teaching and learning is one of those things, but if you had to cite a couple of things about the qualities and characteristics of being here, the students, your colleagues, what would you say?
Jonathan Gruber: I mean, I would say that what’s special and unique about SHASS at MIT is the fact that we are at MIT and that we are the place that can bring together the science and the social sciences and humanities and arts in a productive way, which is so important right now. The conversation cannot go on without talking about AI, but basically the fundamental central issue in AI right now is how do we think about it ethically? How do we regulate it? And there’s no place better to think about that than MIT, where you’ve got the people developing the frontier AI models next to the people who can help you think about how to regulate and think ethically about those models. And so I think this world is increasingly becoming STEM-based, and I think, as a result, the most productive place to learn about topics from anthropology to history to economics is a place where you’ll learn about that alongside STEM.
Peter Dizikes: Since you mentioned that everything is affected by AI, I’m interested in what everybody’s favorite teaching experiences have been here, but you’re also probably having to be a little bit mindful of how to make sure that everybody is doing their own work and putting in the hard work and the hard thinking that it takes to really get what you want out of MIT. So those are two questions. From pre-AI days, do you have a particular favorite kind of teaching experience? What made it great? And then how are we adapting now?
David Kaiser: One of the courses I really love teaching here, I’ve been teaching it on and off, really, for 20 plus years, is cross-listed in our program in Science, Technology, and Society, my home department, also in Physics, and it counts as another one of these, I think, very important requirements that all the undergraduates must take. It’s a communications-intensive course in the major for the physics major. So they have to learn to write essays and express themselves coherently as part of their physics education, as well as, of course, throughout their SHASS coursework.
And so it’s predominantly students who are, like Jon had been, very interested in math and math-y things and physics and all those things, but they also have to come in there and not just rely on their, frankly, fabulous calculating skills. They have to practice reading stuff that might look a little unfamiliar or unexpected to them and they have to practice really composing coherent arguments about that. And the arguments sometimes are about the intellectual work, what was Einstein’s thinking in 1905 and how do we know and why does it matter?
A lot of it in this class turns to the things like I think were on the minds of those authors of the Lewis Report. What are educated people’s responsibilities under very complicated disruptive times like wartime, like the escalation of fighting of Vietnam? The list is long, just within recent history. What does it mean to take a remarkable education in a variety of fields and do something with that that is consistent with what you think you want to do as a person and as a member of a larger group? And to watch our physics majors wrestle with this creatively, and there’s no single answer that they’re racing toward, I think that’s just incredibly rewarding.
And a lot of them, I hear over and over again from seniors who are about to go to very fancy PhD programs in physics, “I never really paused to think about time dilation until I had write an essay about it. Oh, yeah, there’s kind of a reason for that.” Or, “I never really got my head around quantum theory, I could solve my problem sets, but there’s something really strange happening in the universe and it’s not only captured by these very, very complicated mathematical expressions, so that’s essential too.” So I have this collection of favorite moments of these kinds of “aha” where the eyes light up and the jaw drops at least a little bit and you say, “I didn’t even know that was a thing I didn’t know.” And it’s really fun to see that.
Peter Dizikes: And that comes out of having them write about things.
David Kaiser: It has them reading text, and not only a textbook, and then really having to make their own argument based on their own selection of primary and secondary sources, the way we would teach to do in our other courses.
Peter Dizikes: We like to say that writing is thinking.
David Kaiser: Yeah. They have to clarify and make a case. Yeah.
Peter Dizikes: Heather, do you have?
Heather Paxson: I’ve been teaching here for quite a few years now, but before I got here, I probably taught at five other colleges and universities, so lots of different teaching experience in different sorts of institutions. And for many years I would say, MIT students, it’s just different. It is just so much more fun to teach anthropology with MIT students because they came to class having approached the texts, reading them, not to decide whether they agreed with the text or not, they were needed to be persuaded by the argument, and it really made for a very rich conversation in the classroom.
I think it’s interesting because the moments in the classroom that I can think about or the assignments or the engagements that I can think about are actually things that I think we are all trying to steer more towards today. So the things that I’m doing in class or trying to do in class today, more experience-based projects, more hands-on, are the things that actually, thinking back, I’ve done for a long time and are the most memorable.
So just one example, a class I haven’t taught in a very long time, but a colleague is teaching it now, a class called Art Craft Science, which is really fun to teach here. The assignment was to make mozzarella cheese. So I gave them instructions straight from the box of this mozzarella making kit and the instructions were not very well written. They were predicated on a knowledge of cooking and so forth. That was the point. So they had to go home, I gave them the ingredients, they made cheese, and then they write it up as a lab. I figured they knew how to do that, write it up as a lab. And the discussion of the lab was to reflect on the skills that they relied on to be able to enact these really poorly written instructions. So it was all about tacit knowledge. And so that was the lesson.
And that’s the kind of thing I think we’re all trying to reinvent now in the age of AI, but I’m sure we’ve all been doing it, we just didn’t have as much sense of attention to it. But that is MIT, the “mens et manus” thing. It’s all over our curriculum. It always has been, but now it does have this new, I think, shiny coin value to it. So that’s what’s fun.
Peter Dizikes: Our motto “mens et manus” is “mind and hand,” and I’m sure there is going to have to be a lot of continual reinventing of these kinds of exercises going forward. Do you have?
Jonathan Gruber: I would say there are two things that make me happiest as a teacher. One is when I illustrate the power of economics through counterintuitive lessons, when I can see the kids are like, “Wow, that’s really cool. I didn’t think of it that way till I took this class.” That’s really great. When it just can change the way that they think, they can think about things somewhat differently. And that’s what I hope the kids take from the class. I always say, “I don’t care if you remember certain terms, I just want you to think like an economist.” And when I see that happening, it’s wonderful. But most enjoyable is when they laugh at my jokes. My wife can tell if I’ve had a good lecture day, a bad lecture day, what percent of my jokes they laugh at, which is always below 10%, by the way. But the question is, is it 10% or 1%? And that’s really the most important thing to me.
David Kaiser: Jon, quick question. Does the proportion rise closer to midterms? Are they gaming the system?
Jonathan Gruber: No. No, not at all.
David Kaiser: No time series?
Jonathan Gruber: No time series.
David Kaiser: Just checking. All right, good to know.
Peter Dizikes: You haven’t had anyone come in and really study that empirically, though?
Jonathan Gruber: No, but the best review I ever got, now this was many years before he got famous for a different reason, was that I was viewed as a “well-dressed Pee-wee Herman.”
Peter Dizikes: Students will say if a professor makes them laugh, they’ll take that class when they’re shopping around, right?
Jonathan Gruber: Yeah, hopefully so.
Peter Dizikes: Slightly different kind of question here, which is: How has being at SHASS perhaps influenced your careers? You’re all people who’ve done different things in the same career. Heather, you’ve written about some very different topics. Jon, you’ve been very involved in research and also public policy. And Dave, you’ve had two careers in one as a physicist and a historian. So what is it about this place that maybe encourages you to try different things and follow through with them?
Jonathan Gruber: Well, Dave, you’re the two-in-one. You should start.
David Kaiser: Oh, okay. It’s buy one, get one free, I think. So one example comes to mind, Peter. I think many will eventually. But a number of years ago I wrote a book as an historian that I just loved immersing myself in all the things historians do, finding dusty old papers and interviewing people around. And it was called “How the Hippies Saved Physics.” It was a kind of an obnoxious title or funny title. And it was really who cared about certain obscure sounding questions in quantum physics before the whole field knew we had to care about them. It was really, I think, to me, at least an engaging and fun story about people on the margins who made contributions there.
Where I’m going with this is because I’m here and very lucky to live in more than one department and interact with all kinds of folks, one of the extremely gifted postdocs in physics who had just come to MIT to work with me on the physics side, read the book on a lark because it had a funny cover, I think is why he probably picked it up. And the upshot is that got us thinking more about our own physics projects because the historical study said, “Oh, I never thought that’s where these ideas came from, and I see what they did then and we’ve learned a lot more about these things in the interim. Let’s try this something new.” So we put a little group together and that became a five-year, really, adventure for me on the physics side that grew entirely, at least for me, from the fact that I’d spent several years writing this kind of deep-dive historical study.
The ability to have one lead to the other, to have these conversations happening close in time and close on campus to each other, I mean, that’s extraordinary and I’m very lucky, and I don’t know that I would have that at many other places where I could have been or where our friends are. So I think that the boundaries are not actually that high between our various parts of campus. They can feel high at times, but there really is the kind of cross-campus traffic, and we’re trying to get more of that going with recent initiatives. I think we really can just bring questions together without saying, “Oh, but you’re in that department, I’m in this department.”
Peter Dizikes: Having read “How the Hippies Saved Physics,” which came out in 2011, I would say you were writing about figures who, even at the time, were semi-overlooked, but since then have gone on to win major awards, and in a way the whole area of study there has been elevated.
David Kaiser: Well, that’s right. One of what I like to call “my hippies,” shared the Nobel Prize in physics in 2022. And in fact, one of the colleagues that I got to do the physics work as a follow-on with shared that same Nobel Prize, I think it’s, frankly, because he began working with me. Anton hasn’t gone on record, but I think the record speaks for itself. Anyway, the point is it’s now sort of extraordinarily exciting work that came from just 50+ years earlier from really being on the margin and being denigrated. And that kind of arc in the span of a single human lifetime or a career is really rapid change. Anyway, to be able to sit and watch that from many facets, it was a great adventure.
Peter Dizikes: And that joke landed, so you’re batting over 10% in this.
David Kaiser: I mean, look, I’m not keeping score, Peter, but I know where it’s going to be at the end.
Jonathan Gruber: I would say two things. So one is, going back to my undergrad days, I think many students here are head down, do the work, don’t necessarily engage with a lot of what’s going on in the world. I had a political science professor named Louis Menand who changed my life, who made me engage. He’d worked in the great society. He really was very opinionated, but in a way that he could defend it. It really opened my eyes and he began by getting involved in working on policy at MIT. So I was the first student representative to the committee on the undergraduate program when Margaret MacVicar set it up in 1985. I was the first student representative. And then it grew into my interest in just policy in general, so that was very exciting for me.
And then the other thing was the way I’ve been involved in policy is a particularly MIT way, which is that I’m the numbers guy when health care policy gets made. I develop computer models and mathematical models to help folks understand how their policies will affect people. But those models themselves don’t do any good unless we can explain what they’re doing in clear terms. So it’s really that crosswalk of why it’s great to be at MIT, which is I have the math skills to do it and I have the incredible students to help me, I mean, the work in this area has been helped by so many amazing students, but to have the SHASS skills and the communication skills to be able to explain what I’m doing and why it’s important, that is really kind of where SHASS is perfect for me.
Peter Dizikes: And also noteworthy that you had such an influential class that was not in econ, as important as you found those to be, but this is a political science class as well that helped feed into it.
Jonathan Gruber: Exactly.
Peter Dizikes: Heather, on maybe a slightly different note, how do you keep this healthy, productive culture going in all these different departments? We have this famous culture in the Department of Economics and in many other departments throughout SHASS where there’s this culture of openness to inquiry and elevating interest in students, but how does one, over 75 years, keep that going?
Heather Paxson: Well, thanks for asking the anthropologist about culture. I think we often think of culture in terms of ideas and values, a shared set of ideas and values, but my one word answer to that is actually “participation.” I love that, Jon, you were a student rep on an institute committee. I mean, it’s that kind of participation in the workings of our organizations and the workings of our departments, of our deciding what gets included in the curriculum, that participation is what creates a sense of belonging and certainly is the stuff of culture.
Peter Dizikes: So the things we study over 75 years are going to evolve and change, the things we believe are going to evolve and change.
Heather Paxson: So like an institution’s culture is what mediates between what changes and what stays constant.
Peter Dizikes: Do you find that to be broadly the case here?
Jonathan Gruber: That’s a great quote. I will be using that.
Peter Dizikes: Also, you’re now batting 100% on jokes as well. Dave, what can we expect from the conference which is coming up in the very near future?
David Kaiser: Very near future. I’m really excited about it. It’s been a lot of work from really, genuinely a very large, wonderful, hardworking committee. I’m most excited because we have 40 plus speakers, including Jon, and Heather’s going to share us a panel. We’re going to hear from early career scholars, from more experienced scholars, we’re going to hear from people representing every single unit in SHASS, from alumni, including Jon, more recent alumni, done different things with their SHASS and MIT educations out in the broader world. We’re going to have a session I’m especially excited about, a showcase put together by Music and Theater Arts, original musical compositions, a dance performance, the jazz ensemble play. I mean, this is just fantastic. For free, really? Plus really good food. It’s going to be great.
It’s going to be an exhausting, but, I think, very, very exciting two days. I think the goal really is to showcase how we’re thrilled to be doing things in our own fields, advancing knowledge in the way that we and our immediate colleagues are most excited about, and it’s not only limited to that. And I think part of the message will be, and has been, as we began the discussion with, practically every challenge we might tick off on our finger is the biggies that keep us up at night. None of those will be solved by a technical fix alone, or frankly, a little tweak on a humanistic side or social science either. We really, really have to continue getting even better at doing the kinds of collaborative work across fields and across departments.
None of these challenges has a single or simple answer. If they did, they wouldn’t be persistent challenges. So the more that we can share with ourselves across our departments with MIT and beyond, it’s open to the public, the symposium is, that this is really a place where we can enter together with humility and experience, both, and try to build teams that couldn’t do these things on their own. And I think we’ve been doing more and more of that with the presidential initiatives, MITHIC and the whole series of them. I think we just have to keep building that as a muscle we can flex and get used to using more often. And if the symposium can help recenter that emphasis for our own colleagues and beyond, I think that’d be a great, great success.
Jonathan Gruber: Peter, I think this raised a really important issue, which is in economics, we have the concept of the public good. What’s the public good? That’s a good where one person’s efforts benefit everyone. In this world of incredibly intense academic pressure and pressure to earn a good living, it’s hard to come to university and focus on the public good as opposed to private good. SHASS is the place at MIT that focuses students on the public good.
You have people like David and Heather who spend so much time dedicated to so many different committees and making MIT function, and that’s led by SHASS. Not that there aren’t great participants all around the university, but SHASS is really the participation leader. And universities need that. That’s the lifeblood of this university, is that kind of volunteerism and participation. I hope that students by being exposed our courses get the value of the public good, that they realize that maybe it’s not as valuable to them, per se, but that there’s a value to the institution and the world of them doing the kind of volunteering that Heather and David do.
Peter Dizikes: That’s very well said.
Jonathan Gruber: Thank you.
Peter Dizikes: Thank you all so much for joining us.
Jonathan Gruber: Thank you.
David Kaiser: Thank you.
Heather Paxson: Thank you, Peter.
Peter Dizikes: It’s much appreciated.
Finding purpose through researchThis summer, BSG-MSRP-Bio student Marina Milea investigated how lung cancers become resistant to targeted therapies, gaining hands-on research experience in the Jacks Lab at the Koch Institute.Most mornings this summer, Marina Milea arrived at the Koch Institute for Integrative Cancer Research building ready to juggle several experiments at once. While one set of samples incubated, she stained mouse tissue sections for immunohistochemical analysis, prepared to run a Western Blot gel, and checked in on an organoid culture.
All this work, and more, was part of learning the complex workflows behind studying how cancer evolves over time in the Jacks Lab at MIT. For the rising senior, who is majoring in biology at the City College of New York (CCNY), the pace was exactly what she had hoped to find through MIT's Bernard S. and Sophie G. Gould MIT Summer Research Program in Biology (BSG-MSRP-Bio).
"The techniques can be taught," she says. "The hardest part has been understanding the complex mouse and organoid models and why we're using them. Once you understand the biology behind the model, you can really interpret your results and think about how they might translate to human biology."
Milea is investigating how lung cancers driven by mutations in the KRAS gene become resistant to targeted therapies by transforming into a different subtype that is often harder to detect and treat, a phenomenon called adeno-to-squamous transition. By studying the signaling pathways and protein families that support this transition, researchers hope to identify new therapeutic targets for patients whose histologically-transformed cancers no longer respond to treatment.
"I wanted to do something that had translational aspects to it — to work on research that could potentially change how patients receive therapy," she says. "That's incredibly motivating as an undergraduate."
Building a foundation
Milea says CCNY has played an important role in helping her pursue research to build upon her strong academic foundation. Located in New York City, the university is uniquely positioned to foster collaborations with nearby institutions, connecting students with laboratory experiences across the city while serving a diverse student population that includes many first-generation and low-income students.
Milea's interest in biology began while attending high school in England, where students choose academic subjects early. Initially drawn to medicine, she pivoted to biomedical research after being diagnosed with an understudied health condition, sparking her curiosity about the mechanisms underlying disease.
Before coming to MIT, Milea gained research experience in several laboratories, most notably at Columbia University between the Azizi and McFaline-Figueroa labs.
"I went from having no cell culture experience to learning CRISPR techniques, T-cell engineering, and machine-learning approaches in a single summer," she says. "It was intense, but it gave me confidence that I could handle a research environment like MIT's."
Learning to think like a scientist
At MIT, Milea found herself in a laboratory that matched both her scientific interests and her desire for close mentorship, working with graduate student Carrie Rodriguez.
"I could tell Carrie genuinely wanted to teach," she says. "She explains not just the protocols, but the biology behind them. By understanding why we're doing each experiment, I could contribute my own ideas."
As the weeks progressed, Rodriguez gradually entrusted Milea with carrying out more and more work independently.
"By the second month, I was running entire workflows on my own," Milea says. "I felt like I was really helping move the project forward."
Milea's willingness to learn and engage deeply with the science made her a valuable member of the lab.
"Marina arrived in the lab with an outstanding attitude, ready to take full advantage of this opportunity. Over the course of the summer, she was able to learn a number of new techniques and, more importantly, dig deep into the biology of lung cancer. She was a wonderful addition to the lab," Tyler Jacks says.
Looking ahead
Outside the laboratory, faculty lectures, journal clubs, and conversations with researchers all play a part in broadening the scientific perspective of BSG-MSRP-Bio program students. A lecture by MIT Professor David C. Page, for example, whose work explores sex differences in health and disease, reinforced Milea's long-term goal of advancing research in women's health.
"He talked about pursuing scientific questions because you believe they're important, even if they're not yet considered priorities," she says. "That, in particular, resonated deeply with me."
Following graduation, Milea plans to pursue a PhD in biomedical sciences and hopes to build a career that combines research, teaching, and mentorship.
A program that values potential
Looking back, Milea hopes other students will feel confident pursuing opportunities that initially appear out of reach.
"A lot of people count themselves out without understanding what a program like this one is looking for," she says. "They value people who have original thinking and who can really contribute to the projects intellectually and practically."
Although the BSG-MSRP-Bio program is one of the country's premier undergraduate research programs, she believes its commitment to fostering students' potential is what makes it exceptional.
"It's somehow the most competitive and the most open-access program there is in the country," she says. "You can be an international student, first-generation, low-income, or from a non-research-intensive university — but you still need to meet high expectations. It's somehow both, which is great."
For Milea, that's what makes the program unique.
"They have high expectations," she says, "but you can be anybody."
A home a world away from homeOne graduate student family treasures the community they found alongside other MIT student parents.For Nicholas Maurer, an international PhD student from Australia pursuing his degree in social and engineering systems through the Institute of Data, Systems, and Society, MIT was a lifelong goal. Growing up in Australia with a background in physics and engineering, he worked as a researcher, but never stopped wondering what it would be like to study at MIT.
When the opportunity came two years ago, he and his wife Andrea made the leap across the world, bringing their young children Elaine, 5, and Zachary, 3, with them. “It was always on my radar,” Maurer recalls. “Coming to MIT felt like a dream come true.”
Weighing their options
Maurer’s wife, Andrea, explains that it was “always in the cards” for the couple to travel for his studies, but neither of them expected this step to come after they had kids. Nevertheless, when Nicholas received multiple PhD offers, the decision came down to one crucial factor: support for their family of four. Together, the couple researched resources before deciding on the move. MIT's commitment to student parents stood out immediately.
As they learned more about the MIT Grant for Graduate Students with Children, on-campus childcare options, and Westgate — MIT's dedicated student family housing — their interest grew. They could tell that MIT cared about building a real home for its families.
Finding community in Westgate and beyond
Their residence has become far more than housing for the Maurer family; it's the heart of their MIT experience. Maurer credits the dedicated family accommodation with helping them form instant connections. “The biggest support has been Westgate,” he says.
For both Nicholas and Andrea, the international character of Westgate held special meaning. After moving from Australia, being surrounded by families from around the world eased the transition. The couple eventually became more involved with the Westgate community as parent resource coordinators, helping maintain connections among other parents and spouses.
When the family initially arrived at MIT, Andrea also found friendships through MIT Spouses and Partners Connect (MIT S&PC). “Meeting other spouses provided great comfort as others shared their experiences navigating this new life,” she explained, adding that it was helpful to see how others supported their partners through various MIT programs.
Although financial cuts necessitated S&PC's closure last year, she has been able to keep the spirit of the initiative going through informal meetups and coffee hours.
Parenting at MIT
The family has made the most of MIT's community offerings, attending student-parent lunches during finals week, visiting Rock Spot for rock climbing, and enjoying free ice cream events. They've also taken advantage of MIT Activities Committee discounts for family activities, allowing them to explore the greater Boston area.
Although the supports are substantial, Maurer is candid about the realities of balancing a PhD with parenting. “It's not for the fainthearted,” he says. “It takes a lot of time management and being honest with your capacity. I have learned to say no to some social activities or enrolling in that extra class I’m interested in, in favor of focusing on my core research objectives and supporting my family.”
Amid the challenges, though, there's genuine joy. “It's been amazing seeing our kids meet and play with kids from all over the world,” Maurer reflects. “MIT is an amazing place.”
Carter Stubbs named Institute auditorNew Audit Division leader brings track record of collaboration, deep knowledge of audit program and MIT operations to role.Carter Stubbs has been appointed MIT’s Institute auditor, effective Nov. 2.
Stubbs, who currently serves as audit assistant director for IT Audit and Advisory Services, has been a member of the MIT community for more than 11 years and brings deep institutional knowledge, highly salient management experience, and a forward-looking vision to the role. Stubbs will succeed Michael Moody, who has served as Institute auditor for 12 years and will retire from MIT in October.
Executive Vice President and Treasurer Glen Shor announced the news today in a letter to MIT’s Academic Council.
“Carter stood out in a competitive field of candidates thanks to his impressive audit and IT expertise, collaborative leadership style, and robust understanding of MIT’s complex operations,” Shor says. “He has earned the trust and admiration of colleagues inside and outside the division and is well-positioned to write its next chapter.”
As Institute auditor, Stubbs will lead a team of internal auditors responsible for independently evaluating MIT’s academic, research, and administrative processes, including operations at Lincoln Laboratory. He will oversee a comprehensive, risk-based audit and advisory program spanning financial, operational, compliance, and technology reviews across the Institute.
The MIT Audit Division maintains a dual reporting structure to ensure its independence. Stubbs and the audit team work for the MIT Corporation Risk and Audit Committee, but receive administrative support from the MIT Office of the Executive Vice President and Treasurer.
“Carter’s strong technical command of IT auditing and hands-on experience auditing and advising on major systems implementations will be especially valuable as the Institute continues to advance its business and digital transformation roadmap,” says Pat Callahan, the chair of the Risk and Audit Committee. “The committee will be well-served by his experience with our current audit program, his demonstrated leadership and sound judgment, and his wide-ranging knowledge of the Institute.”
Stubbs joined MIT in 2015 as a senior auditor of information technology, steadily assuming increasing responsibility for information technology, data analytics, and advisory services. He now leads those functions for the Audit Division and serves on the division’s management team. Working closely with the Institute auditor, Stubbs shapes annual risk assessment work, audit planning, and broader division strategy while managing the oversight of complex engagements; contributing to quality assurance and advancing the division’s capabilities; and proactively responding to emerging institutional needs. Stubbs collaborates with leaders from across MIT’s academic, research, administrative, and technology units, including Lincoln Laboratory, and facilitates communications with Institute governance.
During his time at MIT, Stubbs has built an extensive network of partners and developed a multifaceted understanding of the Institute’s operating model, higher education and research risks, and the leadership judgment necessary to navigate complex institutional matters. He has helped steer cross-Institute efforts involving research data management, artificial intelligence, cybersecurity, and digital transformation. A graduate of the 2025 MIT Leader to Leader program, Stubbs served as an advisor to the MIT Working Group on Artificial Intelligence in Administration and Operations and is a member of the MIT Data Incident Response Team.
“I am honored to serve as MIT’s next Institute auditor,” says Stubbs. “The Audit Division plays an essential role in advancing the Institute’s mission of education and research through independent insight, trusted partnership, and thoughtful perspective on risk. I look forward to building on the division’s strong foundation and helping the Institute navigate an increasingly complex regulatory and risk environment.”
Prior to joining MIT, Stubbs held audit roles at Clean Harbors Environmental Services, Denbury Resources, and PricewaterhouseCoopers, where he developed broad expertise in IT and business process controls across multiple industries. He holds certifications as both a certified internal auditor and certified information systems auditor and earned a BBA in information and operations management from Texas A&M University.
Batteries that safely break down in the GI tract could improve ingestible devices Made from “bioresorbable” materials, the new batteries could power capsules for drug delivery, sensing, and other applications.Using materials safe for human consumption, MIT researchers have created tiny batteries that could be used to power ingestible electronic devices. Such batteries could make the devices safer for patients and minimize the environmental impact of the batteries after they are excreted.
In a new study, the researchers showed that the batteries, which generate 1.84 volts, could power two different types of devices: an RFID tag that can transmit from the stomach, and a capsule that produces a small electrical current that stimulates production of ghrelin, the hunger hormone.
This type of battery, which contains electrodes made from magnesium and molybdenum trioxide, could also be deployed in other ingestible devices for sensing or therapeutic applications, the researchers say.
“For many of the systems we’re developing, we need power, and we power the system through different ways,” says Giovanni Traverso, a professor of mechanical engineering at MIT, a gastroenterologist at Brigham and Women’s Hospital, and an associate member of the Broad Institute of MIT and Harvard. “Often, we use batteries, so the question here was: Could we develop a battery that was bioresorbable, and then apply that across a range of application areas?”
Traverso is the senior author of the paper, which appears today in Nature Chemical Engineering. Former MIT postdoc Mehmet Girayhan Say is the paper’s lead author.
Biocompatible batteries
Over the past decade, Traverso and his collaborators have developed ingestible capsules that can monitor vital signs, deliver a variety of drugs, and detect opioid overdoses.
Not all of these devices require a power source. For those that do, the researchers have powered the devices from an external source that wirelessly transmits power, harvested power from the GI tract, or used small coin batteries. However, those batteries, which usually contain lithium, silver oxide, or other metals, could pose a safety risk if the battery’s protective coating was damaged while traveling through the GI tract.
To create a safer battery and allow the systems to be fully self-contained with no external power needed, the researchers turned to metals that can act as electrodes but are safe for human consumption in small amounts — magnesium and molybdenum trioxide.
“Those materials are known to be relatively safe. That was the biggest driver, thinking about materials that can be tolerated by humans,” Traverso says.
The researchers used magnesium to create the battery’s anode and molybdenum trioxide for the cathode. The battery also contains an ionic liquid gel electrolyte, and the entire system is bioresorbable, meaning that it can be fully broken down and absorbed by the body. The researchers designed two different versions of the battery that could be used for different applications —a disc 7.5 millimeters in diameter and a rectangular bar 24 millimeters long.
To test how the batteries would behave in the GI tract, the researchers first exposed them to a highly acidic solution similar to gastric juice. They found that the batteries function normally for about three days, then their performance begins to slowly decline. Within a few weeks, they break down completely.
The researchers then incorporated the rectangular battery into a degradable device they first reported in 2023, which is designed to deliver a small electrical current to the lining of the stomach. In their earlier work, Traverso’s lab showed that this jolt could stimulate endocrine cells in the stomach to produce ghrelin.
Stimulating ghrelin secretion could prove useful for treating diseases that involve nausea or loss of appetite, such as cachexia (loss of body mass that can occur in patients with cancer or other chronic diseases).
The initial version of that device was powered by two silver oxide coin batteries, similar to those used in FDA-approved ingestible devices. By replacing those with the new magnesium-molybdenum oxide batteries, the researchers made nearly the entire device — with the exception of a printed circuit board — bioresorbable. Any components that aren’t absorbed can be passed through the GI tract and excreted.
In the new study, the researchers showed that new battery was strong enough to generate continuous electrical stimulation for up to three days. Tests in animals showed that 20 minutes of stimulation within the stomach could boost ghrelin levels by about 50 percent.
“What makes this work exciting is that we were able to show that a bioresorbable battery is not just a concept. It can actually power clinically relevant functions inside the gastrointestinal tract and then simply dissolve,” Say says.
Battery-powered communication
The researchers then incorporated the battery into a RFID device, which they designed to help patients adhere to their medication schedules. This capsule can transmit its location from within the GI tract via a bioresorbable RFID tag made from molybdenum and cellulose.
An earlier RFID system, known as SAFARI and reported by Traverso’s lab in January, used passive RFID tags, powered by harvested energy, which limits the communication range.
In the new study, tests in animals showed that RFID tags could be effectively powered by a disc-shaped bioresorbable battery. With the new battery, the device could transmit continuously from the GI tract, and with a longer range (up to 1.5 meters).
The researchers are now planning a clinical trial for the SAFARI system, which they expect will begin in about two years. Such systems could not only be safer for patients, but also would reduce the environmental impact of batteries that would eventually be excreted into the sewage system.
“The benefits are twofold: one, the ability to be bioresorbable, but also the potential to minimize environmental impact because the materials will be degraded in the environment as well,” Traverso says.
The research was funded by Novo Nordisk, the Karl van Tassel Career Development Professorship, MIT’s Department of Mechanical Engineering, the Brigham and Women’s Hospital Division of Gastroenterology, and the U.S. Advanced Research Projects Agency for Health (ARPA-H).
Unmasking “zombie cells” in aging tissue with an AI-powered barcodeTracking down senescent cells, which accumulate as we age, could help diagnose age-related disorders and guide researchers working on new treatments.As we age, some of the cells in our body enter a state of senescence, in which they stop dividing but do not die. Those senescent cells can contribute to age-related disorders such as cancer, tissue degeneration, and inflammatory diseases.
In an advance that could lead to better ways to diagnose and treat those diseases, MIT researchers have developed a noninvasive way to detect biomarkers of senescence. Their method is based on Raman microscopy, which can reveal the biochemical composition of cells without harming them.
By combining Raman microscopy with gene expression data at single-cell resolution from the same cells, the researchers were able to identify unique “barcodes” that can be used to quickly identify senescent cells. This study was done in mouse cells, but the researchers are now working on adapting it for use with human tissue.
“You can imagine that one day we may develop an endoscope that can look inside your body and identify cellular senescence,” says Jeon Woong Kang, an MIT research scientist and one of the senior authors of the study.
The research is part of a National Institutes of Health initiative called the Cellular Senescence Network, which is pursuing a deeper understanding of senescence in hopes of developing therapies that could combat some of the tissue-damaging effects of senescent cells.
Peter So, director of the MIT Laser Biomedical Research Center (LBCR) and an MIT professor of biological engineering and mechanical engineering, and Jian Shu, an assistant professor at Massachusetts General Hospital (MGH) and Harvard Medical School, and an associate member of the Broad Institute and Ragon Institute, are also senior authors of the paper, which appears today in Nature Aging. Lead authors of the paper are Ke Zhang, an instructor at MGH and Harvard Medical School; Xingjian Chen, a postdoc at MGH and Harvard Medical School; Francesco Monticolo, a postdoc at MGH and Harvard Medical School; and Salvatore Sorrentino, a postdoc at MIT.
Characterizing senescence
Cell senescence is often triggered by DNA damage, which leads to an irreversible arrest of the cell cycle. These cells don’t die, but they undergo significant changes to their shape, metabolic processes, and gene expression profiles.
The immune system is responsible for clearing out these “zombie cells,” but as people age, this process becomes less efficient. When senescent cells accumulate, they may contribute to sagging skin, muscle weakness, and chronic conditions such as osteoarthritis and type 2 diabetes.
Cellular senescence also has beneficial effects, playing critical roles in embryonic development and tissue regeneration.
“Senescence is not just a pathological condition,” So says. “The idea behind the NIH Cellular Senescence Network is to take a very comprehensive approach to understand senescence and identify senescent cells, because it plays a role in so many normal physiological conditions and many pathological conditions.”
Scientists have already identified a few biomarkers for senescence, including two proteins called p16 and p21, which are involved in halting the cell cycle. However, those proteins can only be identified using a process that ends up destroying the cells.
The MIT team wanted to find a way to noninvasively identify senescent cells using Raman microscopy. Unlike RNA-sequencing, which consumes the cells as it analyzes them, Raman microscopy is a nondestructive technique that reveals the chemical composition of tissues or cells by shining near-infrared or visible light on them.
In the new study, the researchers used Raman microscopy in conjunction with spatial RNA sequencing — a technique that reveals where genes are active within a tissue — to identify new markers of senescence. By combining these two techniques, they were able to generate a much broader picture of the distinctive features of senescent cells, including gene expression levels, spatial location, and other biochemical information.
“Our idea was to look at many different features to characterize senescence. That’s why we wanted to combine both single-cell gene expression and Raman microscopy, so that we can characterize the senescence from two complementary views,” Shu says.
Using both methods of analysis, the researchers examined skin and lung tissue from 2-month-old mice and 26-month-old mice.
One of the most dramatic changes seen in both lung and skin cells was an increase in lipid synthesis in older cells, along with accumulation of lipids. How this affects the physiology of the cells is not yet known, the researchers say.
The researchers also found some effects that were specific to each tissue. In senescent skin cells, they discovered that cellular pathways associated with muscle contraction and with remodeling of collagen and the extracellular matrix were significantly affected. And in aged lung tissue, they found increased activity of genes involved in immune activation and inflammation.
In future work, the researchers hope to study further what role these changes play in senescent cells.
Identifying senescent cells
Using these data, the researchers were able to identify combinations of Raman peaks that correlate with senescence. These peaks, which represent specific chemical bonds, are linked to the presence of certain lipids, proteins, or other molecules.
“Combining the most important Raman features with the most important gene signatures, we were able to create a barcode that can help us to identify senescent cells in a more unbiased way,” Sorrentino says. “Using this barcode, we can focus on a few Raman bands that emerged as the most informative in this work.” Using these bands, it could be possible to identify senescent cells by looking for just those bands of the Raman spectrum. This could help to enable diagnostics that would detect cells that have become senescent.
To help make that possible, the researchers are now working on a higher-speed version of their Raman imaging system. Currently, it takes about 30 hours to analyze a tissue sample about one square millimeter in size, but they hope to develop a system that can quickly pick out the Raman barcodes they identified from larger samples.
The research was funded by the National Institutes of Health and Massachusetts General Hospital.
MIT researchers are mapping extreme weather risks — and building tools to act on themThe Climate Grand Challenges “New World of Weather” project shows how modeling, planning tools, and infrastructure analysis are translating research into real-world resilience.Warming temperatures are fueling more extreme weather-related events — catastrophic floods, severe hurricanes and cyclones, and wildfires exacerbated by drought. But the tools used by local communities, emergency and public safety agencies, and insurance and risk markets have not kept pace with the up-to-date data and modeling for accurately predicting how these events will evolve.
Addressing that shortcoming was one of five research areas selected for MIT’s 2022 Climate Grand Challenges, an ambitious effort to accelerate science-based solutions to climate problems. The area, titled “Preparing for a New World of Weather and Climate Extremes,” focuses on tools to help evaluate a location’s vulnerabilities to flooding, cyclones, humid heat waves, or other climate-related events.
Four years later, collaborations among more than 40 faculty and student researchers on Weather and Climate Extremes projects have yielded 29 published research papers and digital tools and datasets that are already in use or close to deployment. Individual projects cut across forecasting, risk assessment, on-the-ground planning, and resilient infrastructure.
“Communities across the United States and around the world are already confronting the consequences of extreme weather,” says Evelyn Wang, MIT’s vice president for energy and climate, whose office has been funding and supporting all of the Grand Challenges since 2024. “Through the Climate Grand Challenges, an interdisciplinary team at MIT is advancing the science, technologies, and practical strategies needed to help communities anticipate these risks and build greater resilience.”
Reducing scientific uncertainties
Paul O’Gorman, the Robert R. Shrock Professor of Earth and Planetary Sciences at MIT and co-lead of Weather and Climate Extremes, is refining the science behind forecasting extreme weather events, such as last year’s major flooding events in Central Texas and in Pakistan. “There have been a lot of unprecedented, record-breaking events,” he says, “and we want to understand how they are changing as the climate warms, and how they’re changing in different regions.”
One aspect that his group has been examining is the relationship between extreme rainfall events and a warming climate. Climate models predict that extreme rainfall increases less in summer than other seasons in much of the United States and Europe. O’Gorman’s team found that these seasonal shifts stem from not only how much water is in the atmosphere, which is measured by specific humidity, but also how close it is to saturation, which is measured by relative humidity. “We found that changes in relative humidity played a big role, which was something that hadn’t been appreciated before, and something we need to take into account,” he says.
Modeling is challenging: Relative humidity depends on air circulation, how fast land warms relative to the ocean, soil moisture, and vegetation. “It’s a complex story, but this helps us understand precipitation patterns,” O’Gorman says.
Kerry Emanuel, MIT professor (post tenure) in the Department of Earth, Atmospheric and Planetary Sciences who was also a co-lead of Weather and Climate Extremes, is researching better ways to estimate the risks of extreme hurricanes and severe convective storms, such as thunderstorms and tornadoes. “For hurricanes, we’re pretty much there. We can reproduce the statistics of real hurricanes extremely well just using coarse-grained weather data that has no hurricanes in it,” he says. But for severe convective storms, “we’re not close to being there,” and these storms “in the last decade have cost more lives and more damage than hurricanes.”
Research on the physics of storms is already influencing practice, Emanuel notes. For example, a company called First Street uses Emanuel’s methods to guide local governments, insurers, developers, and real-estate platforms on environmental risk for every piece of private property in the United States.
Improving resilience
Another phase of the Grand Challenge, led by Miho Mazereeuw, an associate professor in MIT’s Department of Architecture and a leading expert on resilient design, translates the information from scientific modeling and data collection into tools for on-the-ground planners. For example, working with leaders and community members in Boston and Broward County, Florida, the team has developed interactive web-based tools that make it easier to plan for impacts such as flooding over a broad range of scenarios.
“When an extreme event happens, there is a gap between scientific knowledge and actionable public information,” says Aditya Barve, a research scientist in Mazereeuw’s Urban Risk Lab. This happens at various levels — from getting real-time information out to people when they need it to collecting data to enable long-term planning to disseminating those plans to communities. “The idea is to target the gap through tools in community emergency data collection, proactive recovery planning, and AI-assisted tools for at-scale visualization of future climate impacts, so that communities are prepared when something happens.”
The team has worked on making flood modeling outputs usable by a wider range of stakeholders, especially where the need for specialized software or technical expertise can slow decision-making across city departments. “Users can ask practical questions, such as which schools are likely to stay driest across different flood scenarios, and receive answers grounded in flood models and city datasets within seconds,” Barve says.
As for recovery after extreme weather events, Mazereeuw points out that most municipalities have an emergency response plan, but few create a recovery plan that includes housing before the event. But, she says, if communities plan how recovery can lead to a better future for the city, they can better leverage emergency relief funding that becomes available. “In almost all cases, the resources available after a disaster are much larger,” she says. “By having a plan in place, those resources can fit the vision of the place moving forward.”
Optimizing energy infrastructure
Associate Professor Michael Howland is working to analyze the impacts of extreme weather on energy infrastructure with a team that includes Jessika Trancik, a professor in the MIT Institute of Data Systems and Society (IDSS), and Saurabh Amin, the Edmund K. Turner Professor in Civil Engineering at MIT. The team is particularly looking at impacts on the electrical power system and ways to optimize decisions on the placement and sizing of new energy infrastructure.
Howland, who is the Jeffrey Cheah Career Development Professor of Civil and Environmental Engineering at MIT, says electrical power systems are increasingly being altered by two things at the same time: first, the proliferation of renewable energy and storage technologies, and second, large-scale changes in weather and extreme events driven by climate change. “Each of these would independently push our electrical power system potentially outside of what we are used to, and their combined, synergistic impacts could be even larger because they are occurring simultaneously,” he says.
Bringing climate modeling and grid-infrastructure work together has accelerated practical insights into how we can adapt to climate change while simultaneously mitigating it, Howland notes. Such modeling can also help to inform infrastructure decisions in ways that may not be obvious. For example, he says, their optimization model for the siting of power resources in Texas resulted in placing a number of wind power plants along the Gulf Coast. “If you look at an average wind speed map,” he says, “you would say this doesn’t make much sense because it’s really windy in northwest Texas on average, and much less windy along the Gulf Coast.”
But it turns out that the typical daily cycle of winds is complementary, so that wind farms distributed between both locations tend to smooth each other out and to better complement solar power generation, easing burdens on the grid. Now, “we’re trying to take it further not just by smoothing the generation, but actually aligning it with the time- and space-varying electricity demand so that we can reduce storage, transmission, and other backup generation needs,” he says.
This work is ongoing, and the hope is that it will lead to products that can directly help utility grid planners and regulators with actionable information about the siting and sizing of various electrical infrastructure resources, Howland says. “We want to continuously push on model realism and accuracy to eventually make it more of a practical and useful tool for grid planners.”
Emanuel adds that the Weather and Climate Extremes Grand Challenge, and other projects working to pinpoint the kinds of risks that can be expected from a changing climate, have produced a great deal of specific and detailed information that could guide political, economic, and civic decision-making. Applying it in the real world can be slow — “like steering a supertanker,” he says — but progress will come.
A new chapter for MIT ReadsA new focus on fiction and memoir aims to help the MIT community celebrate the power of storytelling and strengthen social connection.As it marks its 10-year anniversary, MIT Reads is being reimagined for the age of artificial intelligence.
Recognizing the need to foster social connection and a sense of our shared humanity, the popular MIT Libraries’ program will turn its focus to fiction and memoir, and to the particular power of stories to help us understand ourselves and our place in the world.
“At MIT, we spend a great deal of time on imagining and building for the future. Reading fiction prompts us to think about how what we build might change us,” says MIT Libraries Director Chris Bourg. “Reading together also gives us the increasingly rare opportunity for both individual reflection and shared connection.”
MIT Reads is also evolving with MIT as it explores AI’s influence on the education landscape and the social fabric of the Institute. The value of collective reading, reflection, and discussion has never been more relevant.
A recently released report from MIT’s Ad Hoc Committee on AI Use in Teaching, Learning, and Research Training urges strengthening social connection and personal well-being, citing MIT Reads as a way to “engage many more people across campus in conversation about shared norms and why community matters.”
Launched in 2016, MIT Reads was designed to foster empathy, understanding, and belonging within the campus community. Each selected book is accompanied by programming such as talks by the featured author, panel discussions, and small-group conversations facilitated by library staff.
The program’s reach extends well beyond MIT. Most author events are open to the public and streamed online, and videos of MIT Reads talks have been viewed more than 5,000 times.
To mark this new era of MIT Reads, President Sally Kornbluth has selected the fall 2026 book “Exhalation,” by Ted Chiang. “Exhalation” is a bestselling collection of short stories, named one of The New York Times’ best books of 2019. In it, Chiang creates thought-provoking science fiction scenarios involving robots, time travel, and alternate universes, while exploring timely issues of identity, free will, language, and the impacts of technology.
“With the stories in his 2019 ‘Exhalation’ collection, Ted Chiang offered an uncanny preview of many issues we’re grappling with now concerning technology, particularly the relationship between humans and artificial intelligence,” says Kornbluth. “He raises deep questions about the future that humans and machines will share and offers provocative ideas and possibilities. I’m delighted that MIT Reads will give us the opportunity to explore his work together.”
“MIT is not alone in grappling with these big questions around technology and its relationship with humanity,” adds Bourg. “These questions call for a much wider discussion, and we invite readers everywhere to join us.”
In addition to its discussion as part of MIT Reads, students in the first-year advising seminar 21.A01 (Reading Great Books with Compass) will be reading “Exhalation” this fall; the class is part of the Compass initiative designed by faculty from across the School of Humanities, Arts, and Social Sciences and supported by the MIT Human Insight Collaborative.
A new understanding of how enzymes influence bacterial protein productionNovel research expands scientific understanding of how RNA shapes the reading of genetic information.Antimicrobial resistance is one of the most pressing global health and development challenges of our time. Bacteria and other pathogens are rapidly developing resistance to existing treatments, making infections harder to treat. Without new approaches, minor inconveniences today, such as routine surgeries or even a paper cut, could become life-threatening tomorrow.
Now, an international group of scientists reports the discovery of aminovaleramididine synthetase (AvaS), the first identified pyridoxal phosphate (PLP)-dependent enzyme responsible for producing a chemical modification linked to how bacteria respond to metabolic stress. This discovery sheds new light on how bacteria use RNA modification to control protein production, opening new avenues to study bacterial adaptation and identify future targets and better strategies for developing antimicrobial therapeutics.
The work was led by researchers from the Singapore-MIT Alliance for Research and Technology’s Antimicrobial Resistance interdisciplinary research group (SMART AMR), alongside collaborators from MIT, Nanyang Technological University in Singapore, and institutions in the United States, Poland, and France.
“While many RNA modifications have been known for decades, researchers are still uncovering the full extent of their roles. The discovery of AvaS opens a previously unknown chapter in RNA biology and is an important step forward in our understanding of processes relevant to antimicrobial resistance,” says Professor Peter Dedon, co-lead principal investigator at SMART AMR, professor of biological engineering at MIT, and co-corresponding author of a new paper on the work. “As we continue to map the RNA modification landscape, we expect many more discoveries with meaningful implications for infectious disease, antimicrobial resistance, and fundamental biology.”
Bacteria can develop resistance to antibiotics using various strategies, many of which depend on the bacteria’s ability to regulate which proteins are made, when they are made, and how accurately they are produced — whether by pumping drugs out of their cell, creating enzymes that break down drugs, or developing new cell processes to avoid the antibiotics’ target.
To build these proteins, bacteria rely on RNA molecules to read genetic instructions and direct protein production. Among these RNA molecules are transfer ribonucleic acid (tRNAs), a specialized class of RNA that acts as molecular delivery vehicles bringing chemical “stickers” to help bacteria control how proteins are made in response to stress and changing conditions such as exposure to antibiotics.
In the open-access paper, “Pyridoxal phosphate-dependent biosynthesis of aminovaleramide by AvaS in tRNA,” published Sept. 9 in Nature Chemical Biology, the researchers described their discovery of the new enzyme and identified it as being responsible for creating a tRNA chemical modification known as aminovaleramide cytidine (ava2C) in Pseudomonas aeruginosa, a harmful bacterium responsible for a range of serious human infections such as pneumonia and sepsis. While ava2C had previously been detected in several bacteria and plants, the enzyme responsible for producing this modification was previously unknown.
Using SMART AMR’s high-throughput liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based RNA modification profiling platform, the team systematically screened thousands of P. aeruginosa mutants and discovered AvaS. The researchers also confirmed the presence of ava2C in other organisms, including the bacteria Acinetobacter baumannii and Vibrio cholerae, as well as the plant Arabidopsis thaliana.
The research revealed that AvaS uses PLP, a vitamin B6 derivative, to convert a known modification, lysidine (k2C), into ava2C; marking the first time that a PLP-dependent enzyme has been linked to tRNA modification. Traditionally, PLP-dependent enzymes have only been associated with amino acid metabolism and related biochemical pathways.
The research findings revealed a few important insights about PLP-dependent enzymes. First, the discovery establishes PLP-dependent enzymes as a previously unrecognized class of tRNA-modifying enzymes, expanding the known chemical mechanisms, such as methylation, thiolation, and isomerisation, that bacteria use to regulate protein production. Second, it reveals an entirely new biological function of PLP-dependent enzymes, demonstrating that they can directly modify tRNA in addition to their well-established roles in metabolic processes.
The research also found that ava2C changes how bacteria read genetic codes, enabling the bacteria to produce protein faster and more efficiently while helping them adapt to metabolic and oxidative stress.
“Our discovery has revealed, for the first time, that PLP-dependent enzymes can directly modify tRNA, expanding our knowledge and understanding of RNA-modifying chemistry,” says Jingjing Sun, research scientist at SMART AMR, first author, and co-corresponding author of the paper. “This opens up new avenues for studying bacterial adaptation and developing new and more effective strategies to overcome drug-resistant bacteria.”
Building on this discovery, the SMART AMR team plans to investigate how ava2C affects bacterial stress responses and metabolism and explore how the modification can be disrupted or prevented. Understanding this process could uncover new ways to fight harmful bacteria and develop future antimicrobial therapeutics. With ava2C also being observed in plants, future studies could explore whether other living organisms use similar biological tools to produce certain chemical modifications and how ava2C influences the way proteins are built beyond bacteria.
More broadly, this work highlights the strength of SMART AMR’s first-of-its-kind epitranscriptomics platform as a powerful engine in discovering more unknown RNA-modifying enzymes at scale. This capability could also support biotechnology and pharmaceutical researchers in finding new drug targets and developing better treatments, particularly as bacteria continue to develop resistance against existing drug treatments.
The research conducted at SMART is supported by the National Research Foundation Singapore under its Campus for Research Excellence and Technological Enterprise program.
Fueling a return journey from MarsPhD candidate Lanie McKinney is building technology to convert the Red Planet’s atmosphere into propellant for bringing astronauts home.When Lanie McKinney was 3 years old, her parents stopped at a massive meteor crater during a road trip through the U.S. Southwest. As they prepared to leave, McKinney began to protest.
“I want to wait here for the next one,” she told them.
She didn’t yet understand that another meteor wasn’t likely to land in exactly the same spot. But the story, which her parents still tell, captures a fascination that has remained with McKinney throughout her life.
“I just always remember being captivated by space and what is out there,” she says.
Today, McKinney is entering her fifth year as a PhD candidate at MIT, where she works in the Aerospace Plasma Group with Esther and Harold E. Edgerton Associate Professor Carmen Guerra-Garcia. McKinney’s research focuses on developing technologies that could help humans explore Mars.
One of the challenges of sending humans to the Red Planet is figuring out how to supply them once they arrive — including how to enable their journey back home. Rather than transporting everything from Earth, McKinney is interested in using the resources already available on the planet, a concept known as in-situ resource utilization, or ISRU.
“If we don’t build gas stations on Mars, it will be very difficult to get humans back to Earth,” she says. “We’re going to need some way to produce the propellant on site.”
McKinney’s research uses cold plasma to convert carbon dioxide, which is abundant in the martian atmosphere, into oxygen and carbon monoxide, a technology that could eventually be used to produce life support and propellant on Mars.
An Oklahoma native, McKinney earned her bachelor’s at the University of Tulsa, where she studied physics and applied mathematics. She had initially expected to pursue astrophysics, but a summer research internship at the University of Colorado at Boulder introduced her to plasma physics through a project involving dusty plasmas in the lunar environment.
“I thought it was an incredibly interesting problem,” she says.
At MIT, McKinney has developed a small reactor that can convert carbon dioxide into oxygen and other products. The challenge now is separating out the oxygen before it recombines.
“We can actually perform the conversion step really well,” she says. “But what happens in a plasma is we convert it, and then we get a mixture that needs to be separated.”
Her current work pairs the plasma reactor with an oxygen-selective membrane designed to extract oxygen rapidly. The integration process isn’t well-understood, leaving McKinney and her colleagues with questions about how the reactive plasma environment will affect the membrane.
“We are not entirely sure what we will see,” she says.
For McKinney, the possibility of connecting laboratory experiments to future human missions is what makes the work particularly rewarding.
“I get to work in a really cool lab and develop exciting experiments,” she says. “I get ownership over an entire experimental system, and then I get to connect that to performance requirements for a future Mars system. That’s just the dream.”
That same philosophy has shaped McKinney’s work beyond her thesis. Through MIT’s Space Resources Workshop, she has participated in NASA competitions focused on sustaining humans in space. Her first competition involved designing a self-sustaining Mars mission for 10 years.
“I had no clue what was going on,” she says. “I didn’t know anything about space systems. So, my mentality was, let me jump in and learn.”
She later co-led MIT’s CERBERUZ team for NASA’s LunaRecycle Challenge, which asked teams to develop ways to recycle waste on missions to the moon and deep space. The MIT team recently won first prize in Phase 2, receiving $775,000 in awards for a system that grinds mixed trash into powder that can be reused via injection molding to make spare parts and 3D-printing filament.
Another project McKinney enjoyed brought together engineers and architects through MAS.S66/4.154/16.89 (Space Architecture) to tackle a different problem: how to protect lunar habitats from radiation using only resources available on the moon. The students’ solution was to produce cast bricks from lunar regolith that could be stacked without mortar or another binder. For McKinney, the project demonstrated the value of bringing together people with different expertise.
“The kinds of innovative solutions that can be discovered when you work on a team that brings together different expertise and experiences was one of the project’s major takeaways,” she says.
The experience reflects a broader lesson McKinney has taken from MIT: Research may involve focused individual work, but solving the problems of human space exploration will require collaborations across disciplines.
“I feel like I have learned so much from being a part of these different teams,” she says.
McKinney sees that collaboration as essential to the future she hopes to help build. Reaching the Moon and Mars is only the first step: “What comes next is building up a permanent presence so that we can do amazing science and be really effective at exploration,” she says.
McKinney’s fascination with exploration extends beyond her research. She is an avid hiker and mountaineer, having grown up hiking with her family in the Rockies. She recently completed a mountaineering course in Alaska and summited Mount Baker in the Cascade Range. She sees a connection between those adventures and the curiosity that first drew her to space.
“I love to explore and go on adventures,” she says. “And space is the ultimate thing you could explore.”
That curiosity has also shaped how McKinney approaches her work. When she arrived at MIT from the University of Tulsa, she initially felt intimidated.
“I thought that it was a fluke that I’d gotten in,” she says. “I was very nervous that I was not going to measure up to the environment.”
Over time, she learned to approach unfamiliar problems by asking questions and committing fully to whatever interested her.
“If something interests you, try it and go all in,” she says.
Meet the 2026 tenured professors in the School of Humanities, Arts, and Social SciencesFaculty members granted tenure in Comparative Media Studies/Writing, Economics, Political Science, and Theater.In 2026, five faculty were granted tenure in the MIT School of Humanities, Arts, and Social Sciences.
Volha Charnysh is an associate professor in the Department of Political Science. She studies the role of identity in state-building and economic development and the effects of violence. Her first book, “Uprooted: How post-WWII Population Transfers Remade Europe” (Cambridge University Press, 2024), focuses on the enduring consequences of mass displacement and resulting cultural heterogeneity. She received her PhD from Harvard University in 2017 and joined the MIT faculty in 2018.
Grisha Coleman is a full professor in the Music and Theater Arts Section. Her research explores tensions between our physiological, technological, and ecological systems; human movement, our machines, and the places we inhabit. Her practice engages an interdisciplinary approach to these explorations. She earned an MFA in music composition and integrated media from California Institute of the Arts. She joined the MIT faculty in 2026.
Tung-Hui Hu is an associate professor in the Comparative Media Studies/Writing program. A poet and a scholar of digital media, he is the author of five books, most recently “Digital Lethargy: Dispatches from an Age of Disconnection” (MIT Press, 2022), “A Prehistory of the Cloud” (MIT Press, 2015), and “Greenhouses, Lighthouses” (Copper Canyon Press, 2013). Hu is interested in how concepts such as race and normal language became measurable, governable objects in the form of datasets. He earned a BA in comparative literature from Princeton University, an MFA in creative writing from the University of Michigan, and a PhD in film studies from the University of California at Berkeley. He joined the MIT faculty in 2026.
Tobias Salz is an associate professor in the Department of Economics. He works in the field of industrial organization and studies how digital platforms and other intermediaries shape competition and market outcomes. The applications of his research span digital markets, transportation, and artificial intelligence, and often combine economic theory with novel data and field experiments. His recent work examines market power in web search, personalized platform pricing, and how human experts and AI can work together in medical diagnosis. He received his PhD in economics from New York University in 2016 and joined the MIT faculty in 2019.
Christian Wolf is an associate professor in the Department of Economics. His research is primarily concerned with the question of how monetary and fiscal policy can be used to stabilize the economy. A key aim of his work is to learn as much as possible about such stabilization policy directly from micro- and macroeconomic data, rather than through reliance on structural models. Wolf joined the MIT faculty in 2021 after earning his PhD in economics from Princeton University.
MIT School of Engineering faculty and staff receive awards in spring 2026Faculty members and researchers were honored in recognition of their scholarship, service, and overall excellence.Each year, faculty and researchers across the MIT School of Engineering are recognized with prestigious awards for their contributions to research, technology, society, and education. To celebrate these achievements, the school periodically highlights select honors received by members of its departments, institutes, labs, and centers. The following individuals were recognized in spring 2026:
Faez Ahmed, the Esther and Harold E. Edgerton Associate Professor in the Department of Mechanical Engineering, received a 2025 Air Force Office of Scientific Research Young Investigator Program Award. The award provides early-career U.S. scientists and engineers with up to $450,000 over three years to support innovative research.
Navid Azizan, the Alfred Henry (1929) and Jean Morrison Hayes Career Development Professor and an associate professor in the Department of Mechanical Engineering, has received a National Science Foundation (NSF) CAREER Award. The Faculty Early Career Development (CAREER) Program is a foundation-wide activity that offers the NSF’s most prestigious awards in support of early-career faculty who have the potential to serve as academic role models in research and education and to lead advances in the mission of their department or organization.
Yet-Ming Chiang, the Kyocera Professor of Materials Science and Engineering in the Department of Materials Science and Engineering, was named a Boston Globe Tech Power Player 2026. The annual list highlights the impact of local leaders on technology and business.
Samantha Coday, an assistant professor in the Department of Electrical Engineering and Computer Science, received a 2025 ARPA-E IGNIITE Award. The award aims to support early-career innovators seeking to convert disruptive and unconventional ideas into impactful new technologies across the full spectrum of energy applications.
Srini Devadas, the Edwin Sibley Webster Professor and a professor in the Department of Electrical Engineering and Computer Science, received the 2026 ACM-IEEE CS Eckert-Mauchly Award, which recognizes contributions to computer and digital systems architecture.
Joel Emer, professor of the practice in the Department of Electrical Engineering and Computer Science, received the 2026 ACM SIGARCH/IEEE TCCA Influential Paper Award. This award recognizes the paper from the ISCA Proceedings 20 years earlier that has had the most impact on the field (in terms of research, development, products, or ideas) during the intervening years.
Chuchu Fan, an associate professor in the Department of Aeronautics and Astronautics, received the IEEE Robotics and Automation Society Early Academic Career Award in Robotics and Automation. The award recognizes academics who have made an identifiable contribution or contributions that have had a major impact on the robotics and/or automation fields.
Yoel Fink, the Danae and Vasilis (1961) Salapatas Professor in the Department of Materials Science and Engineering, received the American Physical Society Andrei Sakharov Prize, which recognizes outstanding leadership and achievements of scientists in upholding human rights.
Aristide Gumyusenge, an assistant professor the Department of Materials Science and Engineering, received the 2026 Early Investigator Award from the American Chemical Society's Polymeric Materials: Science and Engineering Division. Honorees are chosen from early-career emerging leaders who have made significant contributions in their respective fields within polymer materials science and engineering.
Paula Hammond, dean of the School of Engineering and an Institute Professor in the Department of Chemical Engineering, received the AIChE 2026 John M. Prausnitz Institute Lecture Award. The Prausnitz AIChE Institute Lectureship is awarded to a distinguished member of AIChE who has made significant contributions to chemical engineering in their field of specialization.
Robert Langer, the David H. Koch (1962) Institute Professor in the departments of Biological Engineering (BE) and Chemical Engineering, received the 2026 Robert A. Welch Award in Chemistry from the Welch Foundation. This prestigious prize recognizes important research contributions that have had a significant and positive impact on humankind.
Gareth McKinley, the School of Engineering Professor of Teaching Innovation and a professor in the Department of Mechanical Engineering, was elected to the National Academy of Sciences. Awardees are recognized by their peers for their outstanding contributions to research in the natural and social sciences.
Farnaz Niroui, Robert J. Shillman (1974) Career Development Professor in Electrical Engineering and Computer Science and an associate professor, received the Rising Star of Microsystems Award from the Transducer Research Foundation, which is intended to highlight the next generation of innovators shaping the future of microsystems, microfabrication, MEMS, micro/nanomanufacturing, and closely related fields.
Tomás Palacios, the Clarence J. LeBel Professor in the Department of Electrical Engineering and Computer Science, received the 2026 Quantum Devices Award from the International Symposium on Compound Semiconductors for significant advancements in wide bandgap semiconductors and nanostructures to improve electronics and pave the way for heterogeneous integration with silicon CMOS.
Ritu Raman, the Eugene Bell Career Development Professor of Tissue Engineering and an associate professor in the Department of Mechanical Engineering, received a Grainger Foundation Frontiers of Engineering Grant from the National Academy of Engineering. The grants provide seed funding for participants at U.S.-based institutions to support further pursuit of new interdisciplinary research and projects stimulated by interactions at the U.S. Frontiers of Engineering symposium.
Lindsey Raymond, an assistant professor in the departments of Electrical Engineering and Computer Science and of Economics, was named a 2025 Early Career Fellow by Schmidt Sciences AI2050. AI2050 issues awards to enable and encourage bold and ambitious research, often multidisciplinary, that is typically hard to fund but socially beneficial. Awards are given for exceptional work tackling one or multiple items from a working list of hard problems.
Daniela Rus, the Panasonic Professor and a professor in the Department of Electrical Engineering and Computer Science, received the 2026 High-Tech Prize of the Bavarian Minister-President. This prize is the most highly endowed award for technology and engineering in Germany.
Afreen Siddiqi, a research scientist in the Department of Aeronautics and Astronautics, received a 2026 Guggenheim Fellowship. Working across 55 disciplines, the fellows were selected from almost 5,000 applicants for “prior career achievement and exceptional promise.”
Vincent Sitzmann, an associate professor in the Department of Electrical Engineering and Computer Science, received both a CAREER Award from the National Science Foundation and the Pattern Analysis and Machine Intelligence (PAMI) Young Researcher Award from the IEEE Computer Society. The PAMI Young Researcher Award is given to a researcher within seven years of completing their PhD for outstanding early career research contributions.
Loza Tadesse, the Latham Family Career Development Professor and an assistant professor in the Department of Mechanical Engineering, was named to Chemical & Engineering News’ 2026 Talented 12. This annual list recognizes early-career researchers who are rising stars in chemistry, selected for their innovative work and growing impact in the field.
Kripa Varanasi, the Maher A. Elmasri Professor of Mechanical Engineering, accepted a United Nations World Intellectual Property Organization Global Award on behalf of his startup, AgZen. The award recognizes the company’s efficient agrochemical spraying patent portfolio.
Understanding the world, from the Cold War to the age of AIFor 75 years, the Center for International Studies has brought together social scientists, engineers, and practitioners to understand global change, shape public debate, and address generational challenges.At a moment when global alliances are shifting, technological change is accelerating, and the boundaries between science and geopolitics are dissolving, understanding the world demands new ways of thinking.
For 75 years, the MIT Center for International Studies (CIS) has helped meet that challenge — bringing together engineers, social scientists, and policy practitioners to confront the most pressing global challenges of their time. From developing the foundations of modern international security to redefining how the United States engages with the world, CIS has not only studied global affairs, it has helped shape them.
What distinguishes CIS is not just the scope of its work, but the way it approaches it.
At MIT, international studies does not sit apart from science and technology, it is embedded within it. This proximity has enabled generations of scholars to tackle geopolitical problems with tools and perspectives rarely found in traditional academic and policy environments.
“Being situated within the world’s leading technical institution enables a lot of exciting possibilities,” says Evan Lieberman, the director of CIS and the Total Professor of Political Science and Contemporary Africa. “We focus on critical problems in international development and security — always with an eye towards the challenges and opportunities presented by technological change. Beyond that, a big part of our mission is to provide global perspectives and engagement avenues relevant to scientists and engineers.”
Established during the dawn of the Cold War, CIS pioneered a new understanding of global power: that science, technology, and geopolitics were becoming deeply intertwined. From the beginning, it convened faculty across disciplines — economics, political science, engineering, and beyond — setting a template that has since become a model for institutions around the world. Over the decades, this approach has produced an outsized impact.
In 1961, a memorandum to President John F. Kennedy from MIT economist Max Millikan — the inaugural director of CIS — helped inspire the creation of the Peace Corps, fundamentally reshaping how the United States engages in global development.
CIS scholars such as Lincoln Bloomfield and William “Bill” Kaufman played a central role in establishing security studies as a rigorous academic field in the late 1950s. Less than two decades later, Jack Ruina and George Rathjens founded the center’s Arms Control and Defense Policy Program (now known as the MIT Security Studies Program), which has influenced generations of policymakers and trained generations of scholars.
The study of modernization and political development has also long been central to the work of the center, with notable luminaries such as Lucian Pye and Myron Weiner helping to lead the way.
A legacy of global exchange
At the same time, CIS has reshaped how knowledge flows across borders. The MIT International Science and Technology Initiatives (MISTI), launched in 1983 by Institute Professor Suzanne Berger, has sent thousands of MIT students abroad to work, study, and conduct research alongside international partners — experiences that extend far beyond traditional study abroad. In doing so, it helped change longstanding assumptions about the United States’ role in the world, demonstrating that learning is most powerful when it is reciprocal.
That ethos of mutual exchange continues to define CIS today. Through initiatives such as the Global Seed Funds, MIT faculty, researchers, and their students collaborate with academic partners around the world to advance shared research agendas.
The connection between these initiatives can be traced to Richard Samuels, Ford International Professor of Political Science and director of CIS from 2000 until 2023. His creation of the MIT-Japan Program in 1981 served as the model for MISTI. He was also the visionary behind the launch of the Global Seed Funds in 2008.
Together, these programs reflect a consistent vision: that the strongest ideas emerge through sustained engagement with partners around the world.
Expertise in action
Drawing on deep regional expertise, CIS also serves as a platform for global engagement across MIT, mobilizing cross-disciplinary knowledge to respond to unfolding international crises and inform both scholarly and policy debates.
Its MIT-MENA Program, led by Richard Nielsen, associate professor of political science, recently convened experts to assess the energy and security implications of disruptions in the Strait of Hormuz; the MIT-Ukraine Program, under the direction of Elizabeth Wood, Ford International Professor of History, brings together scientific, technical, and academic expertise to design sustainable solutions for a nation at war; and the MIT-China Program, directed by Yasheng Huang, professor of global economics and management at the MIT Sloan School of Management, is creating a hub for scholars and policy experts focused on balancing the Institute’s engagement with China.
Scholarship that shapes security
For decades, the MIT Security Studies Program, directed since 2019 by Taylor Fravel, the Arthur and Ruth Sloan Professor of Political Science, has been a leading incubator of ideas that have shaped debates on grand strategy, nuclear policy, civil conflict and Asian security. Its affiliated scholars, fellows, and graduate students have produced policy relevant research that continues to inform policymakers grappling with an increasingly complex international security challenges.
Building on that legacy, SSP recently established the Center for Nuclear Security Policy (CNSP) — made possible by a $45 million gift from the Stanton Foundation. Directed by Vipin Narang, the Frank Stanton Professor of Nuclear Security and Political Science, the CNSP aims to expand MIT’s leadership in addressing one of the most urgent challenges of our time: managing the risks posed by nuclear weapons in a rapidly evolving and uncertain geopolitical environment.
Another cornerstone of CIS’s security work is Seminar XXI, currently led by Kelly Greenhill, who holds faculty appointments at MIT and Tufts University. The annual, nine-month program brings together rising leaders from across the U.S. government, military, and national security community. In three decades, more than 2,500 participants have engaged deeply with issues such as nationalism, technological disruption, and global conflict — developing new frameworks for decision-making in high-stakes environments.
Advancing research, expanding dialogue beyond its anchor programs, CIS continues to invest in the next generation of scholars and practitioners. Undergraduate research initiatives, postdoctoral fellowships, and visiting scholar programs — including the Robert E Wilhelm Fellowship — create space for emerging and established leaders to explore critical questions, from governance and corruption to political reform and social change.
It also prioritizes policy-relevant research by supporting conferences, workshops, labs, and research initiatives on key problems in international affairs.
Finally, CIS plays a vital role in connecting MIT to the broader world. Through public events like the Starr Forum, the center brings leading global voices to campus, fostering dialogue on issues that shape international politics and policy.
The next 75 years
As CIS looks to the future, its mission is evolving to meet a dramatically changing global landscape.
“The moment we’re in now is so different from the Cold War era,” says Lieberman. “We’re seeing a much more complex global system, with new actors and new kinds of challenges.”
In what Lieberman describes as CIS 2.0, the center is sharpening its focus on the forces that will define the coming decades. This includes the geopolitical implications of artificial intelligence, the future of global cooperation in an era of climate crisis, and the evolving role of the United States within an increasingly contested international order.
Addressing these challenges will require exactly the kind of interdisciplinary, globally engaged approach that has defined CIS for the past 75 years. It will also require a renewed commitment to collaboration — across fields, across institutions, and across countries.
“A key source of our value added is to convene complementary sources of expertise,” Lieberman says. “It’s about bringing people together who might not otherwise be in the same room, and asking how we can have the greatest possible impact.”
Seventy-five years after its founding, CIS remains guided by a simple but powerful idea: that understanding the world — and improving it — demands more than any single discipline, perspective, or nation can offer alone.
The CIS’s 75th anniversary symposium, taking place Oct. 15-16, will explore the defining challenges of today with leading thinkers.
Robotic lab sets up and runs optics experiments on demandThe autonomous system could speed up testing of high-tech materials for applications such as solar cells, sensors, video displays, and quantum technologies.Every new generation of phone display, television screen, and solar panel is a result of precision optics experiments, which use lasers and other light sources to measure the optical properties of candidate materials. These experiments can take months to run, requiring scientists to meticulously angle and adjust delicate light sources, mirrors, cameras, and other components, in a careful and constant tuning that can be physically tedious and time-consuming.
But MIT scientists say the whole process of building and running an optics experiment could one day be fully automated. Taking a step toward such a future, they have developed a reconfigurable, robotic optics laboratory.
The new robotic lab autonomously assembles standard optical components into desired configurations. It can then tune the angle and position of mirrors and lenses with micron-scale precision to produce beams of light with specific properties. The system can also safely dismantle an experiment and reassemble the parts into an entirely new setup.
The team showed that the robotic system could autonomously build and fine-tune a tabletop laser cavity — a key element of most optics experiments. The system could also precisely manipulate components to perform several optical tasks, such as centering a laser beam, aligning multiple beams, and automatically stabilizing the beams in response to physical disturbances.
“We start with randomly placed components,” says Sachin Vaidya, a postdoc in MIT’s Research Laboratory of Electronics. “At the end, we have a fully functioning laser that the robot has built.”
The researchers are expanding the robotic lab, in a physical and virtual sense. In addition to improving the system’s physical sensing, maneuvering, and overall space, they are developing a cloud-based application that gives users virtual access to the physical robot. They envision that one day, scientists from anywhere will be able to remotely access robotic optics labs and virtually submit experimental protocols or queries that the labs would then set up and run autonomously.
“There are many things this could enable,” says Marin Soljacic, the Cecil and Ida Green Professor of Physics at MIT. “A robot isn’t going to get bored. It can work 365 days, 24 hours a day, on very boring things. That will free up so much creativity and time for scientists to then push theories and see what we can do. Science could progress much faster.”
The MIT team will present the details of the new system at the Intelligent Robots and Systems (IROS) conference later this month. Along with Soljacic and Vaidya, project team members include co-lead Seou Choi, Caio Silva, and Shrish Choudhury from MIT, Shiekh Uddin of Nokia Bell Labs, and Sajib Shuvo of Arizona State University.
A city of light
A tabletop optics experiment can resemble a miniature city of densely packed mirrors, lenses, and light sources. Scientists manually arrange and align the various components in precise configurations, then shine light into the experiment. The lenses and mirrors bounce and focus the beam into a desired wavelength, frequency, or intensity that can then be used to probe or manipulate a given material.
“Sometimes this manual setup takes days or months depending on the complexity of the experiment,” Soljacic says. “It’s meticulous work that has to be done again and again for each experiment.”
Most labs do incorporate some level of automation in an optics setup, such as motorized tuners that mechanically turn knobs to precisely angle a mirror.
“These components can automate the most tedious parts of an experiment,” Vaidya notes. “But no one has built a full system that goes from no setup to a completely aligned setup in one tool. That was our goal, to show complete automation through all the steps that go into an optics experiment.”
Auto-tuned optics
The team’s robotic lab centers around a robotic arm with seven moveable joints that is attached to a metallic tabletop. The robot picks and places lenses, mirrors, and other optical components, each of which the researchers installed in its own 3D-printed plastic housing.
The housings are designed such that the robot can easily and safely grip and move each component. The researchers etched the top of each housing with a QR code containing information about the component within the housing (such as whether it is a lens versus a mirror, and its exact dimensions and capabilities). Each housing has a magnetic base that helps stabilize a component once the arm places it down on the metallic tabletop.
The researchers designed a Wi-Fi-enabled “fine-adjustment tool” that clips onto the mount of standard optical components. The motorized tool can be wirelessly controlled to turn a component’s knobs, for instance to angle a mirror.
“The way humans do this tuning is by feel, and based on a lot of intuition,” Vaidya says. “This tool is at least as precise as a human, but in reality it is much more precise.”
The team also installed a pair of cameras over the entire setup that provides a birds-eye view of the tabletop experiment. Finally, they developed a “software stack,” or a set of programs that enables the robot to navigate through every step of setting up and continuously tuning an experiment. These steps include recognizing a specific component, knowing how to safely approach and pick it up, where to move it, and how to avoid collisions with other parts of the experiment along the way.
Finally, they designed a simple virtual user interface to allow an experimenter to remotely direct the robot. For instance, when a user drags the icon for a mirror from one spot to another, and clicks a button to confirm, the robot responds by picking up the actual mirror and placing it down at the corresponding location on the table.
As a demonstration, they directed the robot to assemble various components into a laser cavity. A laser cavity consists of two mirrors arranged on either side of a crystal. When a beam of light is shone into the setup, it pings back and forth between the two mirrors. With each pass, the light also passes through the crystal, which amplifies the light’s intensity, to a point that whatever light escapes, is intense enough to form a laser.
“We wanted to pick a demonstration in optics that’s reasonably challenging,” says co-lead author Seou Choi, a graduate student in electrical engineering and computer science. “This is not something a new trainee could do in an afternoon. It requires a lot of alignment and component experience.”
In the end, the robot successfully built a functional laser cavity by autonomously carrying out 50 maneuvers, all within 30 minutes. When the researchers introduced physical disturbances to the setup, such as randomly moving a component on the table, the system automatically readjusted components to maintain the laser’s intensity.
“Even tiny vibrations or temperature changes can degrade an optics experiment,” Vaidya says. “An autonomous lab could continuously monitor its own performance and repair the alignment before valuable data is lost.”
The researchers envision that robotic labs like theirs could be paired with a nearby library of physical components that another robot could fetch and deliver to a tabletop robot to arrange into an experiment. Such a system could work to build and run experiments, then break them down and set up new ones on demand, or continuously run an experiment that requires active 24/7 monitoring.
“A system like this could help industry test prototypes faster, for everything from cameras and displays to solar cells and AR/VR goggles,” Vaidya says.
For their part, the researchers are applying the new robot lab to test promising carbon-capture materials. By shining light with specific properties at these materials, they can get information about how a material absorbs carbon dioxide.
“Experimental optics is the backbone of many important fields,” Vaidya says. “Our work takes the first step toward optical labs that can operate faster, more reliably, and without manual intervention in a domain that demands extreme precision and diversity of experimental setups.”
This research was supported, in part, by the Korea Foundation for Advanced Studies Overseas PhD Scholarship, the U.S. National Science Foundation, the U.S. Army DEVCOM ARL Army Research Office, Parviz Tayebati, the MIT Undergraduate Research Opportunities Program (UROP), the MIT Generative AI Impact Consortium (MGAIC), and Shell International Exploration and Production Inc.
Nanoscale mechanics could enable brain-inspired computingA new device uses reconfigurable motion to mimic the firing behavior of a neuron, which could lead to more efficient computing.MIT researchers have created a new computing platform that could be used to develop intelligent and adaptive next-generation electronics that can simultaneously perform multiple functions, like computing and memory, all within one extremely compact, energy-efficient device.
Such a platform opens opportunities for low-power edge computing applications, interactive medical and environmental monitoring systems, and smart robots.
The researchers accomplished this by leveraging the unique mechanical response of soft polymers at the nanoscale. A mechanical response is how a structure changes when a force is applied to it.
They harnessed this response to create tiny mechanical devices that use reconfigurable motion to remember and process information in a way that mimics how neurons behave in the brain.
Because key computing functions are built into the intrinsic properties of the soft polymer material, the number of components needed to perform the functions are minimized, enabling a compact and versatile platform for information processing.
“Complex and coupled nanoscale phenomena can provide tremendous opportunities for new approaches to information processing and integrating multiple functionalities, such as computing, sensing, and actuation. This could enable levels of energy efficiency, autonomy, and reconfigurability in nanoscale devices and systems that are challenging to achieve with conventional computing platforms,” says Farnaz Niroui, an associate professor of electrical engineering and computer science (EECS), a member of the Research Laboratory of Electronics (RLE), and senior author of a paper on this device. “Here, we harness the intrinsic mechanical properties of materials to engineer device-level dynamics, such that the material building blocks play a much more active role in defining device functionality than conventionally considered.”
She is joined on the paper by co-lead authors Peter Satterthwaite and Sarah Spector, EECS graduate students; as well as Jeremiah Johnson, the A. Thomas Guertin Professor of Chemistry at MIT; Maxwell Conte, a graduate student in the Department of Materials Science and Engineering; Teddy Hsieh, an EECS graduate student; postdoc Eduard Bobylev; and Srinidhi Venkatesh ’25. The research appears today in Science Advances.
Bioinspired computation
Biological systems can leverage physical changes, like motion or deformation, to process information efficiently and without needing access to a central controller.
For instance, an octopus has a highly distributed nervous systems, with about two-thirds of its neurons spread throughout its arms. This allows the octopus to sense and process information about its environment locally and generate responses without requiring access to the central brain.
As an example, an octopus can mechanically change the color cells in its skin, enabling it to go through a rapid and context-specific camouflage process.
“You can think of an octopus as continuous computing matter, with computing, memory, sensing, and actuation distributed throughout its body,” Niroui adds.
Inspired by such performance, the researchers sought to develop a platform that can compute using mechanical transformations at the nanoscale. In mechanical computing, calculations are performed through physical transformations like movement and compression.
While bioinspired mechanical computing platforms have been developed at the micro and macro scales, the MIT researchers shrunk their device to the nanoscale. At this scale, even minute mechanical transformations can lead to drastic changes in a material’s properties. This can enable complex computing in an energy-efficient platform.
But achieving the reversible nanomechanical transformations needed for such computing is a fundamental challenge. When two surfaces come very close, they experience strong adhesive forces that pull the surfaces together, making them impossible to unstick.
To overcome this fundamental challenge, the researchers built a device with a super-thin film of the soft polymer polydimethylsiloxane (PDMS) sandwiched between two metal electrodes. This soft spacer balances the adhesive forces between the two metal surfaces, keeping the electrodes from crashing together in an irreversible way.
“The soft material serves as a ‘nano-spring,’ to help balance the forces to achieve nanoscale mechanical reconfiguration in a controlled and reversible manner,” Niroui explains.
When the researchers apply a voltage to the device, the two metal plates attract to one another, compressing the soft material and altering the electrical current flowing through the device.
“PDMS is viscoelastic, which means that after being compressed, it takes time to return to its original state. This allows the devices to dynamically remember the history of forces and voltages applied to them, and convert that history into an electrical response,” says Satterthwaite.
They researchers used this performance to demonstrate an artificial neuron.
Brain-inspired information processing
In the brain, each neuron accumulates an electrical charge a little bit at a time until it reaches a threshold and fires, passing information to other neurons in the network.
The researchers’ device mirrors this behavior. As voltage is applied over time, it accumulates stimulus as the electrodes gradually compress the PDMS. After crossing a threshold, it “fires” like a neuron before relaxing back to its original state.
“We have this complex functionality, which is the basis of biological computing, all contained in one nanoscale device,” Satterthwaite says.
Since computing and memory are incorporated within a single device with no need for external components, like capacitors or complex circuitry, this platform can achieve high energy efficiency with a small footprint.
“The performance highly relies on the memory introduced using the soft polymer. We can intentionally engineer this over a large design space to meet the requirements of the desired applications,” Spector says.
The device can also be compatible with biological systems, Spector adds. For instance, it could be useful in applications like smart prosthetics that can rapidly process tactile data or low-power wearable patches that collect and analyze health indicators in real-time.
In the future, the researchers want to expand this work to further integrate sensing with computing and memory to realize nanomechanical computing matter with applications in intelligent and adaptive systems.
This work was funded, in part, by the U.S. Defense Advanced Research Projects Agency (DARPA), the U.S. National Science Foundation (NSF), an MIT EECS MathWorks Fellowship, and the Netherlands Organization for Scientific Research. Device fabrication was carried out, in part, using MIT.nano facilities.
New AI technique could make minimally invasive surgeries safer and more preciseThis patient-specific method, called xvr, helps doctors use X-rays for surgical navigation in fields such as orthopedics and neurosurgery.Researchers created a new technique that accurately and rapidly matches X-rays captured during surgery with a patient’s preoperative 3D medical scan. This method could make it easier for clinicians to precisely pilot minimally invasive surgical tools, leading to faster and safer procedures.
Clinicians perform many minimally invasive surgeries using real-time X-rays to help them steer devices like catheters and endoscopes through tiny incisions. But since X-rays are flat images, it can be challenging to determine exactly where surgical tools are located and oriented within the patient’s body, increasing the risk of complications.
To help localize surgical devices, clinicians may manually align X-rays with preoperative 3D medical images, such as CT scans or MRIs. Artificial intelligence tools designed to streamline this process struggle to align images robustly for all patients, making them infeasible in practice.
This new system, developed by scientists and clinicians at MIT and collaborating institutions, uses an AI model that adapts to each patient in only about five minutes. The model automatically matches one patient’s X-rays with 3D scans in a matter of seconds, and with sub-millimeter precision.
Named xvr (which stands for X-ray volume registration), it outperformed existing AI methods by an order of magnitude across a wide range of patients, body parts, and medical procedures.
“A majority of Americans live more than an hour away from a center that can perform noninvasive procedures, like emergency stroke interventions. An hour in stroke time is incredibly substantial. Making these procedures easier by combining 2D and 3D information enables these types of highly specialized life-saving procedures to be more accessible to much broader parts of the population,” says Vivek Gopalakrishnan, a postdoc in the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL); a recent graduate of the Harvard-MIT Program in Health Sciences and Technology; and lead author of a paper on xvr, which appears today in Nature.
He is joined on the paper by his advisor Polina Golland, the Sunlin and Priscilla Chou Professor of Electrical Engineering and Computer Science (EECS), a principal investigator in CSAIL, the leader of the Medical Vision Group, and co-senior author of the paper; and Neel Dey, a former postdoc in the Medical Vision Group who is now an investigator at Harvard Medical School and Massachusetts General Hospital as well as co-senior author on the paper. Additional co-authors include David-Dimitris Chlorogiannis, a researcher and clinician at Harvard Medical School; Andrew Abumoussa, a neurosurgeon at St. Luke’s Marion Bloch Neuroscience Institute; Anna M. Larson, a pediatric clinician at Shriners Children’s Hospital; Nazim Haouchine, an assistant professor of radiology at Harvard and Brigham and Women’s Hospital; Darren B. Orbach, a physician and scientist at Boston Children’s Hospital; and Sarah Frisken, an associate professor of radiology at Harvard.
Making X-rays more informative
In many minimally invasive surgical procedures, like angioplasty to open blocked arteries, clinicians insert instruments through a tiny incision and use a high-speed mobile X-ray scanner to generate images that allow them to visualize the procedure from any angle.
But to guide surgical tools without accidentally damaging other tissue, clinicians must align real-time X-rays with the patient’s preoperative MRI or CT scan. This process, called registration, helps them determine where the tool is in relation to anatomical structures.
“It takes decades of training for a clinician to become skilled enough to see grainy, 2D images and understand how everything is oriented. We want to make these 2D X-rays more informative, so it becomes safer and easier to do these life-saving procedures,” Gopalakrishnan says.
Manual registration methods are slow and burdensome, requiring the clinician to guess the position of a surgical instrument by punching numbers into a computer or clicking anatomical landmarks on a screen.
To streamline the process, researchers are developing AI models that can predict 2D/3D registration. But people have such diverse anatomy that a model which works well for some patients may fail for others.
A lack of high-quality annotated medical image data makes it difficult to train a deep-learning model robust enough to adapt to many patients, Gopalakrishnan says.
Rather than trying to make a machine-learning model that can be applied to all patients, the researchers built a model designed to adapt extremely well for the specific patient.
“We tailor this one specific model for this one specific patient, and it doesn’t matter if it works on other people because there will be different models for those people,” Gopalakrishnan adds.
Patient-specific machine learning
Xvr takes one patient’s preoperative 3D scan, like an MRI or CT, and uses it to generate thousands of synthetic X-rays from many angles, producing about 1,000 images each second. It uses a physics-based simulation of the X-ray process to ensure these synthetic images are realistic.
“Instead of generating data from nothing, like some types of generative AI, this physics simulation is entirely based on the CT scan or MRI from this patient. Because xvr creates patient-specific data in a purely physics-based manner, there is no room for hallucinations,” Gopalakrishnan says.
The xvr framework uses these simulated data to train an AI model that can accurately align this patient’s 2D X-rays with their 3D image scan in a matter of seconds.
But while such a registration model is highly accurate, it would take about 12 hours to train from scratch for each patient, making it impossible to deploy in an emergency. To make the process faster, the researchers used xvr to pretrain a more versatile AI system, called a foundation model, that can quickly adjust to each new patient.
They collected whole-body 3D medical scans from more than 2,000 patients covering a wide range of ages, image modalities, and regions. Xvr used these diverse data to generate synthetic X-rays and train a foundation model to perform 2D/3D registration.
This pretrained model can adapt to a new patient in about five minutes, and performs registration with the same accuracy as if it had been trained from scratch.
“So now you can get patient-specific accuracy but also in a very rapid time frame,” Gopalakrishnan says.
The team tested the model on the largest available dataset of real 2D/3D registrations, incorporating data from five hospitals that covered dozens of bones and organ systems in adult and pediatric patients.
Xvr significantly outperformed other AI-based methods in accuracy and robustness, while operating fast enough for emergency surgeries. The model could also be used to improve the performance of robotic surgery technologies.
In the future, the researchers hope to focus on making xvr faster for real-time deployment, conducting further studies to verify its reliability in additional situations, and extending the system to handle more complex scenarios, like moving body parts.
“For the past two years, we’ve been carefully developing this algorithm and validating it. Now, we are collaborating closely with surgical robotics companies and clinical groups to turn this research into useful tools for navigation or deployment,” Gopalakrishnan says.
This work was funded, in part, but the National Institutes of Health (NIH), the MIT CSAIL-Wistron Program, the MIT-IBM Computing Research Lab, the MIT Jameel Clinic, the MIT Health and Life Sciences Collaborative, and the Chou Family Transformative Research Fund.
MIT startups inspire with impressive presentations at Demo Day 2026The event featured ventures solving problems in manufacturing, cybersecurity, health care spending, and more.The annual “Demo Day” event at MIT, which marks the end of the delta v startup accelerator, fell on the 25th anniversary of the Sept. 11 attacks this year, giving MIT entrepreneurs a chance to honor the memory of those lost that day while presenting their startup progress in the program.
Each year, the event celebrates all that students achieved while working full-time on their ventures over the summer with support and guidance from the Martin Trust Center for MIT Entrepreneurship.
But the usually boisterous night started with the program’s military veterans asking for a moment of silence.
“Today is a day of remembrance, but also a day of celebration,” founder and MIT graduate student Kevin Power MAP ’25 told the audience in opening remarks. “It’s about building to create a better world. Today, we honor those lost the way we believe they would want: by being humble, taking care of each other, and building something worthy of the people who never had this chance. In this room, people are taking on the hardest problems in health care, cybersecurity, defense, robotics, and manufacturing.”
Now in its 15th year, delta v Demo Day gives MIT entrepreneurs a chance to share their work and inspire classmates to adopt the entrepreneurial mindset. The companies that presented were whittled down from an initial list of over 200, twice the amount that applied in 2025.
Across a whirlwind 90 minutes inside a jam-packed Kresge Auditorium, 13 teams presented their startups to the audience in two-minute presentations. Many shared business milestones and progress in line with what a typical company would achieve over multiple years, including customer partnerships, prototype deployments, and even revenue.
Each team received mentorship and support along with $75,000 in equity-free funding, a dramatic increase from years past. This year’s cohort featured undergraduates, graduate students, and postdocs, from across all of MIT’s schools.
“One of the things I love about delta v is it brings students from all across our community together to approach challenges with different perspectives,” Paula Hammond, dean of the MIT School of Engineering, told the audience. “Their companies are just as wide-ranging. They are working in AI, robotics, health care, aerospace, financial technology, biotech, cybersecurity, and more. At their core, they all share a desire to tackle difficult problems and improve people’s lives.”
This year the Trust Center also announced a new partner model for the delta v program, composed of over 125 leading founders from companies like HubSpot, Okta, and Kayak, along with industry experts and early-stage investors.
The event’s occurrence at the start of the semester is no coincidence: It is timed to attract the next generation of entrepreneurs on campus.
“This is my favorite day of the year,” said Bill Aulet, the managing director of the Trust Center and MIT’s Ethernet Inventors Professor of the Practice at the MIT Sloan School of Management. “Today is about building organizations that will solve the world’s most intractable problems. It’s about more than making money. These presentations will inspire you and make you proud to be a part of the MIT community.”
Artificial intelligence featured prominently in this year’s cohort of companies, which are applying the technology to solve major problems in cybersecurity and manufacturing, improve health care spending, design advanced metal parts, and more.
The company Neural Physics, for instance, is building AI models for manufacturing and other hardware applications. The company’s models are designed to accelerate product design and validation workflows for companies building things like cars, equipment, and machine parts.
“AI can build software overnight,” said co-founder and PhD candidate Mohamed Elrefaie. “AI for software has been solved. The next revolution is physical AI. Design takes too long, and it costs billions. In 1907, it took Henry Ford five years to develop the first Ford car model. Today, it still takes the Ford Motor Company five years to go from design to production. The U.S. advanced manufacturing sector loses roughly $245 billion annually due to engineer delays… [Most] of that time is spent running simulations or making engineering decisions. At Neural Physics, we are building foundation physics models to accelerate those processes.”
Another company, Cerebrus AI, has built a system for detecting when AI agents deviate from approved behavior. The solution builds a baseline of behavior for each deployed agent and monitors their activity to flag unusual behavior that could lead to problems.
“The rollout of revolutionary technology is being held up by three key questions that every executive is asking: Where are my agents? What are they doing? What do they have access to?” co-founder and MBA student Griffin Potrock said. “Security teams want to say yes, but they can’t trust what they can’t see. Cerebrus AI can help those teams.”
The company Talys uses AI agents to help health care organizations find opportunities to lower spending on things like pharmacies, operational processes, and third-party services. The company is already working with health systems and has processed $325 million in spending.
“Decades of attempts to reign in health care spending have fallen short — until now,” co-founder and MBA student Nicolas Berzin said “Why is it so hard? Analytics and dashboards give you pictures of the problem, but not the solution. Meanwhile, consultants are slow and expensive. There are thousands of spend categories, tens of thousands of procedures, and millions of items. Who knows how to save on all of these things? Imagine if you could classify every line, benchmark every item, find every substitution, triage every unprofitable case, and model every scenario across multiple contracts and thousands of procedures and categories like an expert. Talys is a margin-execution system that runs 24/7 to optimize procurement, reduce leakage, and improve case economics.”
Other delta v teams also presented impressive hardware solutions. RBT Resources presented a portable device that simplifies and speeds up blood transfusions, which could be used in hospitals and at the site of traumatic injuries like highways or battlefields.
“Transfusion at the point of injury is an extremely manual process with three key inefficiencies: They are time dependent, gravity dependent, and labor intensive,” explained CEO Anthony Capuano MBA ’26, a former U.S. Navy Seal. “Our goal at RBT Resources is to make transfusions faster and simpler for all medics.”
Gander Robotics developed a low-cost drone submarine that can be used when someone falls overboard on a ship. The hand-thrown, autonomous vessel can sense and travel to the person at sea and give them something to hold onto at the surface, all while providing rescue crews with its exact location.
So-called “man-overboard” situations are surprisingly common on military boats and cruise ships. The device was developed over two years at MIT and the Woods Hole Oceanographic Institute. “Our autonomous rescue swimmer uses a proprietary technique to search with sonar from underneath the surface, where it’s nice and calm even if there’s a storm raging above,” CEO Michael Autery MBA ’26 explained.
The other teams presenting included:
Alpaca is building an integrated ecosystem of hardware and software to allow individuals to host their own frontier AI models without a subscription.
Banzai is building an AI-powered agent to help homeowners, property managers, and asset managers diagnose home repairs faster, improve repair accuracy, and reduce maintenance costs.
Bizon Labs is building a platform for engineering lipid nanoparticles to deliver advanced medicine anywhere in the body.
Cortheon uses AI design optimization to help foundries make complex metal parts at lower cost and with the design freedom of 3D printing.
Exo AI is helping financial institutions automate back-office processes using AI-native software capable of analyzing messy data and connecting fragmented workflows.
Pixology is using agentic AI to help sales teams create visual, engaging pitch materials faster for media rights deals.
Robox is using AI to develop a design engine for physical automation inside systems integrators, robotics firms, and manufacturers.
The Trade Lab is helping importers navigate shifting tariff regulations across the globe and optimize supply chains.
Measure by measure, studying society accuratelyNaoki Egami has become a standout in political methodology, helping refine tools that give scholars durable results.Let’s agree at the outset the world is a complicated place, and social scientists have exacting jobs when it comes to measuring civic phenomena with precision.
After all, even careful studies raise follow-up questions: How much do their findings apply in other settings? Do conclusions about politics in one country apply to other countries? If you’re studying voters in a lopsided election, will your findings apply to voters in a close election? Those questions are all a natural part of the research process.
That’s where Naoki Egami comes in. Egami is an MIT political scientist whose specialty is the methodology of research. He carefully scrutinizes, for one thing, what social scientists call “external validity,” whether the results of particular studies apply more generally.
“I always say political methodology is the field where you ask questions as a political scientist, but then you solve them like an applied statistician or an applied computer scientist,” Egami says. “You find out the underlying mathematical problems behind the empirical challenges people face, and solve them optimally.”
As it happens, Egami’s interests range widely. Years ago, before the current artificial intelligence craze, he started studying what happens when AI tools are introduced into studies. How accurate are they? How can researchers account for AI tendencies? Focusing on these and other questions has helped Egami build a broad portfolio of research, win awards, and flourish in his career. All the while, he retains interest in basic questions about politics, as well as measuring things correctly.
“You need both perspectives,” Egami says. “If you only think about technical statistical theories, you might not work on interesting empirical problems sometimes. But if you only think about problems, you won’t really solve them optimally; you’ll solve them in an ad-hoc way. So, you really want to have both lenses.”
Egami joined MIT’s Department of Political Science as an associate professor with tenure in 2025. He is also a faculty affiliate of the Statistics and Data Science Center at the Institute for Data, Systems, and Society (IDSS).
Workshopping his career
Almost anyone who likes their job has experienced some good fortune in finding it. Egami’s case calls to mind those adages about luck being a mixture of preparation and opportunity.
Egami grew up in Tokyo and attended the University of Tokyo. He was good at math and physics, but he also liked political philosophy and was unsure how to combine his interests. One day, Egami attended a workshop about U.S. graduate school, which he thought was about MBA programs. Actually, it was about PhD programs, and included a political scientist talking about using math in the field, so Egami asked her a question.
“The miracle is: That workshop had 200 people in it, and after it was done, I was packing my stuff to go home, and the panelist, who was a PhD student, came down from the stage and found me,” Egami recalls. “She asked, ‘Are you the one who said you’re interested in political science in the U.S., and likes math?’”
She invited Egami to what he thought would be another career workshop, the following week. Once again, he was mistaken.
“I showed up, and it was an academic seminar,” Egami continues. “There were only 20 people there. It was 19 professors, and me, a first-year undergrad.” Then a professor named Kosuke Imai, now at Harvard University, gave a talk about his own research on using statistics in the social sciences.
“I was super-excited and felt if I could do even 20 percent of that, it would be a dream,” Egami says. “I talked to Kosuke and said, ‘I want to do what you’re doing.’ He probably thought I was just a random person.”
Egami, thus bolstered, started pursuing the goal of becoming a political scientist. He received his BA after spending a year as an exchange student at the University of Michigan, and applied to graduate schools in the U.S., landing at Princeton University — where Imai eventually became one of his advisors. Working with Imai, Rafaela Dancygier, Brandon Stewart, and others, Egami generated papers on methodological topics like external validity — and found substantial interest when he presented them.
“That was a case where the audience or market told me what I should really work on,” Egami says. After earning his PhD from Princeton in 2020, he joined the faculty at Columbia University, moving to MIT five years later.
Enjoying the spirit of MIT
One of the hallmarks of Egami’s work is very close scrutiny of the factors that can influence the results found in empirical studies.
“In statistics, you talk about whether the people in the data are similar, meaning the population data,” Egami says. “But in political science, there are a lot of differences in context.”
Consider the question of how much political campaigns sway the minds of voters. Political scientists have sometimes received permission to conduct field experiments in active political campaigns. That’s a significant step toward generating robust results. And yet, not all campaign settings are the same. Politicians may let researchers in when they expect to triumph, and the dynamics in those races might differ from close races.
“It’s great to do field experiments, and that’s usually where people are allowed to do research,” Egami says. “It’s where politicians know they can win. But most of the time, we’re interested in the battlefield races, the politically competitive districts. And the logic and voter behaviors can be different in those cases.”
Egami’s job, on one level, is to spot such differences and make other researchers aware of them.
Meanwhile, he has also developed a strong interest in scrutinizing the tools of machine learning, as applied to the social sciences. This predates the elevated interested in AI generated by ChatGPT, starting in late 2022. Some of Egami’s work explores how to systematically identify errors introduced by AI tools and then account for this issue when using AI in research.
“In the past, social science data is something we carefully collect and take a long time to really validate before we analyze it,” Egami says. “But if the generation of data is changing. If people use AI to generate data at scale, it can have errors. So I was already thinking: You want to have statistical methods that take into account these errors, otherwise many of the analyses will not be able to be replicated. That’s how I started to work on a lot of things about AI.”
All of this has brought Egami recognition and honors in the field. Last year, he received the Emerging Scholar Award from the Society for Political Methodology. He has also been the recipient of best paper awards from the American Political Science Association’s sections for political methodology (in 2019 and 2025), experimental research (in 2024), and political networks (in 2022). Earning awards in three subfields of the discipline speaks to Egami’s scholarly versatility.
In his view, though, the work he does in different areas is ultimately aligned.
“All these things are in parallel,” Egami says. “I’m trying to start a new research agenda every three to four years. That helps me learn new topics and be motivated.”
Further motivation, he says, comes from being at MIT and liking the experience.
“I already knew MIT was an amazing place I would enjoy,” Egami says. Even so, in his time at MIT, he says, he has gained even more appreciation for the “spirit of engineering,” in the sense of working systematically on solutions to ongoing problems, among other things. In any case, Egami has found the Institute to be a stimulating and congenial place to do his work.
“People are really nice at MIT,” says Egami, who has been teaching both undergraduate and graduate classes.
He adds: “The Department of Political Science is really high-functioning, people are intensive in terms of their work, but it’s just genuinely nice people.”
And, yes, that’s one claim about the world Egami does not have to double-check.
New method enables AI for safety-critical situationsThe “HardFlow” algorithm could help generative AI models produce high-quality outputs that obey strict requirements when “pretty close” doesn’t cut it.MIT researchers have developed a new technique that helps generative artificial intelligence models find solutions to high-stakes problems.
In these settings, a plausible answer is not enough: The output often must also satisfy nonnegotiable safety, physical, or task-specific requirements, known as hard constraints.
The researchers developed a method that helps generative models meet these strict requirements without sacrificing the quality of their outputs.
The key to their technique is to give the model more freedom during the generation process and enforce hard constraints on the final output, rather than at every intermediate step.
In experiments spanning robotics, control of physical processes, and computer vision, the new method consistently satisfied the required constraints while identifying better solutions than existing techniques.
This adaptable, plug-and-play technique works at deployment time, so it can be applied to pretrained generative models without retraining them. It can make such models more useful in applications where safety rules, physical laws, or other strict requirements cannot be violated.
“The promise of generative AI is its ability to explore a rich space of possibilities, but the real world places boundaries on which possibilities are acceptable. Our approach lets us preserve that generative power while enforcing the nonnegotiable requirements of high-stakes or safety-critical applications,” says Navid Azizan, the Alfred H. and Jean M. Hayes Career Development Associate 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 Zeyang Li, a graduate student in mechanical engineering and LIDS; and Kaveh Alim, a graduate student in IDSS and LIDS. The research appears this week in the IEEE Transactions on Pattern Analysis and Machine Intelligence.
Freedom to explore
Pretrained generative AI models, such as diffusion models like Stable Diffusion and flow-matching models like FLUX, are now widely available. These powerful models learn to create new data by transforming random noise. Their availability has enabled people to adapt them to a wide range of applications.
These highly capable models excel at providing answers that come close to satisfying most queries, but in safety-critical applications like robot path planning on a crowded factory floor, an answer that is “nearly correct” may not be good enough.
For instance, a “nearly correct” path from one machine to another might still result in the robot colliding with a human co-worker.
In such safety-critical applications, users often employ a technique called projection-based sampling, which repeatedly forces the model’s partial solutions, called intermediate samples, to satisfy strict requirements during the generation process.
But constraining the entire generation process can prevent the model from reaching a better final solution. These methods also typically focus only on satisfying the hard constraints, missing the opportunity to improve other qualities of the solution, like reducing the length of the robot’s trajectory.
“For constraint satisfaction, what ultimately matters is the model’s final output, since the internal process is discarded. By not requiring every intermediate step to satisfy the constraints, we give the model more freedom to find high-quality solutions that are still feasible in the end,” says Li.
The researchers developed an algorithm called HardFlow that steers the sampling process so that the final output satisfies the user’s hard constraints without being overly restrictive and is of higher quality.
Subtle steering
HardFlow reformulates hard-constrained sampling as a trajectory-optimization problem, using tools from the field of optimal control. This enables the framework to steer the model’s sampling trajectory toward a goal, making subtle corrections along the way while enforcing hard constraints on the final output.
“Control theory gives us a powerful framework for formalizing the optimal way of making these corrections,” Azizan says.
But solving the trajectory-optimization problem around an enormous neural network was no easy task. The model may have hundreds of interconnected layers that process data.
To make the problem tractable, the researchers leveraged the structure of flow-matching models to decompose the problem into a sequence of smaller, single-step subproblems. They then applied systematic transformations and approximations to derive an efficient, scalable algorithm that still finds a feasible solution.
“Essentially, we transformed the trajectory-optimization problem into something that preserves the key properties of the original problem, but can be solved very efficiently at deployment time,” Azizan adds.
Reformulating the task as an optimization problem allows HardFlow to incorporate additional goals that can improve the quality of the final answer. For instance, HardFlow could find a collision-free path for a robot that is also the shortest distance to its goal.
“Our framework can jointly handle both aspects, which helps it perform much better than existing methods,” says Li.
Across experiments in robotic manipulation, maze navigation, and text-guided image editing, HardFlow achieved perfect constraint satisfaction while consistently outperforming baseline methods on measures of solution quality.
For example, it enabled a robotic manipulator to avoid collisions with obstacles while also finding the quickest path to the target object. Most other methods either resulted in collisions or found paths that took significantly more time.
In addition, HardFlow’s computation time was comparable to or lower than that of most competing methods.
In the future, the researchers could extend the framework to settings in which the AI model itself can also be updated, so that constraint satisfaction and sample quality can be improved in a more adaptive manner.
MIT spinout turns plastic waste into resilient building materialsAtlas Building Composites is commercializing MIT research to turn plastic waste into parts for buildings and other infrastructure.The world needs more homes. The world also has too much plastic. Perhaps the only thing those two problems have in common is that they’re hard to solve.
Atlas Building Composites, a spinout of MIT, is on a mission to address both problems with a single solution. The company has developed an AI-powered robotic manufacturing platform capable of turning single-use plastics into durable building materials.
The company emerged from MIT HAUS, a research effort in the MIT Department of Mechanical Engineering that’s short for “Home Architecture for Universal Sustainability.” Atlas uses waterless plastic recycling and large-scale composite additive manufacturing technology to make parts like home foundations, decks, and trusses for walls, floors, and roofs.
“Our mission is to convert waste plastic pollution into durable composites to build 1 billion homes,” says Atlas chair and co-founder A.J. Perez ’13, MNG ’14, PhD ’23, who is also an MIT research scientist. “You can’t divorce these things from each other. We’re not here just to build homes, and we’re not here just to recycle plastic. The conventional way of building homes involves cutting down trees, mining, refining, and a bunch of other dirty activities. We want to avoid all that and address all the plastic bound for our oceans and landfills. We’re turning bottles into buildings.”
Atlas’ parts are already being used to support barns, sheds, decks, and docks. Most recently, the company supplied the U.S. Army Corps of Engineers with American-made recycled composite trusses to construct a 40-foot bridge in a Massachusetts wetland.
Perez and Atlas co-founder Matt Pouliot envision deploying thousands of their AI robotic production systems around the world. A key enabler for that scale is the company’s ability to recycle low-grade plastic into building components without water.
“This is key to democratizing recycling,” Perez says. “Now, every country around the world, regardless of their water access, will be able to do something about their plastic. We strive to study these issues in the real world, not just a lab. When you talk to government officials about creating a new recycling facility, they have to get the local water agency involved, there’s permitting, etc. A lot of that work disappears with the waterless recycling process.”
Research for impact
Since earning his PhD at MIT, Perez has been developing advanced fabrication techniques for homes and new techniques for plastic recycling. In 2019, he started MIT HAUS with David Hardt, MIT’s Ralph E. and Eloise F. Cross Professor in Manufacturing.
“It started with the simple mission of enabling the production of 1 billion homes over a 30-year period,” Perez says. “Then we realized how much the materials needed for those homes would strain global supply chains.”
Perez says building those homes using conventional methods would require a doubling of global production capacity for materials like concrete, not to mention a dramatic acceleration of global deforestation.
“That’s where the light bulb went off,” Perez says. “There’s this other problem humanity has, which is 8 gigatons of plastic that have been produced and are polluting our oceans, rivers, and cities. We decided to plug two really big, hairy problems together.”
Perez met Pouliot, a former Maine senator, and the pair started Atlas to commercialize the technology Perez had been developing at MIT. The founders worked with MIT’s Technology Licensing Office and have since worked with researchers at other universities to independently develop technology for the company’s robotic manufacturing platform, which the founders call the Atlas Factory Stack.
First, single-use plastic from water bottles and other objects is shredded and fed into the Atlas system, where it is melted and fused with American-made fiberglass to make it stronger than wood. From there, a large-scale 3D printer creates the parts, including trusses for floors, walls, roofs, and bridges.
Through research at MIT, Perez has shown large composite trusses can be printed in under 13 minutes and support over 4,000 pounds, exceeding key building standards.
“At MIT, we’ve demonstrated we can produce 60 to 80 pounds of parts per hour, and the systems we’re specifying in Atlas factories operate in the 150 to 200 pound per hour range,” Perez says. “There’s the potential for our robotic manufacturing platform to produce each part at a lower cost than injection molding, and it’s far more flexible and convenient. For example, we can manufacture the parts in the reverse order so that they’ll be placed on the finished goods pallet next to the machine.”
The founders envision Atlas as a technology provider enabling the creation of home factories close to wherever homes need to be built. Today, each Atlas factory cell is capable of producing the structural framing components for about one small home per day.
“The old way of doing things would be some huge factory in China would mass produce one type of part and ship it far away,” Perez says. “I don’t think that’s good for the planet. Another reason we don’t use injection molding is economic: Mega factories don’t produce as many jobs and have a much higher carbon footprint. We want this to be localized to benefit local communities. The plastic is already everywhere. The more local Atlas is, the lower the cost and footprint.”
Going global
Plastics last far longer than wood, especially for applications where they’re in contact with the ground or water. That adds to the company’s environmental benefits.
“If you get a material into the building world and it does its job, it’s going to be used for a very long time and not need to be recycled again for a very long time,” Pouliot says. “That’s important because when you recycle something over and over again, it degrades. This is one of the most sustainable use cases for recycled petrochemical products.”
Atlas’ bridge with the Army Corps of Engineers was installed in less than a day. The founders are also in talks with international franchise partners to deploy the Atlas Factory Stack across the globe.
“To accomplish our mission, I fundamentally believe it’s not going to be one far-away company dominating the industry,” Perez says. “It’s going to be every country leveraging Atlas Factory Stacks to create local recycling jobs, local factory jobs, local construction jobs, and to stimulate their economies with local materials.”
A burst of “pink noise” may lead to more restorative sleepDelivered at just the right time, this type of auditory stimulus can strengthen the flow of cerebrospinal fluid, which clears debris from the brain and keeps it healthy.During the day, waste products such as lactic acid and worn-out proteins build up in the brain. When we sleep at night, waves of cerebrospinal fluid (CSF) help to wash away this waste, keeping the brain healthy.
In a new study, MIT researchers have shown that they can strengthen these CSF waves through exposure to short bursts of a gentle, staticky sound known as “pink noise” during sleep. These bursts increase the amplitude of slow electrical waves in the brain, which then enlarges the CSF waves.
The researchers now hope to explore whether this enhanced CSF flow could help to boost cognitive function, improve memory, or even slow the progression of neurodegenerative diseases caused by the buildup of harmful proteins such as amyloid beta.
“We found that we were able to increase the size of the CSF flow wave during sleep, which as far as we know, there hasn’t been a method to do before. Now that we can enhance CSF flow during sleep in healthy adults, we’re really excited to bring this technology to clinical populations to see what effects we can have,” says Laura Lewis, the Athinoula A. Martinos Associate Professor of Electrical Engineering and Computer Science, a member of MIT’s Institute for Medical Engineering and Science and the Research Laboratory of Electronics, and an associate member of the Picower Institute for Learning and Memory.
Lewis is the senior author of the study, which appears today in Science Translational Medicine. Joshua Levitt, who recently earned his PhD from Boston University and was a visiting graduate student in Lewis’ lab, is the paper’s lead author.
Cleaning up the brain
Cerebrospinal fluid is a clear liquid that surrounds and cushions the brain and spinal cord. In addition to protecting the brain from injury, it also helps provide nutrients such as glucose and removes waste products secreted by brain cells as they burn energy.
In 2019, Lewis reported a way to use functional magnetic resonance imaging (fMRI) to measure CSF waves as they flow in and out of the brain during sleep. That study showed that these waves are tightly coupled with brain waves called slow waves, which are associated with deep sleep.
In the new study, she wanted to further explore the relationship between brain waves and CSF flow, and investigate whether manipulating brain waves might enhance CSF flow. Previous work had already shown that delivering an auditory stimulus at the peak of slow waves can deepen the waves.
“You can make more of these electrical slow waves through an auditory stimulus, if it comes at just the right time. Similar to a child on a swing, if you push them when they’re at the right moment in their movement, you can make that swing go farther,” Lewis says. “The challenge is: How do you find just the right time?”
The auditory stimulus used for this study is a 50-millisecond burst of pink noise. Similar to white noise, pink noise contains all sound frequencies audible to the human ear, but the lower pitch frequencies are louder and the higher pitch frequencies are softer. This creates a balanced, gentle sound similar to steady rain or a distant waterfall.
To deliver these bursts at the peak of the brain’s slow waves, the researchers had to measure each participant’s EEG activity as they slept. This proved challenging because they also needed to measure fMRI signals to monitor CSF flow, and the magnetic fields used for fMRI interfere with EEG signals.
To overcome that, the researchers developed a way to process the EEG signals to eliminate the noise caused by fMRI, very rapidly — in less than 100 milliseconds. To make up for that small lag time in the EEG measurement, they also developed an algorithm that could predict when the slow wave peaks would occur. This allowed them to deliver the pink noise stimulus at the correct time.
More restorative sleep
In tests of 14 healthy volunteers, the researchers found that the auditory stimulus they delivered — which is not loud enough to wake a sleeping person — increased the amplitude of both the slow electrical waves and the CSF waves, during sleep.
Their fMRI studies also revealed that the slow waves stimulate blood vessels to constrict and dilate, allowing them to act as a pump that drives CSF out of the brain. Slow waves are seen only during non-REM sleep, and they become more prominent in deeper stages of sleep.
The researchers now hope to study whether enhancing CSF flow could help people to get more restorative sleep, especially people with insomnia. They also plan to explore whether increasing the flow of CSF, and the removal of waste products from the brain, could help people with Alzheimer’s and other diseases characterized by buildup of harmful proteins.
“Brain waste clearance is really important for Alzheimer’s and other forms of dementia, which are caused, in part, by the buildup of molecules like amyloid and tau in the brain. If we can improve brain waste clearance, we may be able to help prevent the buildups of these plaques that lead to disease,” Levitt says.
Levitt has started a company that hopes to develop a device, such as a headband, that people could use at home to increase CSF flow by delivering an auditory stimulus at the right time.
The research was funded by a McKnight Scholar Award, a Sloan Fellowship, a Pew Biomedical Scholars Award, the Simons Foundation Collaboration on Plasticity in the Aging Brain, the MIT EECS Transformative Research Fund, the National Institutes of Health, the Corundum Convergence Institute, and the Panasonic Well Fellowship for AI and Wellness.
An electrochemical approach turns ammonia into pure hydrogenAn MIT team has demonstrated a more efficient way to extract pure hydrogen gas from hydrogen carrier molecules.As a liquid that is easily stored and transported, ammonia (NH3) is an attractive carrier for hydrogen, which is used in fuel cells, semiconductor manufacturing, chemical processing, and other applications. However, breaking ammonia into hydrogen and nitrogen typically requires high temperatures, and the resulting gas mixture must undergo additional purification before the hydrogen can be used in many applications.
MIT researchers have now developed an electrochemical approach to promote hydrogen release from ammonia while simultaneously separating and concentrating the hydrogen into a high-purity stream. Their strategy, which uses electricity to speed up the extraction, reduces the temperature and energy required to recover hydrogen from ammonia and other hydrogen carriers.
In a new study, the researchers showed that their approach can generate highly concentrated, pure streams of hydrogen.
“We have shown the ability to use electrochemistry to drive thermodynamically uphill and kinetically difficult dehydrogenation reactions,” says Yogesh Surendranath, the Donner Professor of Science and a professor of chemistry and chemical engineering. “In this case, we studied the conversion of ammonia and a liquid organic molecule because of their importance as possible hydrogen carriers for a hydrogen economy. But the concepts we learned here could in principle be translated further, and we’re actively working on translating it to other important dehydrogenation reactions.”
Surendranath is the corresponding author of the study, which appears today in Nature. MIT postdoc Rui Zeng, now a professor of materials science and engineering at Harbin Institute of Technology in Shenzhen, China, is the paper’s lead author.
Extracting hydrogen
Hydrogen is widely used in semiconductor manufacturing and chemical processing and is also an energy carrier in fuel cells that use hydrogen and oxygen to generate electricity without combustion. Expanding its use, however, will require practical ways to store and distribute it.
Hydrogen gas itself is difficult to transport efficiently without compression or liquefaction. One alternative is to store hydrogen chemically in compounds that are liquids or can be readily liquefied, then release it where and when it is needed.
Ammonia is one promising hydrogen carrier because it is already produced and transported across large distances, but recovering hydrogen from ammonia remains challenging. That process, known as “cracking,” requires temperatures higher than 500 degrees Celsius to achieve high reaction rates and conversion. The hydrogen must then be separated from nitrogen and unreacted ammonia.
“We wanted to ask whether we could use electrical inputs to drive what would otherwise be an unfavorable dehydrogenation reaction, and simultaneously do it in a way that would separate the hydrogen from the hydrogen carrier, so that it would be very pure and could be used directly in a fuel cell or other application that requires a high purity hydrogen stream,” Surendranath says.
The key element of the researchers’ new design is the coupling of a palladium-based separation membrane with a hydrogen-generating electrode through a molten hydroxide electrolyte. The separation membrane selectively transports hydrogen while preventing other components of the reaction mixture from passing through.
Using the new setup, ammonia is first dehydrogenated by a catalyst containing ruthenium and cesium. The hydrogen then reaches the separation membrane, whose opposite side is in contact with a molten hydroxide electrolyte.
The electrochemical gradient across this membrane effectively creates a “vacuum” for hydrogen, providing a strong driving force for its transport across the membrane. It also converts the hydrogen into protons and electrons, which travel separately through the molten electrolyte and external circuit, respectively, before recombining at a second electrode to form hydrogen gas.
Because the membrane selectively transports hydrogen, the system produces a concentrated stream of hydrogen gas without requiring a separate downstream purification process.
“Using this electrochemical process, we’re able to do this active pumping of hydrogen from a low concentration to a high concentration,” Surendranath says.
Continuously extracting hydrogen can also help drive the dehydrogenation reaction forward, especially when the presence of hydrogen inhibits the reaction. In this way, this strategy does more than separate the product: It changes the reaction environment and enables hydrogen recovery under milder conditions.
This process thus can be performed at temperatures around 200 or 300 degrees Celsius, much lower than those required for conventional ammonia cracking. Another advantage is that it creates a pure stream of hydrogen that doesn’t need to be purified later on — a step that requires additional energy.
Curtis Berlinguette, a professor of chemistry and chemical and biological engineering at the University of British Columbia, described the method as “a powerful new way” to solve the problem of obtaining a pure stream of hydrogen from ammonia and other hydrogen carriers.
“By using electricity to pull hydrogen through the membrane as it is released, they accelerate the dehydrogenation of ammonia and liquid organic hydrogen carriers while simultaneously producing a purified hydrogen stream. This is an important advance for the energy sciences because it opens a credible pathway for transporting hydrogen in stable chemical carriers and releasing it where and when it is needed,” says Berlinguette, who was not involved in the research.
Powering transportation
In this study, the researchers showed that this approach could be used to dehydrogenate not only ammonia but also methylcyclohexane. This molecule is part of a class known as liquid organic hydrogen carriers (LOHCs), which also hold potential as an energy carrier.
The researchers envision that their new strategy could be useful for transportation applications, such as powering cars, buses, or ships, or for fabricating semiconductors or electronics. Pure hydrogen gas is used for several steps in semiconductor manufacturing, where it plays important roles in boosting manufacturing yields and reducing surface defects.
Because palladium is an expensive metal, the researchers are now working on ways to reduce the amount of palladium needed for the separation membrane. They are also working on scaling up the process, and on applying it to other dehydrogenation reactions that could be industrially useful.
The research was funded by the U.S. National Science Foundation.
Study predicts large disparities in access to food, water, and energy in 2050 In some regions of the world, the poorest people may spend about 50 percent of their income on food, while the richest spend about 5 percent.How will global access to food, water, and energy evolve in coming decades? A new study co-authored by MIT researchers suggests the answers could be very different depending on region, resource, and income.
Based on extensive modeling of many different resource scenarios, the study finds that in some regions, lower-income people could be spending roughly 50 percent of their income on food by the year 2050, in contrast to higher-income groups that could spent about 5 percent of income on food in the same areas.
“For a lot of these outcomes, the lower-income groups see much worse potential insecurity,” says Jennifer Morris, a principal research scientist at the MIT Center for Sustainability Science and Strategy and the MIT Energy Initiative, and co-author of a new paper detailing the findings. The results, she notes, can be evaluated by policymakers in different global regions to understand what the long-term, large-scale resource security risks may become for different parts of their populations.
“Anything that’s taking up half of your income is potentially destabilizing for your entire life because it leaves so few resources for the other critical needs and basic life necessities,” Morris says.
The study focuses on projecting future access to food, water, and energy, based on long-term variation across a dozen major factors influencing their availability, from economic conditions and agriculture production to trade conditions, climate, land use, and more.
“This study shows that there is no single driver of future food, energy, and water insecurity,” says Gi Joo Kim, a research scientist at Tulane University and co-author of the paper. “Income is important, but regional conditions, land use, energy systems, water availability, and consumer behavior all shape the risks people face.” For policymakers, he adds, “This means they need to consider specific combinations of factors that create vulnerability in each region.”
The paper, “Identifying Key Uncertainties and Drivers of Future Resource Security Outcomes Through a Multisector Scenario Ensemble,” appears in the journal Earth’s Future.
In addition to Morris and Kim, the authors include Brian O’Neill, an earth scientist at the Pacific Northwest National Laboratory; Marshall Wise, a system engineer at the Pacific Northwest National Laboratory; John Weyant, a professor of management science and engineering at Stanford University; and Jonathan Lamontagne, an associate professor of civil and environmental engineering at Tufts University.
Filling a gap
The current study fills a gap in modeling among scientists studying issues such as long-term resource security. Given the complications of long-term analyses, many studies have used what scientists term “shared socioeconomic pathway” circumstances, a small set of senarios spanning broad global narratives about the future, rather than exploring specific outcomes such as how long-term resource access may shift in linked fashion across income groups in different regions of the world. Two years ago, the same group of authors wrote a paper calling for more socioeconomically specific scenario analysis focused on outcomes for human well-being; the current study is their effort to develop that kind of modeling.
“For this type of study, where we’re focused on human well-being outcomes, the income piece is really important,” Morris says.
To conduct the study, the researchers adopted an existing framework in the field, the Global Change Analysis Model (GCAM) version 7.1, which represents interactions between energy, economies, water, land, and climate while dividing the world into 32 regions, 235 water basins, and 384 land-use regions and making adjustments for things like estimated commodity prices over time.
The research group used 12 main variables connected to resource availability, including population, GDP, income distribution, carbon intensity, land use, agricultural trade, multiple energy consumption scenarios, multiple water-use projections, and more. They ran simulations for 3,735 different scenarios involving these factors, to better understand the range of possible resource outcomes by 2050.
Broadly, the modeling does uncover some significant regional variations. In 2050 food security may be most acute in parts of sub-Saharan Africa, while energy security could be most acute for low-income residents in some parts of Asia, Eastern Europe, and the Middle East.
But within any region, there may still be substantial variation in resource security. In southern Africa, the modeling suggests that the poorest 10 percent of the population by income could be spending 49.6 percent of its income on food, compared to just 5.5 percent for the wealthiest 10 percent of the population. In West and East Africa the projected food burden for the bottom 10 percent of the population in terms of income is projected to be 48.4 percent and 42.5 percent, respectively.
To understand the potential change this represents over time, the researchers compared the results to data from the year 2015 in the GCAM model. For the lowest-income group across western Africa in 2015, the average food burden was about 25 percent of people’s income, compared to estimates for 2050 that range from about 20 percent to 75 percent of income. In southern Africa, the lowest-income group spent about 20 percent of their income on food in 2015, but the scholars’ modeling projects an increase in food burden ranging from 25 percent to 65 percent of income. The wide variation in projected burden reflects the wide range in possible future scenarios.
When it comes to energy, variation by income is also apparent. In some parts of the Middle East, for instance, the residential energy burden in 2050 is estimated to be just 1.7 percent for the highest income bracket but 18.9 for the lowest income bracket; in Eastern Europe, the energy burden reaches 11.3 percent of income for the lowest-income bracket, while resting at under 5 percent for the highest-income bracket.
“Regional averages can make future resource-security risks appear more manageable than they actually are,” Kim says. “This means analyses that stop at the average may miss exactly the populations most vulnerable to future change.”
Understanding the dynamics
To be sure, as the scholars emphasize, there are many uncertainties when it comes to resource access, and uncertainty is always part of modeling the global economy and resources. Still, they believe these kinds of projections can provide a more detailed outlook about social conditions in 2050 than has previously been available.
“At the very least, it’s highlighting areas of concern and showing that they differ in different parts of the world,” Morris says. “One of the outputs of this type of study is to map that out and provide that kind of insight. That can also inform the focus of further studies into specific regions and concerns.”
The researchers also believe the results will provide a new roadmap for policymakers who may be concerned about long-term resource provision across the entirety of their societies. While having new projections is valuable, modeling also helps analysts and policymakers see which factors most clearly influence future resource outcomes, as well.
“Our method was designed to identify the conditions that produce different resource security outcomes, rather than to predict one most likely future,” Kim says.
“It’s a different approach to scenarios than we typically see,” Morris adds. “The approach and method have been appealing to people because they have a broad range of uses and applications.”
The research was supported, in part, by the U.S. Department of Energy; Stanford University; and the National Research Foundation of Korea.
Governor Healey, MIT President Kornbluth to Kick Off Festivities at MIT Future Fest The five-day festival will explore the future of science, technology, art and design from Wednesday, Sept. 30 to Sunday, Oct. 4Massachusetts Governor Maura Healey and MIT President Sally Kornbluth will kick off MIT Future Fest, a new annual festival exploring the future of science, technology, art, and design, with “The Future Begins Here” panel, a celebration of Massachusetts innovation, talent and the bold questions shaping what comes next. The event will take place on Wednesday, September 30 at 3:30 PM at MIT’s Kresge Auditorium.
Curated and produced by the MIT Museum, the inaugural MIT Future Fest will take place across MIT’s campus from September 30–October 4, 2026. Governor Healy and President Kornbluth will be joined on the opening panel by Moderna co-founder and Flagship Pioneering founder and CEO Noubar Afeyan, MIT professor and entrepreneur Sangeeta Bhatia, and Bob Mumgaard, CEO and Co-Founder of Commonwealth Fusion Systems. Economic Development Secretary Eric Paley will moderate the discussion, which will explore how public, private, and educational institutions can work together to sustain talent pipelines, turn discovery into impact, and build the future
“Massachusetts is where the future is being invented, and MIT Future Fest is a chance to showcase our leadership in technology and design to the world,” said Governor Maura Healey. “From AI and robotics to clean energy and life sciences, the breakthroughs happening here are changing how we live and work. As Governor, I want Massachusetts to be the place where the best minds from around the world come to study, conduct research, start companies and scale their ideas. Our administration is investing in the talent, research and partnerships that make that possible, and we’re proud to launch MIT Future Fest with MIT.”
“The breakthrough discoveries that shape modern life came from decades of scientists and creators asking fundamental questions about how the world works. MIT Future Fest celebrates that same spirit of curiosity on mission," said MIT President Sally Kornbluth. "When you bring together engineers, inventors, artists, scientists, designers and entrepreneurs, you create the conditions for truly transformative innovation. This festival is an invitation to join that conversation, with the conviction that the future isn't something that happens to us—it's something we create together."
“The Future Beings Here” is one of more than 70 public talks, tours, performances, exhibitions, installations, and open laboratories included in the five-day program. Additional festival highlights and the full programming line-up are available at mitfuturefest.org.
New method allows scientists to follow gene activity over time in the same cells In the new method, cells package and export their RNA, enabling researchers to sequence and analyze the RNA without killing the cells.The following press release was issued Sept. 1 by the Broad Institute of MIT and Harvard.
In recent years, scientists have built methods to measure a cell’s transcriptome, or all the RNA produced by a cell, to study the cell’s identity and genetic activity. However, these methods rely on killing the cell to access the bits of RNA within, and offer only a one-time snapshot.
Now, researchers at the Broad Institute and at MIT have invented a “cellular self-reporting” approach to make living cells share their own transcriptomes, so that scientists can analyze them without killing the cells. Described in Cell, the live cell transcriptomic method relies on virus-like particles, which the cells use to package and deliver RNA to the culture medium they’re bathed in. Scientists can simply sample the medium to isolate the RNA, and do this repeatedly to reveal how gene activity in the same cell population changes as the cells mature or respond to perturbations. The researchers applied their method to a variety of cellular model systems, demonstrating its potential to help reveal how cells go awry over time in disease and how drugs affect cells.
“Our lab focuses our time and resources on developing tools that will actually get used and make real impact on the broader field,” says study senior author Paul Blainey, who is a core member of the Broad and a professor of biological engineering at MIT. “It’s so gratifying to see a real coming to fruition of this concept, which was complete science fiction when we started. It’s a great example of the innovative impact long-term high-risk, high-reward research can have.”
A cellular special delivery
The effort to build the new method began more than a decade ago, when the Blainey lab set out to find a new way to do RNA sequencing without killing cells. “The existing methods were a bit medieval and involved stabbing cells or cutting pieces off of them,” recalls Blainey. Inspired by the performance of molecular technologies such as CRISPR-based technology and their ease of adoption, Blainey and study first author Jacob Borrajo committed to developing a molecular method, which they knew would be challenging and take time, but would also make the approach scalable and easy for other labs to perform.
The team found inspiration in retroviruses, which over millions of years evolved the ability to package their RNA genomes in protein shells to spread from one infected cell to another. To build their method, the team engineered mammalian cells to express a retroviral structural protein that can encapsulate not only viral RNA but also a cell’s RNA. Integrated into the cell’s membrane, the viral protein is able to recruit cellular RNA, form a shell around it to create a virus-like particle, and bud off from the membrane to enter the liquid medium around the cell. The scientists then take a sample of the medium, isolate the RNA, and sequence it to get a view of the transcriptome from that cell population — all without destroying or damaging the cells.
“Compared to methods using robotics or mechanical biopsies of cells, our molecularly encoded solution could be much more broadly enabling for the average life science or biomedical lab, particularly the time dynamic questions that we hope to elucidate with this technology,” says co-first author Mohamad Najia, research fellow in the Blainey lab and the lab of George Daley at Boston Children’s Hospital. Najia and Borrajo led the work along with co-first author Anna Le, a postdoc in the Blainey lab.
Message in a bottle
To test the method’s broad applicability, the researchers showed that it worked in immortalized human cells, in cancer cell lines, in stem cells and neuronal cells made from them, and in primary cells from human donors. They also tested a culture of two human cell types growing together, using tags on the virus-like particles so that the signals from the two cell types could be distinguished during analysis.
In addition, cellular self-reporting is useful for studying systems with crucial three-dimensional structures that researchers would rather not disturb. The team demonstrated their method on spheroids of human endothelial cells, capturing short-term transcriptional changes after biochemically stimulating the cells.
They also collaborated with Linda Griffith, a professor of biological and mechanical engineering at MIT, to apply their method to her lab’s organ-on-a-chip devices. These models mimic the physiology of organs and can help minimize preclinical or animal model testing, but their complexity makes retrieving cells from the devices for analysis difficult. With cellular self-reporting, the researchers monitored gene expression dynamics in endothelial cells within the devices over time, revealing changes in genes related to how tissues form vascular networks that depended upon the source of supporting fibroblasts, such as from either uterus or lung.
The Broad team is continuing to look for new applications and biological questions to ask with their system, and are working to make the approach feasible for studying single cells. For now, they hope that scientists interested in following how cells and tissues change over time will give their method a try.
Stories from the steel mills: A model for sharing workers’ historiesMIT anthropologist Chris Walley developed a project for people in Southeast Chicago to tell their histories — an approach any community can adopt.For generations, the steel mills of Southeast Chicago offered work and a way of life, experienced by tens of thousands of families. Open around the clock, three shifts per day, the vast works of U.S. Steel, Republic Steel, Inland Steel, and many others provided demanding but steady jobs, while making materials to build the country.
Professor Christine Walley, head of the MIT Anthropology program, grew up in the area, where her father worked for Wisconsin Steel. Over time, U.S. manufacturing downsized — her father’s plant closed in 1980 — and the mills left Chicago. Walley’s 2013 book, “Exit Zero: Family and Class in Postindustrial Chicago,” chronicles the economic and psychological toll plant closures took on the area’s workers and families. The book was followed by a documentary, “Exit Zero,” directed by Chris Boebel, director of video at MIT Open Learning (and Walley’s husband).
Then Walley turned to a new effort — the Southeast Chicago Archive and Storytelling Project, an online repository of objects and images, as well as new video features about the industry, labor history, and the local community. The project was developed in collaboration with a team from the Southeast Chicago Historical Society, which in 1985 opened a museum about the steelworking life. This award-winning newer online project has been supported, in part, by MIT, the National Endowment for the Humanities, and others.
The idea is to use objects to tell stories about the area’s history. To mark Labor Day, MIT News offers this photo essay based on materials from the Southeast Chicago Archive and Storytelling Project, recognizing America’s workers — and reflecting on the jobs, work, and life produced by industry and innovation.
It’s hard to depict the vastness of Southeast Chicago’s steel manufacturing area, which stretched for miles into Northwest Indiana and included mills that employed 120,000 workers at their peak. This vintage postcard shows the industry along the Calumet River.
MIT’s 12th president, Howard Johnson, grew up in the area during the Great Depression, where family members toiled in the mills. Johnson’s father worked for U.S. Steel for 50 years, becoming a bookkeeper and accountant, and Johnson attended Bowen High School, which is still open today.
“Families — ours and thousands like it — were the essential centers of life in the community,” Johnson writes in his memoir, published by the MIT Press.
Families have also been essential to the Southeast Chicago Archive and Storytelling Project, which displays more than 1,100 items from the local historical museum’s collection: clothing, photos, scrapbooks, news clippings, recreational objects, oral history materials, and more. Walley says that anyone could take this approach, and use objects to tell stories about their own local history, work, and community life.
“People tend to experience history in their day-to-day lives not through books written by experts, but by telling stories around family objects and photos,” Walley says. “What is meaningful to us about the things we save from the past? Might these items be ‘clues’ that take us on a deeper historical journey?”
Kitty Kalwasinski Markovich (above, left) didn’t set out to become a welder — but as one, she nearly appeared the movies. Born Kazmira Kalwasinski, she immigrated with her family to Chicago from Poland in 1913, at age 10. During World War II, the steel mills sought replacements for men serving in the military, and she started welding at the South Works of U.S. Steel in Chicago.
Warner Brothers depicted her in this photo shoot (with Florence Josephs, right), as a worker in the “Rosie the Riveter” mode, and considered making a film featuring her. Five of her brothers served in the military, and their names are seen on Markovich’s welding helmet. One of them, Frank Kalwasinski, was killed in World War II, and his sacrifice is represented by the solid star.
Although many American women returned to their former lives as homemakers at the conclusion of the war, Markovich kept working in the mills, welding for 23 years in the South Works before she retired in 1967. It’s also where she met her husband, Michael Markovich. Kitty Kalwasinski Markovich’s family donated many materials to the Southeast Chicago Archive and Storytelling Project.
This hard hat, made around 1986, was donated to the Southeast Chicago Historical Museum along with a cutting from the last beam ever produced at U.S. Steel’s once-mighty South Works, which closed in 1992, having produced steel since the 1800s.
At its peak, South Works employed about 20,000 people. The Chicago steel mill closures, the 1970s through the 1990s, devastated employees and their families who, as Walley details in the “Exit Zero” book, identified strongly with steelworking. Her own father was a third-generation steelworker.
The online storytelling project deploys MIT scholar Sherry Turkle’s notion of “evocative objects,” those that hold great resonance and get our minds in motion. As Turkle writes, “we love the objects we think with.”
Donated to the museum by James Stapay, this hard hat evokes the end of a long industrial era in Chicago, and is featured in “The Closing of the Mills,” one of the project’s four documentary videos created from donated objects.
Working in steel mills was not just physically demanding, but dangerous. Worker injuries and deaths were a recognized problem, especially in the early years. This is prototype safety gear from around 1911-12, from a series of photo albums donated to the Southeast Chicago Historical Society by U.S. Steel itself in the 1980s.
U.S. Steel set up a Committee of Safety early in the 1900s, which recommended 3,000 changes to operations. However, in oral history interviews, workers often recount continuing dangers and terrible accidents in the steel mills.
Some first-person accounts state that as late as the 1960s, workers were still not regularly wearing hard hats. Basic safety practices seemed to improve, though, after the introduction of the U.S. Occupational Safety and Health Administration in 1970. Worker safety was a long-term work in progress.
Many of the close-knit communities formed around the mills have donated materials to the project that range far beyond the factory. For instance, family recreation was important in steelworks neighborhoods. Pictured here, in a photo donated by the Cordero family, is the “Mayas” softball team, made up of members of Southeast Chicago’s Mexican-American community, which won a 1937 community league championship.
Justino Cordero immigrated to Chicago in 1923, became a steelworker, then eventually did electrical work in the mills while opening a radio shop. Cordero, a father of three (two of his children are pictured), organized and coached youth sports teams to keep kids “out of trouble”; wrote a column for The Daily Calumet, a local newspaper; and was involved with his church, Our Lady of Guadalupe. After retirement, Cordero earned undergraduate and master’s degrees, to work with children with disabilities.
Another documentary video from the Southeast Chicago Archive and Storytelling Project, “Mexican-American Journeys,” explores the long history of Mexican-American steelworkers in Chicago, in many dimensions. At least a dozen parishoners of Our Lady of Guadalupe members who had been in the U.S. military in the 1960s were killed in the Vietnam War, serving their country.
In 1937, steelworkers went on strike in Chicago. On Memorial Day, during a peaceful protest at Republic Steel, 10 workers were killed by law enforcement officials — an event that provoked congressional hearings in Washington. The image at left is a poster made up for Local 1033, the union branch for the Republic Steel plant; at right, Local 1033 workers take a vote in later years.
While the so-called “Memorial Day Massacre” was a landmark event in national labor history, it is remembered in more intimate ways in the local area, with many families later donating photos, news clippings, scrapbooks, and interviews about it to the Southeast Chicago Historical Society.
And though the Southeast Chicago Archive and Storytelling Project project focuses heavily on working-class employment and daily life, there are many other possibilities for U.S. community-based history, involving almost any topic. Whatever the places, objects, and stories, but the goal is the same: to keep the past alive.
Fabrication platform could enable flexible, transparent next-generation photonic chipsThis scalable process produces high-performance chips for applications like discreet wearables or pliable augmented-reality displays.The field of silicon photonics, which uses light rather than electricity to transmit and process data on semiconductor chips, has enabled optical systems to evolve from bulky setups to compact and advanced systems. Typically, however, these silicon-photonics chips are rigid and opaque.
MIT scientists have now figured out a scalable way to make silicon-photonics chips flexible and transparent, opening a route to advanced microchips that could be used in applications such as discreet health monitors that conform to the body or transparent augmented-reality displays that fit the curve of a pilot’s helmet.
While scientists have recently performed lab demonstrations of chips that were flexible or transparent, they could only fabricate a few devices at a time.
The MIT researchers, in close collaboration with engineers at NY Creates at the Albany NanoTech Complex, created a fabrication process that uses standard semiconductor manufacturing techniques to generate flexible and transparent silicon-photonics chips on large-scale wafers.
To validate this platform, the researchers bent a single chip thousands of times around cylinders with various diameters — down to the width of a small screw — with no drop in performance. They also determined that looking through the chips would not cause much haze or distortion.
“We’ve now developed a wafer-scale process that produces wafers that are mechanically flexible and optically transparent, enabling novel applications that weren’t previously possible with silicon photonics. We hope that, by working closely with our colleagues at NY Creates and using the foundry at the Albany NanoTech Complex, there’s the potential for us to make the platform accessible to other groups within our research community and open these new application areas to the field of silicon photonics as a whole,” says Jelena Notaros, the Robert J. Shillman Career Development Associate Professor of Electrical Engineering and Computer Science (EECS) at MIT, a member of the Research Laboratory of Electronics, and senior author of a paper on this fabrication platform.
Her co-authors include lead author Tal Sneh and Andres Garcia Coleto, EECS graduate students; Thomas Dyer and Kevin Fealey of the New York Center for Research, Economic Advancement, Technology, Engineering, and Science (NY Creates); and Milica Notaros PhD ’23. The paper appears in the journal Optica.
Flexible and transparent
Over the past decade, researchers have developed techniques to fabricate precise and highly reliable silicon-photonics devices at scale.
They use advanced microelectronics foundry processes to produce 300-millimeter-diameter wafers with billions of nanoscale optical devices. But these methods yield silicon-photonics chips that are rigid and opaque.
“We realized that there are a lot of applications that would benefit from having a chip that is flexible and transparent,” Notaros says.
Scientists have previously made single silicon-photonics chips that were either transparent or flexible, but these techniques weren’t scalable. To address this scaling challenge, Notaros’ group recently demonstrated a foundry-scale process for making silicon-photonics chips on a flexible substrate.
Now, the team pushed these innovations even farther with a scalable process that produces 300-millimeter silicon-photonics wafers that are both transparent and flexible.
Their fabrication process begins as if they were making a traditional, rigid silicon wafer. The researchers carefully deposit and pattern tiny optical wires known as waveguides onto this rigid silicon substrate.
Then they bond a temporary silicon wafer on top. They flip the wafer over and remove all of the original silicon substrate from what is now the top of the wafer. They are then left with a flat layer of material with a thickness less than a tenth of a human hair.
“Thanks to the fact that we added that rigid temporary support before we flipped the wafer over, we can go all the way down so we are just left with the oxide and waveguiding layers,” Sneh says.
They use an adhesive to stick a thin, transparent polyester film on top of these ultrathin layers and “de-bond” the temporary silicon wafer from the bottom to remove it.
This leaves them with a flexible, transparent wafer only a few microns thick that contains the oxide and waveguide layers needed to capture and transport light for silicon photonics.
“Because we are using stable 300-millimeter foundry fabrication tools, we can design systems with a very large number of devices and feel confident that they are going to perform up to specifications, which is extremely important,” Sneh adds.
The biggest challenge in developing this fabrication process was removing enough material from a large 300-millimeter-diameter silicon wafer to leave only a few microns of material behind.
During fabrication, stress on the wafer typically causes it to bow slightly, making this silicon removal process especially challenging.
“As we were flipping the wafers over on these substrates, if the strain isn’t properly managed and the wafer isn’t perfectly flat, it is going to get ripples across its surface or even shatter in the fabrication line,” Dyer says.
The researchers carefully managed that stress by sticking to low temperature processes at or below 500 degrees Celsius.
They also had to find the right ordering and combination of removal methods.
They used industrial processes to thin the silicon layer, but switched to a more precise selective chemical etch for the last bit. This ensured they would not damage the ultrathin layers left behind.
An eye on performance
The researchers performed three experiments to test different functionalities of these flexible, transparent silicon-photonics wafers.
First, they tested the optical performance of chips with integrated waveguides of different lengths to determine their waveguiding properties.
Then they tested flexibility by bending a chip thousands of times around cylinders with different diameters. These experiments showed no degradation in performance even when they bent it around a cylinder about the size of a small screw. The device didn’t start to degrade until the researchers bent it around a toothpick several times.
“This experiment validated that the platform can be used for our proposed applications, performing even well beyond the metrics required for these intended systems,” Garcia Coleto says.
They also evaluated transparency by setting up a bionic eye and testing whether the chip would distort the user’s vision when placed in front of the eye. They found that the chip causes only minimal haze for the viewer and would not noticeably distort images the eye perceives when looking through it.
These characteristics could make these chips especially well-suited for enabling silicon-photonics systems for applications like curved augmented-reality displays that conform to a heads-up-display windshield or airplane pilot’s visor. In a pilot’s visor, for instance, such an augmented-reality display could replace the heavy bulk-optical systems that currently provide real-time information to help the pilot react to dangerous conditions.
In the future, the researchers want to add more complex components and functionality to the chips as they move toward enabling these and other new applications. They also want to refine the design to further improve waveguide efficiency and boost transparency performance.
This research was funded, in part, by the National Science Foundation, the U.S. Defense Advanced Research Projects Agency, and a MathWorks Fellowship. Wafer processing was performed at NY Creates, and chip dicing was conducted at MIT.nano.
“You're going to see the impact in 10 years” - President Kornbluth returns to GBH’s “Boston Public Radio” to discuss scientific funding and curiosity driven researchKornbluth weighed in on the consequences of cuts to federal funding for science and the value of curiosity driven research.President Sally Kornbluth took to GBH’s “Boston Public Radio” (BPR) to discuss the value of scientific research amid cuts to federal funding and the new endowment tax impacting MIT and other universities. In her wide-ranging conversation with hosts Jim Braude and Margery Eagan, Kornbluth highlighted ‘Curiosity on a mission,’ MIT’s support for quantum technology, artificial intelligence and research—and where to get soft serve ice cream.
“The best science is scientists just following their instincts, trying to find the answers to fundamental questions,” said Kornbluth.
Scientific discovery is born from a long sequence of experiments, funded largely by federal grants, “but it's not just scientists doing [research] for their own sake,” she explains. “It's all these discoveries on a mission to do important things in the world, whether it's curing diseases or finding new materials or finding new ways to construct buildings.”
Currently, MIT has seen a 20% decline in federal funding, limiting graduate admissions and threatening future breakthroughs. Kornbluth emphasized, “[Researchers] have to go down a lot of blind alleyways following your curiosity to hit the things that are going to have major impact down the road.”
Kornbluth also touched on the impact of the endowment tax on MIT. “We've had to make a lot of budgetary cuts to accommodate the endowment tax and the losses in federal funding, so if you put it together, people have really had to tighten their belts…and really focus to keep our research mission,” she said.
The consequences of restricting research now may be felt a decade later.
Referencing the impacts of long-term research free from short-term pressures of politics and profit, Kornbluth mentioned Prof. Robert Weinberg’s discovery that RAS genes can mutate into many different cancers, including pancreatic cancer. “It's now been shown that RAS could be druggable,” explained Kornbluth. “So, this discovery that was made by Bob 45 years ago is now being translated into RAS targeting drugs that could lead to treatments of cancers like pancreatic cancer.”
Future treatments for cancer, and other diseases, are based on the discoveries made today. “If you look at some of the stuff like immunotherapy for cancer now, that was 40, 50, years of immunology research,” said Kornbluth. “People might not see the impact [of funding cuts] immediately, but you're going to see the impact in 10 years, and your children and your children's children will see the impact.”
Restrictions by the government are not limited to funding cuts. About 40% of MIT’s graduate student population are international students. Kornbluth explained to the hosts how the four-year cap on student visas by the Trump administration is incompatible with the amount of time it takes to obtain a PhD, which is usually at least five to six years.
“This [four-year cap] is untenable for PhD students,” said Kornbluth. She emphasized the many ways international students contribute to research and the economy in the U.S.
“I trained so many fabulous students from all over the world who are now professors in American universities, or working for American industries, or starting their own American companies.”
Though cuts to funding threaten the research pipeline, Kornbluth is confident that technologies such as AI and quantum can advance work at MIT and beyond. She believes that AI will change, not replace, the work of PhD students. “[AI] is going to make each graduate student sort of like a mini faculty member,” said Kornbluth. “They're going to get to have AI agents that can explore multiple ideas with them.”
Looking ahead, Kornbluth outlined her work with Governor Maura Healey to advance quantum technology in Massachusetts, which is “the future in so many things… It's much more efficient in computing, much more sensitive at sensing things like molecules in the blood, like viewing from a canopy what's happening underneath,” she explained.
In May, Healey and Kornbluth announced plans for the Quantum Systems Laboratory at MIT, a shared space for academic and commercial development in quantum, open to researchers both from and beyond MIT.
“We need to make sure that Massachusetts is at the forefront, and so we're building this quantum systems laboratory that is going to have quantum computing but also figure out an interconnect between different forms of quantum computing,” Kornbluth expressed.
The President’s segment on BPR concluded on a sweet note: soft serve.
Kornbluth shouted out the soft serve at Eastern Edge, MIT’s new food hall, that was recently featured in “Soft Serve with Scientists,” a new feature with the host of GBH’s “Curiosity Desk.”
“I was really lobbying hard for the soft serve machine,” revealed Kornbluth.
Off campus? Kornbluth recommends Momma’s Grocery located near Porter Square and the Charles River Speedway. Her favorite is “the maple creamy with the maple sprinkles.”
Archived: Building 18 UpdatesFrom Thursday, August 27th through Sunday, August 30th, MIT Emergency Management posted the following messages on emergency.mit.net regarding an incident at Building 18. As that resource is intended for active issues, these updates, which reflect MIT’s public information on this topic, are archived below.
Building 18 to reopen at 6 a.m. Monday
Aug. 30, 2026, 10:16 p.m.
Appropriate decontamination protocols have now been completed in the lab space of the student who reported attempting the synthesis of dimethyl mercury. Given the actions we have taken and the information received, as well as consultations with industrial hygienists, medical experts at MIT Health, and outside experts, it is our assessment that it is now safe to reopen Building 18. The building will reopen at 6 a.m. tomorrow, Monday, August 31.
Decontamination of the sealed suite in the impacted residence hall has also been successfully completed. The residence hall, which was never closed, remains open. For a campus map, visit https://whereis.mit.edu.
Building 18 - update— Aug. 29, 2026, 3:36 p.m.
Offices across campus have been responding to a reported hazardous material incident involving a single individual in a chemistry laboratory. The Institute became aware of the matter after the individual, a graduate student, self-reported to a local emergency room and claimed to have synthesized dimethyl mercury, a compound that is not authorized as part of their research program. Emerging information calls into question whether this compound was in fact synthesized. We are also able to disclose, with the student’s permission, that while the student remains under medical supervision, their initial blood test result, which was received today, shows no sign of exposure to mercury.
Building 18 remains closed at least through Sunday as specialized decontamination efforts continue out of an abundance of caution. This work will continue, and the building will remain closed until the work is complete.
Also out of an abundance of caution, high-touch surfaces in the common areas of the individual’s residence hall were professionally cleaned under the supervision of MIT Environmental Health and Safety (EHS), and decontamination of the resident’s sealed unit is ongoing, as has been shared with residents of the building. The residence remains open and in normal operation, and no restrictions have been placed on the building.
With a focus on public health, decontamination efforts have been ongoing and baseline testing was offered to individuals who were in proximity to the student and their work environment on Wednesday, August 26. As the chemistry department, industrial hygienists, MIT Health medical experts, and other resources consulted collect additional information, we continue to believe there is a very low risk of secondary or tertiary exposures. At this time testing is not recommended by MIT Health officials for any members of the community who did not enter the individual’s lab space on Wednesday.
We continue to gather information about this situation and will update this page if we have more to share. For a campus map, visit https://whereis.mit.edu
Building 18 - update— Aug. 28, 2026, 11:21 a.m.
Building 18 remains closed today as specialized decontamination efforts continue out of an abundance of caution. This work will continue throughout the day, and the building will remain closed until the work is complete.
It remains the case that, based on the information available, this was a localized issue with only one student directly exposed, and this student was the individual working with the compound. Their reported use of the material was unauthorized.
As has been shared with those who work in the building, based on the information available to the department, industrial hygienists, MIT Health medical experts, and other resources consulted, the risk of secondary or tertiary exposures is low, given the compound's characteristics and the information available. For a campus map, visit https://whereis.mit.edu
Building 18 closed— Aug. 27, 2026, 1 p.m.
Out of an abundance of caution, Building 18 is closed for the day following notice of an individual exposed to a hazardous material in a second floor laboratory. City emergency responders were on scene overnight, and cleanup is underway. Building occupants will be notified when the building reopens.
An investigation into the incident is ongoing.
Focused outreach is underway for those who access the impacted laboratory. Support resources are available for members of the MIT community. A comprehensive list of student support resources is accessible at https://doingwell.mit.edu/support/. MyLife Services is among the resources available to all others on campus, with more information at https://health.mit.edu/mit-mit/employees/employee-support-programs.
This page will be updated when the building reopens. For a campus map, visit https://whereis.mit.edu