Transistors, the building blocks of modern electronics, are typically made of silicon. Because it’s a semiconductor, this material can control the flow of electricity in a circuit. But silicon has fundamental physical limits that restrict how compact and energy-efficient a transistor can be.

MIT researchers have now replaced silicon with a magnetic semiconductor, creating a magnetic transistor that could enable smaller, faster, and more energy-efficient circuits. The material’s magnetism strongly influences its electronic behavior, leading to more efficient control of the flow of electricity. 

The team used a novel magnetic material and an optimization process that reduces the material’s defects, which boosts the transistor’s performance.

The material’s unique magnetic properties also allow for transistors with built-in memory, which would simplify circuit design and unlock new applications for high-performance electronics.

“People have known about magnets for thousands of years, but there are very limited ways to incorporate magnetism into electronics. We have shown a new way to efficiently utilize magnetism that opens up a lot of possibilities for future applications and research,” says Chung-Tao Chou, an MIT graduate student in the departments of Electrical Engineering and Computer Science (EECS) and Physics, and co-lead author of a paper on this advance.

Chou is joined on the paper by co-lead author Eugene Park, a graduate student in the Department of Materials Science and Engineering (DMSE); Julian Klein, a DMSE research scientist; Josep Ingla-Aynes, a postdoc in the MIT Plasma Science and Fusion Center; Jagadeesh S. Moodera, a senior research scientist in the Department of Physics; and senior authors Frances Ross, TDK Professor in DMSE; and Luqiao Liu, an associate professor in EECS, and a member of the Research Laboratory of Electronics; as well as others at the University of Chemistry and Technology in Prague. The paper appears today in Physical Review Letters.

Overcoming the limits

In an electronic device, silicon semiconductor transistors act like tiny light switches that turn a circuit on and off, or amplify weak signals in a communication system. They do this using a small input voltage.

But a fundamental physical limit of silicon semiconductors prevents a transistor from operating below a certain voltage, which hinders its energy efficiency.

To make more efficient electronics, researchers have spent decades working toward magnetic transistors that utilize electron spin to control the flow of electricity. Electron spin is a fundamental property that enables electrons to behave like tiny magnets.

So far, scientists have mostly been limited to using certain magnetic materials. These lack the favorable electronic properties of semiconductors, constraining device performance.

“In this work, we combine magnetism and semiconductor physics to realize useful spintronic devices,” Liu says.

The researchers replace the silicon in the surface layer of a transistor with chromium sulfur bromide, a two-dimensional material that acts as a magnetic semiconductor.

Due to the material’s structure, researchers can switch between two magnetic states very cleanly. This makes it ideal for use in a transistor that smoothly switches between “on” and “off.”

“One of the biggest challenges we faced was finding the right material. We tried many other materials that didn’t work,” Chou says.

They discovered that changing these magnetic states modifies the material’s electronic properties, enabling low-energy operation. And unlike many other 2D materials, chromium sulfur bromide remains stable in air.

To make a transistor, the researchers pattern electrodes onto a silicon substrate, then carefully align and transfer the 2D material on top. They use tape to pick up a tiny piece of material, only a few tens of nanometers thick, and place it onto the substrate.

“A lot of researchers will use solvents or glue to do the transfer, but transistors require a very clean surface. We eliminate all those risks by simplifying this step,” Chou says.

Leveraging magnetism

This lack of contamination enables their device to outperform existing magnetic transistors. Most others can only create a weak magnetic effect, changing the flow of current by a few percent or less. Their new transistor can switch or amplify the electric current by a factor of 10.

They use an external magnetic field to change the magnetic state of the material, switching the transistor using significantly less energy than would usually be required.

The material also allows them to control the magnetic states with electric current. This is important because engineers cannot apply magnetic fields to individual transistors in an electronic device. They need to control each one electrically.

The material’s magnetic properties could also enable transistors with built-in memory, simplifying the design of logic or memory circuits.

A typical memory device has a magnetic cell to store information and a transistor to read it out. Their method can combine both into one magnetic transistor.

“Now, not only are transistors turning on and off, they are also remembering information. And because we can switch the transistor with greater magnitude, the signal is much stronger so we can read out the information faster, and in a much more reliable way,” Liu says.

Building on this demonstration, the researchers plan to further study the use of electrical current to control the device. They are also working to make their method scalable so they can fabricate arrays of transistors.

This research was supported, in part, by the Semiconductor Research Corporation, the U.S. Defense Advanced Research Projects Agency (DARPA), the U.S. National Science Foundation (NSF), the U.S. Department of Energy, the U.S. Army Research Office, and the Czech Ministry of Education, Youth, and Sports. The work was partially carried out at the MIT.nano facilities.

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.”

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.

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.

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.

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.” 

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.

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.”

“The minute you think, ‘I’ve done everything I can possibly do for Lincoln Lab,’ next thing you know, you’re belly crawling through a mock rubble pile,” says Niki Fandel. 

Through hundreds of photo shoots each year, the MT Lincoln Laboratory photographer captures technical innovations — from functional fibers to advanced radar systems ­— and the people who develop them for national security. Her work brings her to every corner of the laboratory’s main campus in Lexington, Massachusetts, and to field sites across the country.  

Video by Tim Briggs/MIT Lincoln Laboratory | 5 minutes, 56 seconds

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.

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.

• Amrita Lamba: Postdoc, Saxe lab
  Drawing on her expertise in social neuroscience and game theory, Lamba will examine whether a two-player economic game could be used to distinguish generalized anxiety from social anxiety — a critical step toward personalized treatments for disorder subtypes. 
• Hoonwon Lee: Postdoc, Jasanoff lab
  As a molecular biologist who studies memory formation in the brain, Lee examines how fear memories develop and persist across brain networks, connecting what’s happening at the cellular level to larger brain-wide patterns. His findings may lead to new targets for post-traumatic stress disorder.
• Karen Pang: Graduate student, Anikeeva lab
  Pang studies how the gut communicates with the brain to influence anxiety and depression, developing new tools to understand this connection and ultimately create treatments that address both digestive and mental health problems together.
• Smriti Saini: Graduate student, Gabrieli lab
  Saini is using brain imaging and computational techniques to identify which people with severe social anxiety will benefit from cognitive behavioral therapy, so doctors can personalize treatment decisions rather than relying only on symptoms. 
• Linghua Zhang: Postdoc, Wang lab
  Exercise is known to boost mood, but how it reshapes the mind is unclear. Zhang will study the circuit-level mechanisms behind the brain benefits of physical activity.

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. 

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. 

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.

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."

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.

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). 

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. 

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 of atmospheric science 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, Kerry notes. For example, a company called First Street uses Kerry’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 Moshe Ben-Akiva, 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 a slow — “like steering a supertanker,” he says — but progress will come.

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.

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.