In 2000, Patrick J. McGovern ’59 and Lore Harp McGovern made an extraordinary gift to establish the McGovern Institute for Brain Research at MIT, driven by their deep curiosity about the human mind and their belief in the power of science to change lives. Their $350 million pledge began with a simple yet audacious vision: to understand the human brain in all its complexity, and to leverage that understanding for the betterment of humanity.
 
Twenty-five years later, the McGovern Institute stands as a testament to the power of interdisciplinary collaboration, continuing to shape our understanding of the brain and improve the quality of life for people worldwide.

In the beginning

“This is, by any measure, a truly historic moment for MIT,” said MIT’s 15th president, Charles M. Vest, during his opening remarks at an event in 2000 to celebrate the McGovern gift agreement. “The creation of the McGovern Institute will launch one of the most profound and important scientific ventures of this century in what surely will be a cornerstone of MIT scientific contributions from the decades ahead.”
 
Vest tapped Phillip A. Sharp, MIT Institute professor emeritus of biology and Nobel laureate, to lead the institute, and appointed six MIT professors — Emilio Bizzi, Martha Constantine-Paton, Ann Graybiel PhD ’71, H. Robert Horvitz ’68, Nancy Kanwisher ’80, PhD ’86, and Tomaso Poggio — to represent its founding faculty.  Construction began in 2003 on Building 46, a 376,000 square foot research complex at the northeastern edge of campus. MIT’s new “gateway from the north” would eventually house the McGovern Institute, the Picower Institute for Learning and Memory, and MIT’s Department of Brain and Cognitive Sciences.

Robert Desimone, the Doris and Don Berkey Professor of Neuroscience at MIT, succeeded Sharp as director of the McGovern Institute in 2005, and assembled a distinguished roster of 22 faculty members, including a Nobel laureate, a Breakthrough Prize winner, two National Medal of Science/Technology awardees, and 15 members of the American Academy of Arts and Sciences.
 
A quarter century of innovation

On April 11, 2025, the McGovern Institute celebrated its 25th anniversary with a half-day symposium featuring presentations by MIT Institute Professor Robert Langer, alumni speakers from various McGovern labs, and Desimone, who is in his 20th year as director of the institute.

Desimone highlighted the institute’s recent discoveries, including the development of the CRISPR genome-editing system, which has culminated in the world’s first CRISPR gene therapy approved for humans — a remarkable achievement that is ushering in a new era of transformative medicine. In other milestones, McGovern researchers developed the first prosthetic limb fully controlled by the body’s nervous system; a flexible probe that taps into gut-brain communication; an expansion microscopy technique that paves the way for biology labs around the world to perform nanoscale imaging; and advanced computational models that demonstrate how we see, hear, use language, and even think about what others are thinking. Equally transformative has been the McGovern Institute’s work in neuroimaging, uncovering the architecture of human thought and establishing markers that signal the early emergence of mental illness, before symptoms even appear.

Synergy and open science
 
“I am often asked what makes us different from other neuroscience institutes and programs around the world,” says Desimone. “My answer is simple. At the McGovern Institute, the whole is greater than the sum of its parts.”
 
Many discoveries at the McGovern Institute have depended on collaborations across multiple labs, ranging from biological engineering to human brain imaging and artificial intelligence. In modern brain research, significant advances often require the joint expertise of people working in neurophysiology, behavior, computational analysis, neuroanatomy, and molecular biology. More than a dozen different MIT departments are represented by McGovern faculty and graduate students, and this synergy has led to insights and innovations that are far greater than what any single discipline could achieve alone.
 
Also baked into the McGovern ethos is a spirit of open science, where newly developed technologies are shared with colleagues around the world. Through hospital partnerships for example, McGovern researchers are testing their tools and therapeutic interventions in clinical settings, accelerating their discoveries into real-world solutions.

The McGovern legacy  

Hundreds of scientific papers have emerged from McGovern labs over the past 25 years, but most faculty would argue that it’s the people — the young researchers — that truly define the McGovern Institute. Award-winning faculty often attract the brightest young minds, but many McGovern faculty also serve as mentors, creating a diverse and vibrant scientific community that is setting the global standard for brain research and its applications. Kanwisher, for example, has guided more than 70 doctoral students and postdocs who have gone on to become leading scientists around the world. Three of her former students, Evelina Fedorenko PhD ’07, Josh McDermott PhD ’06, and Rebecca Saxe PhD ’03, the John W. Jarve (1978) Professor of Brain and Cognitive Sciences, are now her colleagues at the McGovern Institute. Other McGovern alumni shared stories of mentorship, science, and real-world impact at the 25th anniversary symposium.

Looking to the future, the McGovern community is more committed than ever to unraveling the mysteries of the brain and making a meaningful difference in lives of individuals at a global scale.
 
“By promoting team science, open communication, and cross-discipline partnerships,” says institute co-founder Lore Harp McGovern, “our culture demonstrates how individual expertise can be amplified through collective effort. I am honored to be the co-founder of this incredible institution — onward to the next 25 years!”

The firefighter health program was researching firefighters’ chemical exposures in electric vehicle fires — a first step to developing protective equipment.

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While President Donald Trump and Elon Musk are attacking the $100 billion plan, Democrats hold the real power over its fate — and they're not fully on board.

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At a measuring site 4,667 feet high in the Swiss canton of Valais, 23 inches of snow fell Wednesday.

One of the most exciting developments in cancer treatment is a wave of new cell therapies that train a patient’s immune system to attack cancer cells. Such therapies have saved the lives of patients with certain aggressive cancers and few other options. Most of these therapies work by teaching immune cells to recognize and attack specific proteins on the surface of cancer cells.

Unfortunately, most proteins found on cancer cells aren’t unique to tumors. They’re also often present on healthy cells, making it difficult to target cancer aggressively without triggering dangerous attacks on other tissue. The problem has limited the application of cell therapies to a small subset of cancers.

Now Senti Bio is working to create smarter cell therapies using synthetic biology. The company, which was founded by former MIT faculty member and current MIT Research Associate Tim Lu ’03, MEng ’03, PhD ’08 and Professor James Collins, is equipping cells with gene circuits that allow the cells to sense and respond to their environments.

Lu, who studied computer science as an undergraduate at MIT, describes Senti’s approach as programming living cells to behave more like computers — responding to specific biological cues with “if/then” logic, just like computer code.

“We have innovated a cell therapy that says, ‘Kill anything displaying the cancer target, but spare anything that has this healthy target,’” Lu explains. “Despite the promise of certain cancer targets, problems can arise when they are expressed on healthy cells that we want to protect. Our logic gating technology was designed to recognize and avoid killing those healthy cells, which introduces a whole spectrum of additional cancers that don’t have a single clean target that we can now potentially address. That’s the power of embedding these cells with logic.”

The company’s lead drug candidate aims to help patients with acute myeloid leukemia (AML) who have experienced a relapse or are unresponsive to other therapies. The prognosis for such patients is poor, but early data from the company’s first clinical trial showed that two of the first three patients Senti treated experienced complete remission, where subsequent bone marrow tests couldn’t detect a single cancer cell.

“It’s essentially one of the best responses you can get in this disease, so we were really excited to see that,” says Lu, who served on MIT’s faculty until leaving to lead Senti in 2022.

Senti is expecting to release more patient data at the upcoming American Association for Cancer Research (AACR) meeting at the end of April.

“Our groundbreaking work at Senti is showing that one can harness synthetic biology technologies to create programmable, smart medicines for treating patients with cancer,” says Collins, who is currently MIT’s Termeer Professor of Medical Engineering and Science. “This is tremendously exciting and demonstrates how one can utilize synthetic biological circuits, in this case logic gates, to design highly effective, next-generation living therapeutics.”

From computer science to cancer care

Lu was inspired as an undergraduate studying electrical engineering and computer science by the Human Genome Project, an international race to sequence the human genome. Later, he entered the Harvard-MIT Health Sciences and Technology (HST) program, through which he earned a PhD from MIT in electrical and biomedical imaging and an MD from Harvard. During that time, he worked in the lab of his eventual Senti co-founder James Collins, a synthetic biology pioneer.

In 2010, Lu joined MIT as an assistant professor with a joint appointment in the departments of Biological Engineering and of Electrical Engineering and Computer Science. Over the course of the next 14 years, Lu led the Synthetic Biology Group at MIT and started several biotech companies, including Engine Biosciences and Tango Therapeutics, which are also developing precision cancer treatments.

In 2015, a group of researchers including Lu and MIT Institute Professor Phillip Sharp published research showing they could use gene circuits to get immune cells to selectively respond to tumor cells in their environment.

“One of the first things we published focused on the idea of logic gates in living cells,” Lu says. “A computer has ‘and’ gates, ‘or’ gates, and ‘not’ gates that allow it to perform computations, and we started publishing gene circuits that implement logic into living cells. These allow cells to detect signals and then make logical decisions like, ‘Should we switch on or off?’”

Around that time, the first cell therapies and cancer immunotherapies began to be approved by the Food and Drug Administration, and the founders saw their technology as a way to take those approaches to the next level. They officially founded Senti Bio in 2016, with Lu taking a sabbatical from MIT to serve as CEO.

The company licensed technology from MIT and subsequently advanced the cellular logic gates so they could work with multiple types of engineered immune cells, including T cells and “natural killer” cells. Senti’s cells can respond to specific proteins that exist on the surface of both cancer and healthy cells to increase selectivity.

“We can now create a cell therapy where the cell makes a decision as to whether to kill a cancer cell or spare a healthy cell even when those cells are right next to each other,” Lu says. “If you can’t distinguish between cancerous and healthy cells, you get unwanted side effects, or you may not be able to hit the cancer as hard as you’d like. But once you can do that, there’s a lot of ways to maximize your firepower against the cancer cells.”

Hope for patients

Senti’s lead clinical trial is focusing on patients with relapsed or refractory blood cancers, including AML.

“Obviously the most important thing is getting a good response for patients,” Lu says. “But we’re also doing additional scientific work to confirm that the logic gates are working the way we expect them to in humans. Based on that information, we can then deploy logic gates into additional therapeutic indications such as solid tumors, where you have a lot of the same problems with finding a target.”

Another company that has partnered with Senti to use some of Senti’s technology also has an early clinical trial underway in liver cancer. Senti is also partnering with other companies to apply its gene circuit technology in areas like regenerative medicine and neuroscience.

“I think this is broader than just cell therapies,” Lu says. “We believe if we can prove this out in AML, it will lead to a fundamentally new way of diagnosing and treating cancer, where we’re able to definitively identify and target cancer cells and spare healthy cells. We hope it will become a whole new class of medicines moving forward.”

Programmers can now use large language models (LLMs) to generate computer code more quickly. However, this only makes programmers’ lives easier if that code follows the rules of the programming language and doesn’t cause a computer to crash.

Some methods exist for ensuring LLMs conform to the rules of whatever language they are generating text in, but many of these methods either distort the model’s intended meaning or are too time-consuming to be feasible for complex tasks.

A new approach developed by researchers at MIT and elsewhere automatically guides an LLM to generate text that adheres to the rules of the relevant language, such as a particular programming language, and is also error-free. Their method allows an LLM to allocate efforts toward outputs that are most likely to be valid and accurate, while discarding unpromising outputs early in the process. This probabilistic approach boosts computational efficiency.

Due to these efficiency gains, the researchers’ architecture enabled small LLMs to outperform much larger models in generating accurate, properly structured outputs for several real-world use cases, including molecular biology and robotics.

In the long run, this new architecture could help nonexperts control AI-generated content. For instance, it could allow businesspeople to write complex queries in SQL, a language for database manipulation, using only natural language prompts.

“This work has implications beyond research. It could improve programming assistants, AI-powered data analysis, and scientific discovery tools by ensuring that AI-generated outputs remain both useful and correct,” says João Loula, an MIT graduate student and co-lead author of a paper on this framework.

Loula is joined on the paper by co-lead authors Benjamin LeBrun, a research assistant at the Mila-Quebec Artificial Intelligence Institute, and Li Du, a graduate student at John Hopkins University; co-senior authors Vikash Mansinghka ’05, MEng ’09, PhD ’09, a principal research scientist and leader of the Probabilistic Computing Project in the MIT Department of Brain and Cognitive Sciences; Alexander K. Lew SM ’20, an assistant professor at Yale University; Tim Vieira, a postdoc at ETH Zurich; and Timothy J. O’Donnell, an associate professor at McGill University and a Canada CIFAR AI Chair at Mila, who led the international team; as well as several others. The research will be presented at the International Conference on Learning Representations.

Enforcing structure and meaning

One common approach for controlling the structured text generated by LLMs involves checking an entire output, like a block of computer code, to make sure it is valid and will run error-free. If not, the user must start again, racking up computational resources.

On the other hand, a programmer could stop to check the output along the way. While this can ensure the code adheres to the programming language and is structurally valid, incrementally correcting the code may cause it to drift from the meaning the user intended, hurting its accuracy in the long run.

“It is much easier to enforce structure than meaning. We can quickly check whether something is in the right programming language, but to check its meaning you have to execute the code. Our work is also about dealing with these different types of information,” Loula says.

The researchers’ approach involves engineering knowledge into the LLM to steer it toward the most promising outputs. These outputs are more likely to follow the structural constraints defined by a user, and to have the meaning the user intends.

“We are not trying to train an LLM to do this. Instead, we are engineering some knowledge that an expert would have and combining it with the LLM’s knowledge, which offers a very different approach to scaling than you see in deep learning,” Mansinghka adds.

They accomplish this using a technique called sequential Monte Carlo, which enables parallel generation from an LLM to compete with each other. The model dynamically allocates resources to different threads of parallel computation based on how promising their output appears.

Each output is given a weight that represents how likely it is to be structurally valid and semantically accurate. At each step in the computation, the model focuses on those with higher weights and throws out the rest.

In a sense, it is like the LLM has an expert looking over its shoulder to ensure it makes the right choices at each step, while keeping it focused on the overall goal. The user specifies their desired structure and meaning, as well as how to check the output, then the researchers’ architecture guides the LLM to do the rest.

“We’ve worked out the hard math so that, for any kinds of constraints you’d like to incorporate, you are going to get the proper weights. In the end, you get the right answer,” Loula says.

Boosting small models

To test their approach, they applied the framework to LLMs tasked with generating four types of outputs: Python code, SQL database queries, molecular structures, and plans for a robot to follow.

When compared to existing approaches, the researchers’ method performed more accurately while requiring less computation.

In Python code generation, for instance, the researchers’ architecture enabled a small, open-source model to outperform a specialized, commercial closed-source model that is more than double its size.

“We are very excited that we can allow these small models to punch way above their weight,” Loula says.

Moving forward, the researchers want to use their technique to control larger chunks of generated text, rather than working one small piece at a time. They also want to combine their method with learning, so that as they control the outputs a model generates, it learns to be more accurate.

In the long run, this project could have broader applications for non-technical users. For instance, it could be combined with systems for automated data modeling, and querying generative models of databases.

The approach could also enable machine-assisted data analysis systems, where the user can converse with software that accurately models the meaning of the data and the questions asked by the user, adds Mansinghka.

“One of the fundamental questions of linguistics is how the meaning of words, phrases, and sentences can be grounded in models of the world, accounting for uncertainty and vagueness in meaning and reference. LLMs, predicting likely token sequences, don’t address this problem. Our paper shows that, in narrow symbolic domains, it is technically possible to map from words to distributions on grounded meanings. It’s a small step towards deeper questions in cognitive science, linguistics, and artificial intelligence needed to understand how machines can communicate about the world like we do,” says O’Donnell.

This research is funded, in part, by the Canada CIFAR AI Chairs Program, the MIT Quest for Intelligence, and Convergent Research. 

The following is part of a series of short interviews from the Department of Electrical Engineering and Computer Science (EECS). Each spotlight features a student answering questions about themselves and life at MIT. Today’s interviewee, YongYan (Crystal) Liang, is a senior majoring in EECS with a particular interest in bioengineering and medical devices — which led her to join the Living Machines track as part of New Engineering Education Transformation (NEET) at MIT. An Advanced Undergraduate Research Opportunities Program (SuperUROP) scholar, Liang was supported by the Nadar Foundation Undergraduate Research and Innovation Scholar award for her project, which focused on steering systems for intravascular drug delivery devices. A world traveler, Liang has also taught robotics to students in MISTI Global Teaching Labs (GTL) programs in Korea and Germany — and is involved with the Terrascope and MedLinks communities. 

Q: Do you have a bucket list? If so, share one or two of the items on it.

A: I’d like to be proficient in at least five languages in a conversational sense (though probably not at a working proficiency level). Currently, I’m fluent in English, and can speak Cantonese and Mandarin. I also have a 1,600-plus day Duolingo streak where I’m trying to learn the foundations of a few languages, including German, Korean, Japanese, and Russian. 

Another bucket list item I have is to try every martial art/combat sport there is, even if it’s just an introduction class. So far, I’ve practiced taekwondo for a few years, taken a few lessons in boxing/kickboxing, and dabbled in beginners’ classes for karate, Krav Maga, and Brazilian jiujitsu. I’ll probably try to take judo, aikido, and other classes this upcoming year! It would also be pretty epic to be a fourth dan black belt one day, though that may take a decade or two.

Q: If you had to teach a really in-depth class about one niche topic, what would you pick?

A: Personally, I think artificial organs are pretty awesome! I would probably talk about the fusion of engineering with our bodies, and organ enhancement. This might include adding functionalities and possible organ regeneration, so that those waiting for organ donations can be helped without being morally conflicted by waiting for another person’s downfall. I’ve previously done research in several BioEECS-related labs that I’d love to talk about as well. This includes the Traverso Lab at Pappalardo, briefly in the Edelman Lab at the [Institute for Medical Engineering and Science], the Langer Lab at the Koch Institute of Integrative Cancer Research, as well as in the MIT Media Lab with the Conformable Decoders and BioMechatronics group. I also contributed to a recently published paper related to gastrointestinal devices: OSIRIS.  

Q: If you suddenly won the lottery, what would you spend some of the money on? 

A: I would make sure my mom got most of the money. The first thing we’d do is probably go house shopping around the world and buy properties in great travel destinations — then go around and live in said properties. We would do this on rotation with our friends until we ran out of money, then put the properties up for rent and use the money to open a restaurant with my mom’s recipes as the menu. Then I’d get to eat her food forever.

Q: What do you believe is an underrated invention or technology?

A: I feel like many people wear glasses or put on contacts nowadays and don’t really think twice about it, glossing over how cool it is that we can fix bad sight and how critical sight is for our survival. If a zombie apocalypse happened and my glasses broke, it would be over for me. And don’t get me started about the invention of the indoor toilet and plumbing systems!

Q: Are you a re-reader or a re-watcher? If so, what are your comfort books, shows, or movies? 

A: I’m both a re-reader and a re-watcher! I have a lot of fun binging webtoons and dramas. I’m also a huge Marvel fan, although recently, it’s been a hit or miss. Action and romcoms are my kinda vibes, and occasionally I do watch some anime. If I’m bored I usually re-watch some [Marvel Cinematic Universe] movies, or Fairy Tail, or read some Isekai genre stories. 

Q: It’s time to get on the shuttle to the first Mars colony, and you can only bring one personal item. What are you going to bring along with you?

A: My first thought was my phone, but I feel like that may be too standard of an answer. If we were talking about the fantasy realm, I might ask Stephen Strange to borrow his sling ring to open more portals to link the Earth and Mars. As to why he wouldn’t have just come with us in the first place, I don’t know; maybe he’s too busy fighting aliens, or something?

Q: What are you looking forward to about life after graduation? What do you think you’ll miss about MIT? 

A: I won’t be missing dining hall food very much, that’s for sure — except for the amazing oatmeal from one of the Maseeh dining hall chefs, Sum! I am, however, excited to live the nine-to-five life for a few years and have my weekends back. I’ll miss my friends dearly, since everyone will be so spread out across the States and abroad. I’ll miss the nights we spent watching movies, playing games, cooking, eating, and yapping away. I’m excited to see everyone grow and take another step closer to their dreams. It will be fun visiting them and being able to explore the world at the same time! For more immediate plans, I’ll be going back to Apple this summer to intern again, and will finish my MEng with the 6A program at Cadence. Afterwards, I shall see where life takes me!

It is clear that humankind needs increasingly more resources, from computing power to steel and concrete, to meet the growing demands associated with data centers, infrastructure, and other mainstays of society. New, cost-effective approaches for producing the advanced materials key to that growth were the focus of a two-day workshop at MIT on March 11 and 12.

A theme throughout the event was the importance of collaboration between and within universities and industries. The goal is to “develop concepts that everybody can use together, instead of everybody doing something different and then trying to sort it out later at great cost,” said Lionel Kimerling, the Thomas Lord Professor of Materials Science and Engineering at MIT.

The workshop was produced by MIT’s Materials Research Laboratory (MRL), which has an industry collegium, and MIT’s Industrial Liaison Program. 

The program included an address by Javier Sanfelix, lead of the Advanced Materials Team for the European Union. Sanfelix gave an overview of the EU’s strategy to developing advanced materials, which he said are “key enablers of the green and digital transition for European industry.”

That strategy has already led to several initiatives. These include a material commons, or shared digital infrastructure for the design and development of advanced materials, and an advanced materials academy for educating new innovators and designers. Sanfelix also described an Advanced Materials Act for 2026 that aims to put in place a legislative framework that supports the entire innovation cycle.

Sanfelix was visiting MIT to learn more about how the Institute is approaching the future of advanced materials. “We see MIT as a leader worldwide in technology, especially on materials, and there is a lot to learn about [your] industry collaborations and technology transfer with industry,” he said.

Innovations in steel and concrete

The workshop began with talks about innovations involving two of the most common human-made materials in the world: steel and cement. We’ll need more of both but must reckon with the huge amounts of energy required to produce them and their impact on the environment due to greenhouse-gas emissions during that production.

One way to address our need for more steel is to reuse what we have, said C. Cem Tasan, the POSCO Associate Professor of Metallurgy in the Department of Materials Science and Engineering (DMSE) and director of the Materials Research Laboratory.

But most of the existing approaches to recycling scrap steel involve melting the metal. “And whenever you are dealing with molten metal, everything goes up, from energy use to carbon-dioxide emissions. Life is more difficult,” Tasan said.

The question he and his team asked is whether they could reuse scrap steel without melting it. Could they consolidate solid scraps, then roll them together using existing equipment to create new sheet metal? From the materials-science perspective, Tasan said, that shouldn’t work, for several reasons.

But it does. “We’ve demonstrated the potential in two papers and two patent applications already,” he said. Tasan noted that the approach focuses on high-quality manufacturing scrap. “This is not junkyard scrap,” he said.

Tasan went on to explain how and why the new process works from a materials-science perspective, then gave examples of how the recycled steel could be used. “My favorite example is the stainless-steel countertops in restaurants. Do you really need the mechanical performance of stainless steel there?” You could use the recycled steel instead.

Hessam Azarijafari addressed another common, indispensable material: concrete. This year marks the 16th anniversary of the MIT Concrete Sustainability Hub (CSHub), which began when a set of industry leaders and politicians reached out to MIT to learn more about the benefits and environmental impacts of concrete.

The hub’s work now centers around three main themes: working toward a carbon-neutral concrete industry; the development of a sustainable infrastructure, with a focus on pavement; and how to make our cities more resilient to natural hazards through investment in stronger, cooler construction.

Azarijafari, the deputy director of the CSHub, went on to give several examples of research results that have come out of the CSHub. These include many models to identify different pathways to decarbonize the cement and concrete sector. Other work involves pavements, which the general public thinks of as inert, Azarijafari said. “But we have [created] a state-of-the-art model that can assess interactions between pavement and vehicles.” It turns out that pavement surface characteristics and structural performance “can influence excess fuel consumption by inducing an additional rolling resistance.”

Azarijafari emphasized  the importance of working closely with policymakers and industry. That engagement is key “to sharing the lessons that we have learned so far.”

Toward a resource-efficient microchip industry

Consider the following: In 2020 the number of cell phones, GPS units, and other devices connected to the “cloud,” or large data centers, exceeded 50 billion. And data-center traffic in turn is scaling by 1,000 times every 10 years.

But all of that computation takes energy. And “all of it has to happen at a constant cost of energy, because the gross domestic product isn’t changing at that rate,” said Kimerling. The solution is to either produce much more energy, or make information technology much more energy-efficient. Several speakers at the workshop focused on the materials and components behind the latter.

Key to everything they discussed: adding photonics, or using light to carry information, to the well-established electronics behind today’s microchips. “The bottom line is that integrating photonics with electronics in the same package is the transistor for the 21st century. If we can’t figure out how to do that, then we’re not going to be able to scale forward,” said Kimerling, who is director of the MIT Microphotonics Center.

MIT has long been a leader in the integration of photonics with electronics. For example, Kimerling described the Integrated Photonics System Roadmap – International (IPSR-I), a global network of more than 400 industrial and R&D partners working together to define and create photonic integrated circuit technology. IPSR-I is led by the MIT Microphotonics Center and PhotonDelta. Kimerling began the organization in 1997.

Last year IPSR-I released its latest roadmap for photonics-electronics integration, “which  outlines a clear way forward and specifies an innovative learning curve for scaling performance and applications for the next 15 years,” Kimerling said.

Another major MIT program focused on the future of the microchip industry is FUTUR-IC, a new global alliance for sustainable microchip manufacturing. Begun last year, FUTUR-IC is funded by the National Science Foundation.

“Our goal is to build a resource-efficient microchip industry value chain,” said Anuradha Murthy Agarwal, a principal research scientist at the MRL and leader of FUTUR-IC. That includes all of the elements that go into manufacturing future microchips, including workforce education and techniques to mitigate potential environmental effects.

FUTUR-IC is also focused on electronic-photonic integration. “My mantra is to use electronics for computation, [and] shift to photonics for communication to bring this energy crisis in control,” Agarwal said.

But integrating electronic chips with photonic chips is not easy. To that end, Agarwal described some of the challenges involved. For example, currently it is difficult to connect the optical fibers carrying communications to a microchip. That’s because the alignment between the two must be almost perfect or the light will disperse. And the dimensions involved are minuscule. An optical fiber has a diameter of only millionths of a meter. As a result, today each connection must be actively tested with a laser to ensure that the light will come through.

That said, Agarwal went on to describe a new coupler between the fiber and chip that could solve the problem and allow robots to passively assemble the chips (no laser needed). The work, which was conducted by researchers including MIT graduate student Drew Wenninger, Agarwal, and Kimerling, has been patented, and is reported in two papers. A second recent breakthrough in this area involving a printed micro-reflector was described by Juejun “JJ” Hu, John F. Elliott Professor of Materials Science and Engineering.

FUTUR-IC is also leading educational efforts for training a future workforce, as well as techniques for detecting — and potentially destroying — the perfluroalkyls (PFAS, or “forever chemicals”) released during microchip manufacturing. FUTUR-IC educational efforts, including virtual reality and game-based learning, were described by Sajan Saini, education director for FUTUR-IC. PFAS detection and remediation were discussed by Aristide Gumyusenge, an assistant professor in DMSE, and Jesus Castro Esteban, a postdoc in the Department of Chemistry.

Other presenters at the workshop included Antoine Allanore, the Heather N. Lechtman Professor of Materials Science and Engineering; Katrin Daehn, a postdoc in the Allanore lab; Xuanhe Zhao, the Uncas (1923) and Helen Whitaker Professor in the Department of Mechanical Engineering; Richard Otte, CEO of Promex; and Carl Thompson, the Stavros V. Salapatas Professor in Materials Science and Engineering.

As technology rapidly propels society forward, MIT is rethinking how it prepares students to face the world and its greatest challenges. Generations of educators have shared knowledge at MIT by connecting lessons to practical applications, but what does the Institute’s motto “mens et manus” (“mind and hand”), referring to hands-on learning, look like in the future?

This was the guiding question of the annual Festival of Learning, co-hosted by MIT Open Learning and the Office of the Vice Chancellor. MIT faculty, instructors, students, and staff engaged in meaningful discussions about teaching and learning as the Institute critically revisits its undergraduate academic program.

“Because the world is changing, we owe it to our students to reflect these realities in our academic experiences,” said Daniel E. Hastings, Cecil and Ida Green Education Professor of Aeronautics and Astronautics and then-interim vice chancellor. “It’s in our DNA to try new things at MIT.”

Fostering a greater sense of purpose

MIT emphasizes hands-on learning much like many engineering schools. What deeply concerned panelists like Susan Silbey, the Leon and Anne Goldberg Professor of Humanities, Sociology, and Anthropology, is that students are not engaging in enough intellectual thinking via significant reading, textual interpretation, or involvement with uncertain questions.

Christopher Capozzola, senior associate dean for open learning, echoed this, saying, “We have designed a world in which [students] feel enormous pressure to maximize their career outcomes at the end” of their undergraduate education.

Students move in systems of explicit incentives, he said, such as grades and the General Institute Requirements, but also respond to unwritten incentives, like extracurriculars, internships, and prestige. “That’s our fault, not theirs,” Capozzola said, and identified this as an opportunity to improve the MIT curriculum.

How can educators encourage students to connect more with course material, instead of treating it as a means to an end? Adam Martin, professor of biology, always asks his students to challenge the status quo by incorporating test questions with data arguing against the models from the textbook.

“I want them to think,” Martin said. “I want them to challenge what we think is the frontier of the field.”

Considering context

One of the most significant topics of discussion was the importance of context in education. For example, class 7.102 (Introduction to Molecular Biology Techniques) uses story-based problem-solving to show students how the curriculum fits into real-world contexts.

The fictional premise driving 7.102 is that a child fell into the Charles River and caught an antibiotic-resistant bacterial infection. To save the child, students must characterize the bacteria and identify phages that could kill it.

“It really shows the students not only basic techniques, but what it’s like to be in a team and in a discovery situation,” said Martin.

This hands-on approach — collecting water, isolating the phages within, and comparing to more reliable sources — unlocks students’ imaginations, Martin said. In an environment intentionally designed to give students room to fail, the narrative incentivizes students to persist with repeated experimentation.

But Silbey, who is also a professor of behavioral and policy sciences at MIT Sloan School of Management, has noticed the reluctance of students to engage with nontechnical contexts. Students, she concluded, “have minimal understanding of how the action of any individual becomes part of something larger, durable, consequential through invisible but powerful mechanisms of aggregation.”

Educators agreed that contextual understanding was equally important to a STEM curriculum as technical instruction. “Teaching and thinking at that interface between technology and society is really crucial for making technologists feel responsible for the things that they create and the things that they use,” added Capozzola.

Amitava Mitra, founding executive director of MIT New Engineering Education Transformation (NEET), highlighted an example where students developed an effective technical solution to decarbonize homes in Ulaanbaatar, Mongolia. Or so they thought.

“Once we saw what was on the ground and understood the context — the social model, the social processes — we realized we had no clue,” the students told Mitra.

One way MIT is trying to bridge these gaps is through the Social and Ethical Responsibilities of Computing program. This curriculum integrates ethical considerations alongside computing courses to help students envision the social and moral consequences of their actions.

In one technical machinery lecture, Silbey’s students had trouble envisioning the negative impacts of autonomous vehicles. But after she shared the history of the regulation of dangerous products, she said many students became more open to examining potential ripple effects.

Creating interdisciplinary opportunities

The panelists viewed interdisciplinary education as critical preparation for the complexities of the real world.

“Whether it’s tackling climate change, creating sustainable infrastructure, creating cutting-edge technologies in life sciences or robotics, we need our engineers, social scientists, and scientists to work in teams cutting across disciplines to create solutions today,” said Mitra.

To expand opportunities for undergraduates to collaborate across academic departments and other campus units, NEET was launched in 2017. NEET is a project-based experiential learning curriculum that requires technical and social expertise. One student group, for example, is designing, building, and installing a solar-powered charging station at MIT Open Space. To introduce a project like this into MIT’s infrastructure, students must coordinate with a variety of Institute offices — such as Campus Planning, Engineering & Energy Management, and Insurance — and city groups, like the Cambridge Fire Department.

“It's an eye-opener for them,” said Mitra.

Capozzola noted how “para-curricular” activities like NEET, MIT Undergraduate Research Opportunities Program, MISTI, D-Lab, and others prove that effective hands-on education doesn’t have to be a formal credit-bearing program.

“Students put in enormous amounts of time and effort for things that shape them, that speak to their passion and this deep engagement,” Capozzola said. “This is a special area where I think MIT particularly excels.”

Moving forward together

In a panel featuring both MIT instructors and students, educators recognized that designing an effective curriculum requires balancing content across subjects or core topics while organizing materials on Canvas — MIT’s learning management system — in a way that’s intuitive for students. Instructors collaborated directly with students and staff via MIT’s Canvas Innovation Fund to make these improvements.

“There are things that the novice students see in what I’m teaching that I don’t see,” said Sean Robinson, lecturer in physics and associate director of the Helena Foundation Junior Laboratory. “Our class is aimed at taking people who think of themselves as physics students and getting them to think of themselves as physicists. I want junior colleagues.”

The biggest takeaway from student panelists was the importance of minimizing logistical struggles by structuring Canvas to guide students toward learning objectives. Cory Romanov ’24, technical instructor of physics, and McKenzie Dinesen, a senior in aerospace engineering and Russian and Eurasian studies, emphasized that explaining learning goals and organizing course content with clear deadlines were simple improvements that went a long way to enhance the student experience.

Emphasizing the benefit of feedback like this, Capozzola said, “It’s important to give people at MIT — students, staff, and others who are often closed out of conversations — a more democratic voice so that we can be a model for the university that we want to be in 25 years.”

As MIT continues to enhance its educational approach, the insights from the Festival of Learning highlight a crucial evolution in how students engage with knowledge. From rethinking course structures to integrating interdisciplinary and experiential learning, the panelists underscored the need for a curriculum that balances technical expertise with a deep understanding of social and ethical contexts.

“It’s important to equip students on the ‘mens’ side with the kinds of civic knowledge that they need to go out into the world,” said Capozzola, “but also the ‘manus,’ to be able to do the everyday work of getting your hands dirty and building democratic institutions.” 

MIT political scientist Adam Berinsky has been named to the 2025 class of Andrew Carnegie Fellows, a high-profile honor for scholars pursuing research in the social sciences and humanities.

The fellowship is provided by The Carnegie Corp. of New York. Berinsky, the Mitsui Professor of Political Science, and 25 other fellows were selected from more than 300 applicants. They will each receive stipends of $200,000 for research that seeks to understand how and why our society has become so polarized, and how we can strengthen the forces of cohesion to fortify our democracy.

“Through these fellowships Carnegie is harnessing the unrivaled brainpower of our universities to help us to understand how our society has become so polarized,” says Carnegie President Louise Richardson. “Our future grant-making will be informed by what we learn from these scholars as we seek to mitigate the pernicious effects of political polarization.”

Berinsky said he is “incredibly honored to be named an Andrew Carnegie Fellow for the coming year. This fellowship will allow me to work on critical issues in the current political moment.”

During his year as a Carnegie Fellow, Berinsky will be working on a project, “Fostering an Accurate Information Ecosystem to Mitigate Polarization in the United States.”

“For a functioning democracy, it is essential that citizens share a baseline of common facts,” says Berinsky. “However, in today’s politically polarized climate, ‘alternative facts,’ and other forms of misinformation — from political rumors to conspiracy theories — distort how people see reality, and damage our social fabric.”

“I’ve spent the last 15 years investigating why individuals accept misinformation and how to counter misperceptions. But there is still a lot of work to be done. My project aims to tackle the serious problem of misinformation in the United States by bringing together existing approaches in new, more powerful combinations. I’m hoping that the whole can be more than the sum of its parts.”

Berinsky has been a member of the MIT faculty since 2003. He is the author of “Political Rumors: Why We Accept Misinformation and How to Fight It” (Princeton University Press, 2023).

Other MIT faculty who have received the Carnegie Fellowship in recent years include economists David Autor and Daron Acemoglu and political scientists Fotini Christia, Taylor Fravel, Richard Nielsen, and Charles Stewart.

Discord is testing the feature:

“We’re currently running tests in select regions to age-gate access to certain spaces or user settings,” a spokesperson for Discord said in a statement. “The information shared to power the age verification method is only used for the one-time age verification process and is not stored by Discord or our vendor. For Face Scan, the solution our vendor uses operates on-device, which means there is no collection of any biometric information when you scan your face. For ID verification, the scan of your ID is deleted upon verification.”...

Cleft lip and cleft palate are among the most common birth defects, occurring in about one in 1,050 births in the United States. These defects, which appear when the tissues that form the lip or the roof of the mouth do not join completely, are believed to be caused by a mix of genetic and environmental factors.

In a new study, MIT biologists have discovered how a genetic variant often found in people with these facial malformations leads to the development of cleft lip and cleft palate.

Their findings suggest that the variant diminishes cells’ supply of transfer RNA, a molecule that is critical for assembling proteins. When this happens, embryonic face cells are unable to fuse to form the lip and roof of the mouth.

“Until now, no one had made the connection that we made. This particular gene was known to be part of the complex involved in the splicing of transfer RNA, but it wasn’t clear that it played such a crucial role for this process and for facial development. Without the gene, known as DDX1, certain transfer RNA can no longer bring amino acids to the ribosome to make new proteins. If the cells can’t process these tRNAs properly, then the ribosomes can’t make protein anymore,” says Michaela Bartusel, an MIT research scientist and the lead author of the study.

Eliezer Calo, an associate professor of biology at MIT, is the senior author of the paper, which appears today in the American Journal of Human Genetics.

Genetic variants

Cleft lip and cleft palate, also known as orofacial clefts, can be caused by genetic mutations, but in many cases, there is no known genetic cause.

“The mechanism for the development of these orofacial clefts is unclear, mostly because they are known to be impacted by both genetic and environmental factors,” Calo says. “Trying to pinpoint what might be affected has been very challenging in this context.”

To discover genetic factors that influence a particular disease, scientists often perform genome-wide association studies (GWAS), which can reveal variants that are found more often in people who have a particular disease than in people who don’t.

For orofacial clefts, some of the genetic variants that have regularly turned up in GWAS appeared to be in a region of DNA that doesn’t code for proteins. In this study, the MIT team set out to figure out how variants in this region might influence the development of facial malformations.

Their studies revealed that these variants are located in an enhancer region called e2p24.2. Enhancers are segments of DNA that interact with protein-coding genes, helping to activate them by binding to transcription factors that turn on gene expression.

The researchers found that this region is in close proximity to three genes, suggesting that it may control the expression of those genes. One of those genes had already been ruled out as contributing to facial malformations, and another had already been shown to have a connection. In this study, the researchers focused on the third gene, which is known as DDX1.

DDX1, it turned out, is necessary for splicing transfer RNA (tRNA) molecules, which play a critical role in protein synthesis. Each transfer RNA molecule transports a specific amino acid to the ribosome — a cell structure that strings amino acids together to form proteins, based on the instructions carried by messenger RNA.

While there are about 400 different tRNAs found in the human genome, only a fraction of those tRNAs require splicing, and those are the tRNAs most affected by the loss of DDX1. These tRNAs transport four different amino acids, and the researchers hypothesize that these four amino acids may be particularly abundant in proteins that embryonic cells that form the face need to develop properly.

When the ribosomes need one of those four amino acids, but none of them are available, the ribosome can stall, and the protein doesn’t get made.

The researchers are now exploring which proteins might be most affected by the loss of those amino acids. They also plan to investigate what happens inside cells when the ribosomes stall, in hopes of identifying a stress signal that could potentially be blocked and help cells survive.

Malfunctioning tRNA

While this is the first study to link tRNA to craniofacial malformations, previous studies have shown that mutations that impair ribosome formation can also lead to similar defects. Studies have also shown that disruptions of tRNA synthesis — caused by mutations in the enzymes that attach amino acids to tRNA, or in proteins involved in an earlier step in tRNA splicing — can lead to neurodevelopmental disorders.

“Defects in other components of the tRNA pathway have been shown to be associated with neurodevelopmental disease,” Calo says. “One interesting parallel between these two is that the cells that form the face are coming from the same place as the cells that form the neurons, so it seems that these particular cells are very susceptible to tRNA defects.”

The researchers now hope to explore whether environmental factors linked to orofacial birth defects also influence tRNA function. Some of their preliminary work has found that oxidative stress — a buildup of harmful free radicals — can lead to fragmentation of tRNA molecules. Oxidative stress can occur in embryonic cells upon exposure to ethanol, as in fetal alcohol syndrome, or if the mother develops gestational diabetes.

“I think it is worth looking for mutations that might be causing this on the genetic side of things, but then also in the future, we would expand this into which environmental factors have the same effects on tRNA function, and then see which precautions might be able to prevent any effects on tRNAs,” Bartusel says.

The research was funded by the National Science Foundation Graduate Research Program, the National Cancer Institute, the National Institute of General Medical Sciences, and the Pew Charitable Trusts.

The administration’s move Wednesday to block work on a wind project off New York state sent chills through the industry.

$20 billion have been frozen at Citibank for two months while the Trump administration tried to rake the money back into the U.S. Treasury.

The filings seek to force the administration to divulge details that include its push to topple a pillar of U.S. climate action, the 2009 endangerment finding.