Fikile R. Brushett, a Ralph Landau Professor of Chemical Engineering Practice, was named director of MIT’s David H. Koch School of Chemical Engineering Practice, effective July 1. In this role, Brushett will lead one of MIT’s most innovative and distinctive educational programs.

Brushett joined the chemical engineering faculty in 2012 and has been a deeply engaged member of the department. An internationally recognized leader in the field of energy storage, his research advances the science and engineering of electrochemical technologies for a sustainable energy economy. He is particularly interested in the fundamental processes that define the performance, cost, and lifetime of present-day and next-generation electrochemical systems. In addition to his research, Brushett has served as a first-year undergraduate advisor, as a member of the department’s graduate admissions committee, and on MIT’s Committee on the Undergraduate Program.

“Fik’s scholarly excellence and broad service position him perfectly to take on this new challenge,” says Kristala L. J. Prather, the Arthur D. Little Professor and head of the Department of Chemical Engineering (ChemE). “His role as practice school director reflects not only his technical expertise, but his deep commitment to preparing students for meaningful, impactful careers. I’m confident he will lead the practice school with the same spirit of excellence and innovation that has defined the program for generations.”

Brushett succeeds T. Alan Hatton, a Ralph Landau Professor of Chemical Engineering Practice Post-Tenure, who directed the practice school for 36 years. For many, Hatton’s name is synonymous with the program. When he became director in 1989, only a handful of major chemical companies hosted stations.

“I realized that focusing on one industry segment was not sustainable and did not reflect the breadth of a chemical engineering education,” Hatton recalls. “So I worked to modernize the experience for students and have it reflect the many ways chemical engineers practice in the modern world.”

Under Hatton’s leadership, the practice school expanded globally and across industries, providing students with opportunities to work on diverse technologies in a wide range of locations. He pioneered the model of recruiting new companies each year, allowing many more firms to participate while also spreading costs across a broader sponsor base. He also introduced an intensive, hands-on project management course at MIT during Independent Activities Period, which has become a valuable complement to students’ station work and future careers.

Value for students and industry

The practice school benefits not only students, but also the companies that host them. By embedding teams directly into manufacturing plants and R&D centers, businesses gain fresh perspectives on critical technical challenges, coupled with the analytical rigor of MIT-trained problem-solvers. Many sponsors report that projects completed by practice school students have yielded measurable cost savings, process improvements, and even new opportunities for product innovation.

For manufacturing industries, where efficiency, safety, and sustainability are paramount, the program provides actionable insights that help companies strengthen competitiveness and accelerate growth. The model creates a unique partnership: students gain true real-world training, while companies benefit from MIT expertise and the creativity of the next generation of chemical engineers.

A century of hands-on learning

Founded in 1916 by MIT chemical engineering alumnus Arthur D. Little and Professor William Walker, with funding from George Eastman of Eastman Kodak, the practice school was designed to add a practical dimension to chemical engineering education. The first five sites — all in the Northeast — focused on traditional chemical industries working on dyes, abrasives, solvents, and fuels.

Today, the program remains unique in higher education. Students consult with companies worldwide across fields ranging from food and pharmaceuticals to energy and finance, tackling some of industry’s toughest challenges. More than a hundred years after its founding, the practice school continues to embody MIT’s commitment to hands-on, problem-driven learning that transforms both students and the industries they serve.

The practice school experience is part of ChemE’s MSCEP and PhD/ScDCEP programs. After coursework for each program is completed, a student attends practice school stations at host company sites. A group of six to 10 students spends two months each at two stations; each station experience includes teams of two or three students working on a month-long project, where they will prepare formal talks, scope of work, and a final report for the host company. Recent stations include Evonik in Marl, Germany; AstraZeneca in Gaithersburg, Maryland; EGA in Dubai, UAE; AspenTech in Bedford, Massachusetts; and Shell Technology Center and Dimensional Energy in Houston, Texas.

MIT researchers have developed a technique that enables real-time, 3D monitoring of corrosion, cracking, and other material failure processes inside a nuclear reactor environment.

This could allow engineers and scientists to design safer nuclear reactors that also deliver higher performance for applications like electricity generation and naval vessel propulsion.

During their experiments, the researchers utilized extremely powerful X-rays to mimic the behavior of neutrons interacting with a material inside a nuclear reactor.

They found that adding a buffer layer of silicon dioxide between the material and its substrate, and keeping the material under the X-ray beam for a longer period of time, improves the stability of the sample. This allows for real-time monitoring of material failure processes.

By reconstructing 3D image data on the structure of a material as it fails, researchers could design more resilient materials that can better withstand the stress caused by irradiation inside a nuclear reactor.

“If we can improve materials for a nuclear reactor, it means we can extend the life of that reactor. It also means the materials will take longer to fail, so we can get more use out of a nuclear reactor than we do now. The technique we’ve demonstrated here allows to push the boundary in understanding how materials fail in real-time,” says Ericmoore Jossou, who has shared appointments in the Department of Nuclear Science and Engineering (NSE), where he is the John Clark Hardwick Professor, and the Department of Electrical Engineering and Computer Science (EECS), and the MIT Schwarzman College of Computing.

Jossou, senior author of a study on this technique, is joined on the paper by lead author David Simonne, an NSE postdoc; Riley Hultquist, a graduate student in NSE; Jiangtao Zhao, of the European Synchrotron; and Andrea Resta, of Synchrotron SOLEIL. The research was published Tuesday by the journal Scripta Materiala.

“Only with this technique can we measure strain with a nanoscale resolution during corrosion processes. Our goal is to bring such novel ideas to the nuclear science community while using synchrotrons both as an X-ray probe and radiation source,” adds Simonne.

Real-time imaging

Studying real-time failure of materials used in advanced nuclear reactors has long been a goal of Jossou’s research group.

Usually, researchers can only learn about such material failures after the fact, by removing the material from its environment and imaging it with a high-resolution instrument.

“We are interested in watching the process as it happens. If we can do that, we can follow the material from beginning to end and see when and how it fails. That helps us understand a material much better,” he says.

They simulate the process by firing an extremely focused X-ray beam at a sample to mimic the environment inside a nuclear reactor. The researchers must use a special type of high-intensity X-ray, which is only found in a handful of experimental facilities worldwide.

For these experiments they studied nickel, a material incorporated into alloys that are commonly used in advanced nuclear reactors. But before they could start the X-ray equipment, they had to prepare a sample.

To do this, the researchers used a process called solid state dewetting, which involves putting a thin film of the material onto a substrate and heating it to an extremely high temperature in a furnace until it transforms into single crystals.

“We thought making the samples was going to be a walk in the park, but it wasn’t,” Jossou says.

As the nickel heated up, it interacted with the silicon substrate and formed a new chemical compound, essentially derailing the entire experiment. After much trial-and-error, the researchers found that adding a thin layer of silicon dioxide between the nickel and substrate prevented this reaction.

But when crystals formed on top of the buffer layer, they were highly strained. This means the individual atoms had moved slightly to new positions, causing distortions in the crystal structure.

Phase retrieval algorithms can typically recover the 3D size and shape of a crystal in real-time, but if there is too much strain in the material, the algorithms will fail.

However, the team was surprised to find that keeping the X-ray beam trained on the sample for a longer period of time caused the strain to slowly relax, due to the silicon buffer layer. After a few extra minutes of X-rays, the sample was stable enough that they could utilize phase retrieval algorithms to accurately recover the 3D shape and size of the crystal.

“No one had been able to do that before. Now that we can make this crystal, we can image electrochemical processes like corrosion in real time, watching the crystal fail in 3D under conditions that are very similar to inside a nuclear reactor. This has far-reaching impacts,” he says.

They experimented with a different substrate, such as niobium doped strontium titanate, and found that only a silicon dioxide buffered silicon wafer created this unique effect.

An unexpected result

As they fine-tuned the experiment, the researchers discovered something else.

They could also use the X-ray beam to precisely control the amount of strain in the material, which could have implications for the development of microelectronics.

In the microelectronics community, engineers often introduce strain to deform a material’s crystal structure in a way that boosts its electrical or optical properties.

“With our technique, engineers can use X-rays to tune the strain in microelectronics while they are manufacturing them. While this was not our goal with these experiments, it is like getting two results for the price of one,” he adds.

In the future, the researchers want to apply this technique to more complex materials like steel and other metal alloys used in nuclear reactors and aerospace applications. They also want to see how changing the thickness of the silicon dioxide buffer layer impacts their ability to control the strain in a crystal sample.

“This discovery is significant for two reasons. First, it provides fundamental insight into how nanoscale materials respond to radiation — a question of growing importance for energy technologies, microelectronics, and quantum materials. Second, it highlights the critical role of the substrate in strain relaxation, showing that the supporting surface can determine whether particles retain or release strain when exposed to focused X-ray beams,” says Edwin Fohtung, an associate professor at the Rensselaer Polytechnic Institute, who was not involved with this work.

This work was funded, in part, by the MIT Faculty Startup Fund and the U.S. Department of Energy. The sample preparation was carried out, in part, at the MIT.nano facilities.

MIT Professor Emeritus Rainer Weiss ’55, PhD ’62, a renowned experimental physicist and Nobel laureate whose groundbreaking work confirmed a longstanding prediction about the nature of the universe, passed away on Aug. 25. He was 92.

Weiss conceived of the Laser Interferometer Gravitational-Wave Observatory (LIGO) for detecting ripples in space-time known as gravitational waves, and was later a leader of the team that built LIGO and achieved the first-ever detection of gravitational waves. He shared the Nobel Prize in Physics for this work in 2017. Together with international collaborators, he and his colleagues at LIGO would go on to detect many more of these cosmic reverberations, opening up a new way for scientists to view the universe.

During his remarkable career, Weiss also developed a more precise atomic clock and figured out how to measure the spectrum of the cosmic microwave background via a weather balloon. He later co-founded and advanced the NASA Cosmic Background Explorer project, whose measurements helped support the Big Bang theory describing the expansion of the universe.

“Rai leaves an indelible mark on science and a gaping hole in our lives,” says Nergis Mavalvala PhD ’97, dean of the MIT School of Science and the Curtis and Kathleen Marble Professor of Astrophysics. As a doctoral student with Weiss in the 1990s, Mavalvala worked with him to build an early prototype of a gravitational-wave detector as part of her PhD thesis. “He will be so missed but has also gifted us a singular legacy. Every gravitational wave event we observe will remind us of him, and we will smile. I am indeed heartbroken, but also so grateful for having him in my life, and for the incredible gifts he has given us — of passion for science and discovery, but most of all to always put people first.” she says.

A member of the MIT physics faculty since 1964, Weiss was known as a committed mentor and teacher, as well as a dedicated researcher. 

“Rai’s ingenuity and insight as an experimentalist and a physicist were legendary,” says Deepto Chakrabarty, the William A. M. Burden Professor in Astrophysics and head of the Department of Physics. “His no-nonsense style and gruff manner belied a very close, supportive and collaborative relationship with his students, postdocs, and other mentees. Rai was a thoroughly MIT product.”

“Rai held a singular position in science: He was the creator of two fields — measurements of the cosmic microwave background and of gravitational waves. His students have gone on to lead both fields and carried Rai’s rigor and decency to both. He not only created a huge part of important science, he also populated them with people of the highest caliber and integrity,” says Peter Fisher, the Thomas A. Frank Professor of Physics and former head of the physics department.

Enabling a new era in astrophysics

LIGO is a system of two identical detectors located 1,865 miles apart. By sending finely tuned lasers back and forth through the detectors, scientists can detect perturbations caused by gravitational waves, whose existence was proposed by Albert Einstein. These discoveries illuminate ancient collisions and other events in the early universe, and have confirmed Einstein’s theory of general relativity. Today, the LIGO Scientific Collaboration involves hundreds of scientists at MIT, Caltech, and other universities, and with the Virgo and KAGRA observatories in Italy and Japan makes up the global LVK Collaboration — but five decades ago, the instrument concept was an MIT class exercise conceived by Weiss.

As he told MIT News in 2017, in generating the initial idea, Weiss wondered: “What’s the simplest thing I can think of to show these students that you could detect the influence of a gravitational wave?”

To realize the audacious design, Weiss teamed up in 1976 with physicist Kip Thorne, who, based in part on conversations with Weiss, soon seeded the creation of a gravitational wave experiment group at Caltech. The two formed a collaboration between MIT and Caltech, and in 1979, the late Scottish physicist Ronald Drever, then of the University of Glasgow, joined the effort at Caltech. The three scientists — who became the co-founders of LIGO — worked to refine the dimensions and scientific requirements for an instrument sensitive enough to detect a gravitational wave. Barry Barish later joined the team at Caltech, helping to secure funding and bring the detectors to completion.

After receiving support from the National Science Foundation, LIGO broke ground in the mid-1990s, constructing interferometric detectors in Hanford, Washington, and in Livingston, Louisiana. 

Years later, when he shared the Nobel Prize with Thorne and Barish for his work on LIGO, Weiss noted that hundreds of colleagues had helped to push forward the search for gravitational waves.

“The discovery has been the work of a large number of people, many of whom played crucial roles,” Weiss said at an MIT press conference. “I view receiving this [award] as sort of a symbol of the various other people who have worked on this.”

He continued: “This prize and others that are given to scientists is an affirmation by our society of [the importance of] gaining information about the world around us from reasoned understanding of evidence.”

“While I have always been amazed and guided by Rai’s ingenuity, integrity, and humility, I was most impressed by his breadth of vision and ability to move between worlds,” says Matthew Evans, the MathWorks Professor of Physics. “He could seamlessly shift from the smallest technical detail of an instrument to the global vision for a future observatory. In the last few years, as the idea for a next-generation gravitational-wave observatory grew, Rai would often be at my door, sharing ideas for how to move the project forward on all levels. These discussions ranged from quantum mechanics to global politics, and Rai’s insights and efforts have set the stage for the future.”

A lifelong fascination with hard problems

Weiss was born in 1932 in Berlin. The young family fled Nazi Germany to Prague and then emigrated to New York City, where Weiss grew up with a love for classical music and electronics, earning money by fixing radios.

He enrolled at MIT, then dropped out of school in his junior year, only to return shortly after, taking a job as a technician in the former Building 20. There, Weiss met physicist Jerrold Zacharias, who encouraged him in finishing his undergraduate degree in 1955 and his PhD in 1962.

Weiss spent some time at Princeton University as a postdoc in the legendary group led by Robert Dicke, where he developed experiments to test gravity. He returned to MIT as an assistant professor in 1964, starting a new research group in the Research Laboratory of Electronics dedicated to research in cosmology and gravitation.

Weiss received numerous awards and honors in addition to the Nobel Prize, including the Medaille de l’ADION, the 2006 Gruber Prize in Cosmology, and the 2007 Einstein Prize of the American Physical Society. He was a fellow of the American Association for the Advancement of Science, the American Academy of Arts and Sciences, and the American Physical Society, as well as a member of the National Academy of Sciences. In 2016, Weiss received a Special Breakthrough Prize in Fundamental Physics, the Gruber Prize in Cosmology, the Shaw Prize in Astronomy, and the Kavli Prize in Astrophysics, all shared with Drever and Thorne. He also shared the Princess of Asturias Award for Technical and Scientific Research with Thorne, Barry Barish of Caltech, and the LIGO Scientific Collaboration.

Weiss is survived by his wife, Rebecca; his daughter, Sarah, and her husband, Tony; his son, Benjamin, and his wife, Carla; and a grandson, Sam, and his wife, Constance. Details about a memorial are forthcoming.

This article may be updated.

Environmental scientists are increasingly using enormous artificial intelligence models to make predictions about changes in weather and climate, but a new study by MIT researchers shows that bigger models are not always better.

The team demonstrates that, in certain climate scenarios, much simpler, physics-based models can generate more accurate predictions than state-of-the-art deep-learning models.

Their analysis also reveals that a benchmarking technique commonly used to evaluate machine-learning techniques for climate predictions can be distorted by natural variations in the data, like fluctuations in weather patterns. This could lead someone to believe a deep-learning model makes more accurate predictions when that is not the case.

The researchers developed a more robust way of evaluating these techniques, which shows that, while simple models are more accurate when estimating regional surface temperatures, deep-learning approaches can be the best choice for estimating local rainfall.

They used these results to enhance a simulation tool known as a climate emulator, which can rapidly simulate the effect of human activities onto a future climate.

The researchers see their work as a “cautionary tale” about the risk of deploying large AI models for climate science. While deep-learning models have shown incredible success in domains such as natural language, climate science contains a proven set of physical laws and approximations, and the challenge becomes how to incorporate those into AI models.

“We are trying to develop models that are going to be useful and relevant for the kinds of things that decision-makers need going forward when making climate policy choices. While it might be attractive to use the latest, big-picture machine-learning model on a climate problem, what this study shows is that stepping back and really thinking about the problem fundamentals is important and useful,” says study senior author Noelle Selin, a professor in the MIT Institute for Data, Systems, and Society (IDSS) and the Department of Earth, Atmospheric and Planetary Sciences (EAPS), and director of the Center for Sustainability Science and Strategy.

Selin’s co-authors are lead author Björn Lütjens, a former EAPS postdoc who is now a research scientist at IBM Research; senior author Raffaele Ferrari, the Cecil and Ida Green Professor of Oceanography in EAPS and co-director of the Lorenz Center; and Duncan Watson-Parris, assistant professor at the University of California at San Diego. Selin and Ferrari are also co-principal investigators of the Bringing Computation to the Climate Challenge project, out of which this research emerged. The paper appears today in the Journal of Advances in Modeling Earth Systems.

Comparing emulators

Because the Earth’s climate is so complex, running a state-of-the-art climate model to predict how pollution levels will impact environmental factors like temperature can take weeks on the world’s most powerful supercomputers.

Scientists often create climate emulators, simpler approximations of a state-of-the art climate model, which are faster and more accessible. A policymaker could use a climate emulator to see how alternative assumptions on greenhouse gas emissions would affect future temperatures, helping them develop regulations.

But an emulator isn’t very useful if it makes inaccurate predictions about the local impacts of climate change. While deep learning has become increasingly popular for emulation, few studies have explored whether these models perform better than tried-and-true approaches.

The MIT researchers performed such a study. They compared a traditional technique called linear pattern scaling (LPS) with a deep-learning model using a common benchmark dataset for evaluating climate emulators.

Their results showed that LPS outperformed deep-learning models on predicting nearly all parameters they tested, including temperature and precipitation.

“Large AI methods are very appealing to scientists, but they rarely solve a completely new problem, so implementing an existing solution first is necessary to find out whether the complex machine-learning approach actually improves upon it,” says Lütjens.

Some initial results seemed to fly in the face of the researchers’ domain knowledge. The powerful deep-learning model should have been more accurate when making predictions about precipitation, since those data don’t follow a linear pattern.

They found that the high amount of natural variability in climate model runs can cause the deep learning model to perform poorly on unpredictable long-term oscillations, like El Niño/La Niña. This skews the benchmarking scores in favor of LPS, which averages out those oscillations.

Constructing a new evaluation

From there, the researchers constructed a new evaluation with more data that address natural climate variability. With this new evaluation, the deep-learning model performed slightly better than LPS for local precipitation, but LPS was still more accurate for temperature predictions.

“It is important to use the modeling tool that is right for the problem, but in order to do that you also have to set up the problem the right way in the first place,” Selin says.

Based on these results, the researchers incorporated LPS into a climate emulation platform to predict local temperature changes in different emission scenarios.

“We are not advocating that LPS should always be the goal. It still has limitations. For instance, LPS doesn’t predict variability or extreme weather events,” Ferrari adds.

Rather, they hope their results emphasize the need to develop better benchmarking techniques, which could provide a fuller picture of which climate emulation technique is best suited for a particular situation.

“With an improved climate emulation benchmark, we could use more complex machine-learning methods to explore problems that are currently very hard to address, like the impacts of aerosols or estimations of extreme precipitation,” Lütjens says.

Ultimately, more accurate benchmarking techniques will help ensure policymakers are making decisions based on the best available information.

The researchers hope others build on their analysis, perhaps by studying additional improvements to climate emulation methods and benchmarks. Such research could explore impact-oriented metrics like drought indicators and wildfire risks, or new variables like regional wind speeds.

This research is funded, in part, by Schmidt Sciences, LLC, and is part of the MIT Climate Grand Challenges team for “Bringing Computation to the Climate Challenge.”

While sharing a single cup of coffee, Raul Radovitzky, the Jerome C. Hunsaker Professor in the Department of Aeronautics and Astronautics, and his wife Flavia Cardarelli, senior administrative assistant in the Institute for Data, Systems, and Society, recently discussed the love they have for their “nighttime jobs” living in McCormick Hall as faculty heads of house, and explained why it is so gratifying for them to be a part of this community.

The couple, married for 32 years, first met playing in a sandbox at the age of 3 in Argentina (but didn't start dating until they were in their 20s). Radovitzky has been a part of the MIT ecosystem since 2001, while Cardarelli began working at MIT in 2006. They became heads of house at McCormick Hall, the only all-female residence hall on campus, in 2015, and recently applied to extend their stay.

“Our head-of-house role is always full of surprises. We never know what we’ll encounter, but we love it. Students think we do this just for them, but in truth, it’s very rewarding for us as well. It keeps us on our toes and brings a lot of joy,” says Cardarelli. “We like to think of ourselves as the cool aunt and uncle for the students,” Radovitzky adds.

Heads of house at MIT influence many areas of students’ development by acting as advisors and mentors to their residents. Additionally, they work closely with the residence hall’s student government, as well as staff from the Division of Student Life, to foster their community’s culture.

Vice Chancellor for Student Life Suzy Nelson explains, “Our faculty heads of house have the long view at MIT and care deeply about students’ academic and personal growth. We are fortunate to have such dedicated faculty who serve in this way. The heads of house enhance the student experience in so many ways — whether it is helping a student with a personal problem, hosting Thanksgiving dinner for students who were not able to go home, or encouraging students to get involved in new activities, they are always there for students.”

“Our heads of house help our students fully participate in residential life. They model civil discourse at community dinners, mentor and tutor residents, and encourage residents to try new things. With great expertise and aplomb, they formally and informally help our students become their whole selves,” says Chancellor Melissa Nobles.

“I love teaching, I love conducting research with my group, and I enjoy serving as a head of house. The community aspect is deeply meaningful to me. MIT has become such a central part of our lives. Our kids are both MIT graduates, and we are incredibly proud of them. We do have a life outside of MIT — weekends with friends and family, personal activities — but MIT is a big part of who we are. It’s more than a job; it’s a community. We live on campus, and while it can be intense and demanding, we really love it,” says Radovitzky.

Jessica Quaye ’20, a former resident of McCormick Hall, says, “what sets McCormick apart is the way Raul and Flavia transform the four dorm walls into a home for everyone. You might come to McCormick alone, but you never leave alone. If you ran into them somewhere on campus, you could be sure that they would call you out and wave excitedly. You could invite Raul and Flavia to your concerts and they would show up to support your extracurricular endeavors. They built an incredible family that carries the fabric of MIT with a blend of academic brilliance, a warm open-door policy, and unwavering support for our extracurricular pursuits.”

Soundbytes

Q: What first drew you to the heads of house role?

Radovitzky: I had been aware of the role since I arrived at MIT, and over time, I started to wonder if it might be something we’d consider. When our kids were young, it didn’t seem feasible — we lived in the suburbs, and life there was good. But I always had an innate interest in building stronger connections with the student community.

Later, several colleagues encouraged us to apply. I discussed it with the family. Everyone was excited about it. Our teenagers were thrilled by the idea of living on a college campus. We applied together, submitting a letter as a family explaining why we were so passionate about it. We interviewed at McCormick, Baker, and McGregor. When we were offered McCormick, I’ll admit — I was nervous. I wasn’t sure I’d be the right fit for an all-female residence.

Cardarelli: We would have been nervous no matter where we ended up, but McCormick felt like home. It suited us in ways we didn’t anticipate. Raul, for instance, discovered he had a real rapport with the students, telling goofy jokes, making karaoke playlists, and learning about Taylor Swift and Nicki Minaj.

Radovitzky: It’s true! I never knew I’d become an expert at picking karaoke playlists. But we found our rhythm here, and it’s been deeply rewarding.

Q: What makes the McCormick community special?

Radovitzky: McCormick has a unique spirit. I can step out of our apartment and be greeted by 10 smiling faces. That energy is contagious. It’s not just about events or programming — it’s about building trust. We’ve built traditions around that, like our “make your own pizza” nights in our apartment, a wonderful McCormick event we inherited from our predecessors. We host four sessions each spring in which students roll out dough, choose toppings, and we chat as we cook and eat together. Everyone remembers the pizza nights — they’re mentioned in every testimonial.

Cardarelli: We’ve been lucky to have amazing graduate resident assistants and area directors every year. They’re essential partners in building community. They play a key role in creating community and supporting the students on their floors. They help with everything — from tutoring to events to walking students to urgent care if needed.

Radovitzky: In the fall, we take our residents to Crane Beach and host a welcome brunch. Karaoke in our apartment is a big hit too, and a unique way to make them comfortable coming to our apartment from day one. We do it three times a year — during orientation, and again each semester.

Cardarelli: We also host monthly barbecues open to all dorms and run McFast, our first-year tutoring program. Raul started by tutoring physics and math, four hours a week. Now, upperclass students lead most of the sessions. It’s great for both academic support and social connection.

Radovitzky: We also have an Independent Activities Period pasta night tradition. We cook for around 100 students, using four sauces that Flavia makes from scratch — bolognese, creamy mushroom, marinara, and pesto. Students love it.

Q: What’s unique about working in an all-female residence hall?

Cardarelli: I’ve helped students hem dresses, bake, and even apply makeup. It’s like having hundreds of daughters.

Radovitzky: The students here are incredibly mature and engaged. They show real interest in us as people. Many of the activities and connections we’ve built wouldn’t be possible in a different setting. Every year during “de-stress night,” I get my nails painted every color and have a face mask on. During “Are You Smarter Than an MIT Professor,” they dunk me in a water tank.

Growing up in the suburban town of Spring, Texas, just outside of Houston, Erik Ballesteros couldn’t help but be drawn in by the possibilities for humans in space.

It was the early 2000s, and NASA’s space shuttle program was the main transport for astronauts to the International Space Station (ISS). Ballesteros’ hometown was less than an hour from Johnson Space Center (JSC), where NASA’s mission control center and astronaut training facility are based. And as often as they could, he and his family would drive to JSC to check out the center’s public exhibits and presentations on human space exploration.

For Ballesteros, the highlight of these visits was always the tram tour, which brings visitors to JSC’s Astronaut Training Facility. There, the public can watch astronauts test out spaceflight prototypes and practice various operations in preparation for living and working on the International Space Station.

“It was a really inspiring place to be, and sometimes we would meet astronauts when they were doing signings,” he recalls. “I’d always see the gates where the astronauts would go back into the training facility, and I would think: One day I’ll be on the other side of that gate.”

Today, Ballesteros is a PhD student in mechanical engineering at MIT, and has already made good on his childhood goal. Before coming to MIT, he interned on multiple projects at JSC, working in the training facility to help test new spacesuit materials, portable life support systems, and a propulsion system for a prototype Mars rocket. He also helped train astronauts to operate the ISS’ emergency response systems.

Those early experiences steered him to MIT, where he hopes to make a more direct impact on human spaceflight. He and his advisor, Harry Asada, are building a system that will quite literally provide helping hands to future astronauts. The system, dubbed SuperLimbs, consists of a pair of wearable robotic arms that extend out from a backpack, similar to the fictional Inspector Gadget, or Doctor Octopus (“Doc Ock,” to comic book fans). Ballesteros and Asada are designing the robotic arms to be strong enough to lift an astronaut back up if they fall. The arms could also crab-walk around a spacecraft’s exterior as an astronaut inspects or makes repairs.

Ballesteros is collaborating with engineers at the NASA Jet Propulsion Laboratory to refine the design, which he plans to introduce to astronauts at JSC in the next year or two, for practical testing and user feedback. He says his time at MIT has helped him make connections across academia and in industry that have fueled his life and work.

“Success isn’t built by the actions of one, but rather it’s built on the shoulders of many,” Ballesteros says. “Connections — ones that you not just have, but maintain — are so vital to being able to open new doors and keep great ones open.”

Getting a jumpstart

Ballesteros didn’t always seek out those connections. As a kid, he counted down the minutes until the end of school, when he could go home to play video games and watch movies, “Star Wars” being a favorite. He also loved to create and had a talent for cosplay, tailoring intricate, life-like costumes inspired by cartoon and movie characters.

In high school, he took an introductory class in engineering that challenged students to build robots from kits, that they would then pit against each other, BattleBots-style. Ballesteros built a robotic ball that moved by shifting an internal weight, similar to Star Wars’ fictional, sphere-shaped BB-8. 

“It was a good introduction, and I remember thinking, this engineering thing could be fun,” he says.

After graduating high school, Ballesteros attended the University of Texas at Austin, where he pursued a bachelor’s degree in aerospace engineering. What would typically be a four-year degree stretched into an eight-year period during which Ballesteros combined college with multiple work experiences, taking on internships at NASA and elsewhere. 

In 2013, he interned at Lockheed Martin, where he contributed to various aspects of jet engine development. That experience unlocked a number of other aerospace opportunities. After a stint at NASA’s Kennedy Space Center, he went on to Johnson Space Center, where, as part of a co-op program called Pathways, he returned every spring or summer over the next five years, to intern in various departments across the center.

While the time at JSC gave him a huge amount of practical engineering experience, Ballesteros still wasn’t sure if it was the right fit. Along with his childhood fascination with astronauts and space, he had always loved cinema and the special effects that forged them. In 2018, he took a year off from the NASA Pathways program to intern at Disney, where he spent the spring semester working as a safety engineer, performing safety checks on Disney rides and attractions.

During this time, he got to know a few people in Imagineering — the research and development group that creates, designs, and builds rides, theme parks, and attractions. That summer, the group took him on as an intern, and he worked on the animatronics for upcoming rides, which involved translating certain scenes in a Disney movie into practical, safe, and functional scenes in an attraction.

“In animation, a lot of things they do are fantastical, and it was our job to find a way to make them real,” says Ballesteros, who loved every moment of the experience and hoped to be hired as an Imagineer after the internship came to an end. But he had one year left in his undergraduate degree and had to move on.

After graduating from UT Austin in December 2019, Ballesteros accepted a position at NASA’s Jet Propulsion Laboratory in Pasadena, California. He started at JPL in February of 2020, working on some last adjustments to the Mars Perseverance rover. After a few months during which JPL shifted to remote work during the Covid pandemic, Ballesteros was assigned to a project to develop a self-diagnosing spacecraft monitoring system. While working with that team, he met an engineer who was a former lecturer at MIT. As a practical suggestion, she nudged Ballesteros to consider pursuing a master’s degree, to add more value to his CV.

“She opened up the idea of going to grad school, which I hadn’t ever considered,” he says.

Full circle

In 2021, Ballesteros arrived at MIT to begin a master’s program in mechanical engineering. In interviewing with potential advisors, he immediately hit it off with Harry Asada, the Ford Professor of Enginering and director of the d'Arbeloff Laboratory for Information Systems and Technology. Years ago, Asada had pitched JPL an idea for wearable robotic arms to aid astronauts, which they quickly turned down. But Asada held onto the idea, and proposed that Ballesteros take it on as a feasibility study for his master’s thesis.

The project would require bringing a seemingly sci-fi idea into practical, functional form, for use by astronauts in future space missions. For Ballesteros, it was the perfect challenge. SuperLimbs became the focus of his master’s degree, which he earned in 2023. His initial plan was to return to industry, degree in hand. But he chose to stay at MIT to pursue a PhD, so that he could continue his work with SuperLimbs in an environment where he felt free to explore and try new things.

“MIT is like nerd Hogwarts,” he says. “One of the dreams I had as a kid was about the first day of school, and being able to build and be creative, and it was the happiest day of my life. And at MIT, I felt like that dream became reality.”

Ballesteros and Asada are now further developing SuperLimbs. The team recently re-pitched the idea to engineers at JPL, who reconsidered, and have since struck up a partnership to help test and refine the robot. In the next year or two, Ballesteros hopes to bring a fully functional, wearable design to Johnson Space Center, where astronauts can test it out in space-simulated settings.

In addition to his formal graduate work, Ballesteros has found a way to have a bit of Imagineer-like fun. He is a member of the MIT Robotics Team, which designs, builds, and runs robots in various competitions and challenges. Within this club, Ballesteros has formed a sub-club of sorts, called the Droid Builders, that aim to build animatronic droids from popular movies and franchises.

“I thought I could use what I learned from Imagineering and teach undergrads how to build robots from the ground up,” he says. “Now we’re building a full-scale WALL-E that could be fully autonomous. It’s cool to see everything come full circle.”

Cognitive readiness denotes a person's ability to respond and adapt to the changes around them. This includes functions like keeping balance after tripping, or making the right decision in a challenging situation based on knowledge and past experiences. For military service members, cognitive readiness is crucial for their health and safety, as well as mission success. Injury to the brain is a major contributor to cognitive impairment, and between 2000 and 2024, more than 500,000 military service members were diagnosed with traumatic brain injury (TBI) — caused by anything from a fall during training to blast exposure on the battlefield. While impairment from factors like sleep deprivation can be treated through rest and recovery, others caused by injury may require more intense and prolonged medical attention.

"Current cognitive readiness tests administered to service members lack the sensitivity to detect subtle shifts in cognitive performance that may occur in individuals exposed to operational hazards," says Christopher Smalt, a researcher in the laboratory's Human Health and Performance Systems Group. "Unfortunately, the cumulative effects of these exposures are often not well-documented during military service or after transition to Veterans Affairs, making it challenging to provide effective support."

Smalt is part of a team at the laboratory developing a suite of portable diagnostic tests that provide near-real-time screening for brain injury and cognitive health. One of these tools, called READY, is a smartphone or tablet app that helps identify a potential change in cognitive performance in less than 90 seconds. Another tool, called MINDSCAPE — which is being developed in collaboration with Richard Fletcher, a visiting scientist in the Rapid Prototyping Group who leads the Mobile Technology Lab at the MIT Auto-ID Laboratory, and his students — uses virtual reality (VR) technology for a more in-depth analysis to pinpoint specific conditions such as TBI, post-traumatic stress disorder, or sleep deprivation. Using these tests, medical personnel on the battlefield can make quick and effective decisions for treatment triage.

Both READY and MINDSCAPE are a response to a series of Congressional legislation mandates, military program requirements, and mission-driven health needs to improve brain health screening capabilities for service members.

Cognitive readiness biomarkers

The READY and MINDSCAPE platforms incorporate more than a decade of laboratory research on finding the right indicators of cognitive readiness to build into rapid testing applications. Thomas Quatieri oversaw this work and identified balance, eye movement, and speech as three reliable biomarkers. He is leading the effort at Lincoln Laboratory to develop READY.

"READY stands for Rapid Evaluation of Attention for DutY, and is built on the premise that attention is the key to being 'ready' for a mission," he says. "In one view, we can think of attention as the mental state that allows you to focus on a task."

For someone to be attentive, their brain must continuously anticipate and process incoming sensory information and then instruct the body to respond appropriately. For example, if a friend yells "catch" and then throws a ball in your direction, in order to catch that ball, your brain must process the incoming auditory and visual data, predict in advance what may happen in the next few moments, and then direct your body to respond with an action that synchronizes those sensory data. The result? You realize from hearing the word "catch" and seeing the moving ball that your friend is throwing the ball to you, and you reach out a hand to catch it just in time.

"An unhealthy or fatigued brain — caused by TBI or sleep deprivation, for example — may have challenges within a neurosensory feed-forward [prediction] or feedback [error] system, thus hampering the person's ability to attend," Quatieri says.

READY's three tests measure a person’s ability to track a moving dot with their eye, balance, and hold a vowel fixed at one pitch. The app then uses the data to calculate a variability or "wobble" indicator, which represents changes from the test taker's baseline or from expected results based on others with similar demographics, or the general population. The results are displayed to the user as an indication of the patient's level of attention.

If the READY screen shows an impairment, the administrator can then direct the subject to follow up with MINDSCAPE, which stands for Mobile Interface for Neurological Diagnostic Situational Cognitive Assessment and Psychological Evaluation. MINDSCAPE uses VR technology to administer additional, in-depth tests to measure cognitive functions such as reaction time and working memory. These standard neurocognitive tests are recorded with multimodal physiological sensors, such as electroencephalography (EEG), photoplethysmography, and pupillometry, to better pinpoint diagnosis.

Holistic and adaptable

A key advantage of READY and MINDSCAPE is their ability to leverage existing technologies, allowing for rapid deployment in the field. By utilizing sensors and capabilities already integrated into smartphones, tablets, and VR devices, these assessment tools can be easily adapted for use in operational settings at a significantly reduced cost.

"We can immediately apply our advanced algorithms to the data collected from these devices, without the need for costly and time-consuming hardware development," Smalt says. "By harnessing the capabilities of commercially available technologies, we can quickly provide valuable insights and improve upon traditional assessment methods."

Bringing new capabilities and AI for brain-health sensing into operational environments is a theme across several projects at the laboratory. Another example is EYEBOOM (Electrooculography and Balance Blast Overpressure Monitoring System), a wearable technology developed for the U.S. Special Forces to monitor blast exposure. EYEBOOM continuously monitors a wearer's eye and body movements as they experience blast energy, and warns of potential harm. For this program, the laboratory developed an algorithm that could identify a potential change in physiology resulting from blast exposure during operations, rather than waiting for a check-in.

All three technologies are in development to be versatile, so they can be adapted for other relevant uses. For example, a workflow could pair EYEBOOM's monitoring capabilities with the READY and MINDSCAPE tests: EYEBOOM would continuously monitor for exposure risk and then prompt the wearer to seek additional assessment.

"A lot of times, research focuses on one specific modality, whereas what we do at the laboratory is search for a holistic solution that can be applied for many different purposes," Smalt says.

MINDSCAPE is undergoing testing at the Walter Reed National Military Center this year. READY will be tested with the U.S. Army Research Institute of Environmental Medicine (USARIEM) in 2026 in the context of sleep deprivation. Smalt and Quatieri also see the technologies finding use in civilian settings — on sporting event sidelines, in doctors' offices, or wherever else there is a need to assess brain readiness.

MINDSCAPE is being developed with clinical validation and support from Stefanie Kuchinsky at the Walter Reed National Military Medical Center. Quatieri and his team are developing the READY tests in collaboration with Jun Maruta and Jam Ghajar from the Brain Trauma Foundation (BTF), and Kristin Heaton from USARIEM. The tests are supported by concurrent evidence-based guidelines lead by the BTF and the Military TBI Initiative at Uniform Services University.

Back in the 17th century, German astronomer Johannes Kepler figured out the laws of motion that made it possible to accurately predict where our solar system’s planets would appear in the sky as they orbit the sun. But it wasn’t until decades later, when Isaac Newton formulated the universal laws of gravitation, that the underlying principles were understood. Although they were inspired by Kepler’s laws, they went much further, and made it possible to apply the same formulas to everything from the trajectory of a cannon ball to the way the moon’s pull controls the tides on Earth — or how to launch a satellite from Earth to the surface of the moon or planets.

Today’s sophisticated artificial intelligence systems have gotten very good at making the kind of specific predictions that resemble Kepler’s orbit predictions. But do they know why these predictions work, with the kind of deep understanding that comes from basic principles like Newton’s laws? As the world grows ever-more dependent on these kinds of AI systems, researchers are struggling to try to measure just how they do what they do, and how deep their understanding of the real world actually is.

Now, researchers in MIT’s Laboratory for Information and Decision Systems (LIDS) and at Harvard University have devised a new approach to assessing how deeply these predictive systems understand their subject matter, and whether they can apply knowledge from one domain to a slightly different one. And by and large the answer at this point, in the examples they studied, is — not so much.

The findings were presented at the International Conference on Machine Learning, in Vancouver, British Columbia, last month by Harvard postdoc Keyon Vafa, MIT graduate student in electrical engineering and computer science and LIDS affiliate Peter G. Chang, MIT assistant professor and LIDS principal investigator Ashesh Rambachan, and MIT professor, LIDS principal investigator, and senior author Sendhil Mullainathan.

“Humans all the time have been able to make this transition from good predictions to world models,” says Vafa, the study’s lead author. So the question their team was addressing was, “have foundation models — has AI — been able to make that leap from predictions to world models? And we’re not asking are they capable, or can they, or will they. It’s just, have they done it so far?” he says.

“We know how to test whether an algorithm predicts well. But what we need is a way to test for whether it has understood well,” says Mullainathan, the Peter de Florez Professor with dual appointments in the MIT departments of Economics and Electrical Engineering and Computer Science and the senior author on the study. “Even defining what understanding means was a challenge.” 

In the Kepler versus Newton analogy, Vafa says, “they both had models that worked really well on one task, and that worked essentially the same way on that task. What Newton offered was ideas that were able to generalize to new tasks.” That capability, when applied to the predictions made by various AI systems, would entail having it develop a world model so it can “transcend the task that you’re working on and be able to generalize to new kinds of problems and paradigms.”

Another analogy that helps to illustrate the point is the difference between centuries of accumulated knowledge of how to selectively breed crops and animals, versus Gregor Mendel’s insight into the underlying laws of genetic inheritance.

“There is a lot of excitement in the field about using foundation models to not just perform tasks, but to learn something about the world,” for example in the natural sciences, he says. “It would need to adapt, have a world model to adapt to any possible task.”

Are AI systems anywhere near the ability to reach such generalizations? To test the question, the team looked at different examples of predictive AI systems, at different levels of complexity. On the very simplest of examples, the systems succeeded in creating a realistic model of the simulated system, but as the examples got more complex that ability faded fast.

The team developed a new metric, a way of measuring quantitatively how well a system approximates real-world conditions. They call the measurement inductive bias — that is, a tendency or bias toward responses that reflect reality, based on inferences developed from looking at vast amounts of data on specific cases.

The simplest level of examples they looked at was known as a lattice model. In a one-dimensional lattice, something can move only along a line. Vafa compares it to a frog jumping between lily pads in a row. As the frog jumps or sits, it calls out what it’s doing — right, left, or stay. If it reaches the last lily pad in the row, it can only stay or go back. If someone, or an AI system, can just hear the calls, without knowing anything about the number of lily pads, can it figure out the configuration? The answer is yes: Predictive models do well at reconstructing the “world” in such a simple case. But even with lattices, as you increase the number of dimensions, the systems no longer can make that leap.

“For example, in a two-state or three-state lattice, we showed that the model does have a pretty good inductive bias toward the actual state,” says Chang. “But as we increase the number of states, then it starts to have a divergence from real-world models.”

A more complex problem is a system that can play the board game Othello, which involves players alternately placing black or white disks on a grid. The AI models can accurately predict what moves are allowable at a given point, but it turns out they do badly at inferring what the overall arrangement of pieces on the board is, including ones that are currently blocked from play.

The team then looked at five different categories of predictive models actually in use, and again, the more complex the systems involved, the more poorly the predictive modes performed at matching the true underlying world model.

With this new metric of inductive bias, “our hope is to provide a kind of test bed where you can evaluate different models, different training approaches, on problems where we know what the true world model is,” Vafa says. If it performs well on these cases where we already know the underlying reality, then we can have greater faith that its predictions may be useful even in cases “where we don’t really know what the truth is,” he says.

People are already trying to use these kinds of predictive AI systems to aid in scientific discovery, including such things as properties of chemical compounds that have never actually been created, or of potential pharmaceutical compounds, or for predicting the folding behavior and properties of unknown protein molecules. “For the more realistic problems,” Vafa says, “even for something like basic mechanics, we found that there seems to be a long way to go.”

Chang says, “There’s been a lot of hype around foundation models, where people are trying to build domain-specific foundation models — biology-based foundation models, physics-based foundation models, robotics foundation models, foundation models for other types of domains where people have been collecting a ton of data” and training these models to make predictions, “and then hoping that it acquires some knowledge of the domain itself, to be used for other downstream tasks.”

This work shows there’s a long way to go, but it also helps to show a path forward. “Our paper suggests that we can apply our metrics to evaluate how much the representation is learning, so that we can come up with better ways of training foundation models, or at least evaluate the models that we’re training currently,” Chang says. “As an engineering field, once we have a metric for something, people are really, really good at optimizing that metric.”

In welcoming the undergraduate Class of 2029 to campus in Cambridge, Massachusetts, MIT President Sally Kornbluth began the Institute’s convocation on Sunday with a greeting that underscored MIT’s confidence in its new students.

“We believe in all of you, in the learning, making, discovering, and inventing that you all have come here to do,” Kornbluth said. “And in your boundless potential as future leaders who will help solve real problems that people face in their daily lives.”

She added: “If you’re out there feeling really lucky to be joining this incredible community, I want you to know that we feel even more lucky. We’re delighted and grateful that you chose to bring your talent, your energy, your curiosity, creativity, and drive here to MIT. And we’re thrilled to be starting this new year with all of you.”

The event, officially called the President’s Convocation for First-years and Families, was held at the Johnson Ice Rink on campus.

While recognizing that academic life can be “intense” at MIT, Kornbluth highlighted the many opportunities available to students outside the classroom, too. A biologist and cancer researcher herself, Kornbluth observed that students can participate in the Undergraduate Research Opportunities Program (UROP), which Kornbluth called “an unmissable opportunity to work side by side with MIT faculty at the front lines of research.” She also noted that MIT offers abundant opportunities for entrepreneurship, as well as 450 official student organizations.

“It’s okay to be a beginner,” Kornbluth said. “Join a group you wouldn’t have had time for in high school. Explore a new skill. Volunteer in the neighborhoods around campus.”

And if the transition to college feels daunting at any point, she added, MIT provides considerable resources to students for well-being and academic help.

“Sometimes the only way to succeed in facing a big challenge or solving a tough problem is to admit there’s no way you can do it all yourself,” Kornbluth observed. “You’re surrounded by a community of caring people. So please don’t be shy about asking for guidance and help.”

The large audience heard additional remarks from two faculty members who themselves have MIT degrees, reflecting on student life at the Institute.

As a student, “The most important things I had were a willingness to take risks and put hard work into the things I cared about,” said Ankur Moitra SM ’09, PhD ’11, the Norbert Wiener Professor of Mathematics.

He emphasized to students the importance of staying grounded and being true to themselves, especially in the face of, say, social media pressures.

“These are the things that make it harder to find your own way and what you really care about,” Moitra said. “Because the rest of the world’s opinion is right there staring you in the face, and it’s impossible to avoid it. And how will you discover what’s important to you, what’s worth pouring yourself into?”

Moitra also advised students to be wary of the tech tools “that want to do the thinking for you, but take away your agency” in the process. He added: “I worry about this because it’s going to become too easy to rely on these tools, and there are going to be many times you’re going to be tempted, especially late at night, with looming p-set deadlines. As educators, we don’t always have fixes for these kinds of things, and all we can do is open the door and hope you walk through it.”

Beyond that, he suggested,“Periodically remind yourself about what’s been important to you all along, what brought you here. For your next four years, you’re going to be surrounded by creative, clever, passionate people every day, who are going to challenge you. Rise to that challenge.” 

Christopher Palmer PhD ’14, an associate professor of finance in the MIT Sloan School of Management, began his remarks by revealing that his MIT undergraduate application was not accepted — although he later received his doctorate at the Institute and is now a tenured professor at MIT.

“I played the long game,” he quipped, drawing laughs.

Indeed, Palmer’s remarks focused on cultivating the resilience, focus, and concentration needed to flourish in the long run.

While being at MIT is “thrilling,” Palmer advised students to “build enough slack into your system to handle both the stress and take advantage of the opportunities” on campus. Much like a bank conducts a “stress test” to see if it can withstand changes, Palmer suggested, we can try the same with our workloads: “If you build a schedule that passes the stress test, that means time for curiosity and meaningful creativity.”

Students should also avoid the “false equivalency that your worth is determined by your achievements,” he added. “You have inherent, immutable, instrinsic, eternal value. Be discerning with your commitments. Future you will be so grateful that you have built in the capacity to sleep, to catch up, to say ‘Yes’ to cool invitations, and to attend to your mental health.”

Additionally, Palmer recommended that students pursue “deep work,” involving “the hard thinking where progress actually happens” — a concept, he noted, that has been elevated by computer scientist Cal Newport SM ’06, PhD ’09. As research shows, Palmer explained, “We can’t actually multitask. What we’re really doing is switching tasks at high frequency and incurring a small cost every single time we switch our focus.”

It might help students, he added, to try some structural changes: Put the phone away, turn off alerts, pause notifications, and cultivate sleep. A healthy blend of academic work, activities, and community fun can emerge.

Concluding her own remarks, Kornbluth also emphasized that attending MIT means being part of a community that is respectful of varying viewpoints and all people, and sustains an ethos of fair-minded understanding.

“I know you have extremely high expectations for yourselves,” Kornbluth said, adding: “We have high expectations for you, too, in all kinds of ways. But I want to emphasize one that’s more important than all the others — and that’s an expectation for how we treat each other. At MIT, the work we do is so important, and so hard, that it’s essential we treat each other with empathy, understanding and compassion. That we take care to express our own ideas with clarity and respect, and make room for sharply different points of view. And above all, that we keep engaging in conversation, even when it’s difficult, frustrating or painful.”

The MIT Sailing Pavilion hosted an altogether different marine vessel recently: a prototype of a solar electric boat developed by James Worden ’89, the founder of the MIT Solar Electric Vehicle Team (SEVT). Worden visited the pavilion on a sizzling, sunny day in late July to offer students from the SEVT, the MIT Edgerton Center, MIT Sea Grant, and the broader community an inside look at the Anita, named for his late wife.

Worden’s fascination with solar power began at age 10, when he picked up a solar chip at a “hippy-like” conference in his hometown of Arlington, Massachusetts. “My eyes just lit up,” he says. He built his first solar electric vehicle in high school, fashioned out of cardboard and wood (taking first place at the 1984 Massachusetts Science Fair), and continued his journey at MIT, founding SEVT in 1986. It was through SEVT that he met his wife and lifelong business partner, Anita Rajan Worden ’90. Together, they founded two companies in the solar electric and hybrid vehicles space, and in 2022 launched a solar electric boat company.

On the Charles River, Worden took visitors for short rides on Anita, including a group of current SEVT students who peppered him with questions. The 20-foot pontoon boat, just 12 feet wide and 7 feet tall, is made of carbon fiber composites, single crystalline solar photovoltaic cells, and lithium iron phosphate battery cells. Ultimately, Worden envisions the prototype could have applications as mini-ferry boats and water taxis.

With warmth and humor, he drew parallels between the boat’s components and mechanics and those of the solar cars the students are building. “It’s fun! If you think about all the stuff you guys are doing, it’s all the same stuff,” he told them, “optimizing all the different systems and making them work.” He also explained the design considerations unique to boating applications, like refining the hull shape for efficiency and maneuverability in variable water and wind conditions, and the critical importance of protecting wiring and controls from open water and condensate.

“Seeing Anita in all its glory was super cool,” says Nicole Lin, vice captain of SEVT. “When I first saw it, I could immediately map the different parts of the solar car to its marine counterparts, which was astonishing to see how far I’ve come as an engineer with SEVT. James also explained the boat using solar car terms, as he drew on his experience with solar cars for his solar boats. It blew my mind to see the engineering we learned with SEVT in action.”

Over the years, the Wordens have been avid supporters of SEVT and the Edgerton Center, so the visit was, in part, a way to pay it forward to MIT. “There’s a lot of connections,” he says. He’s still awed by the fact that Harold “Doc” Edgerton, upon learning about his interest in building solar cars, carved out a lab space for him to use in Building 20 — as a first-year student. And a few years ago, as Worden became interested in marine vessels, he tapped Sea Grant Education Administrator Drew Bennett for a 90-minute whiteboard lecture, “MIT fire-hose style,” on hydrodynamics. “It was awesome!” he says.

For both research and medical purposes, researchers have spent decades pushing the limits of microscopy to produce ever deeper and sharper images of brain activity, not only in the cortex but also in regions underneath, such as the hippocampus. In a new study, a team of MIT scientists and engineers demonstrates a new microscope system capable of peering exceptionally deep into brain tissues to detect the molecular activity of individual cells by using sound.

“The major advance here is to enable us to image deeper at single-cell resolution,” says neuroscientist Mriganka Sur, a corresponding author along with mechanical engineering professor Peter So and principal research scientist Brian Anthony. Sur is the Paul and Lilah Newton Professor in The Picower Institute for Learning and Memory and the Department of Brain and Cognitive Sciences at MIT.

In the journal Light: Science and Applications, the team demonstrates that they could detect NAD(P)H, a molecule tightly associated with cell metabolism in general and electrical activity in neurons in particular, all the way through samples such as a 1.1-millimeter “cerebral organoid,” a 3D-mini brain-like tissue generated from human stem cells, and a 0.7-milimeter-thick slice of mouse brain tissue.

In fact, says co-lead author and mechanical engineering postdoc W. David Lee, who conceived the microscope’s innovative design, the system could have peered far deeper, but the test samples weren’t big enough to demonstrate that.

“That’s when we hit the glass on the other side,” he says. “I think we’re pretty confident about going deeper.”

Still, a depth of 1.1 milimeters is more than five times deeper than other microscope technologies can resolve NAD(P)H within dense brain tissue. The new system achieved the depth and sharpness by combining several advanced technologies to precisely and efficiently excite the molecule and then to detect the resulting energy, all without having to add any external labels, either via added chemicals or genetically engineered fluorescence.

Rather than focusing the required NAD(P)H excitation energy on a neuron with near ultraviolet light at its normal peak absorption, the scope accomplishes the excitation by focusing an intense, extremely short burst of light (a quadrillionth of a second long) at three times the normal absorption wavelength. Such “three-photon” excitation penetrates deep into tissue with less scattering by brain tissue because of the longer wavelength of the light (“like fog lamps,” Sur says). Meanwhile, although the excitation produces a weak fluorescent signal of light from NAD(P)H, most of the absorbed energy produces a localized (about 10 microns) thermal expansion within the cell, which produces sound waves that travel relatively easily through tissue compared to the fluorescence emission. A sensitive ultrasound microphone in the microscope detects those waves and, with enough sound data, software turns them into high-resolution images (much like a sonogram does). Imaging created in this way is “three-photon photoacoustic imaging.”

“We merged all these techniques — three-photon, label-free, photoacoustic detection,” says co-lead author Tatsuya Osaki, a research scientist in the Picower Institute in Sur’s lab. “We integrated all these cutting-edge techniques into one process to establish this ‘Multiphoton-In and Acoustic-Out’ platform.”

Lee and Osaki combined with research scientist Xiang Zhang and postdoc Rebecca Zubajlo to lead the study, in which the team demonstrated reliable detection of the sound signal through the samples. So far, the team has produced visual images from the sound at various depths as they refine their signal processing.

In the study, the team also shows simultaneous “third-harmonic generation” imaging, which comes from the three-photon stimulation and finely renders cellular structures, alongside their photoacoustic imaging, which detects NAD(P)H. They also note that their photoacoustic method could detect other molecules such as the genetically encoded calcium indicator GCaMP, that neuroscientists use to signal neural electrical activity.

With the concept of label-free, multiphoton, photoacoustic microscopy (LF-MP-PAM) established in the paper, the team is now looking ahead to neuroscience and clinical applications.

For instance, through the company Precision Healing, Inc., which he founded and sold, Lee has already established that NAD(P)H imaging can inform wound care. In the brain, levels of the molecule are known to vary in conditions such as Alzheimer’s disease, Rett syndrome, and seizures, making it a potentially valuable biomarker. Because the new system is label-free (i.e., no added chemicals or altered genes), it could be used in humans, for instance, during brain surgeries.

The next step for the team is to demonstrate it in a living animal, rather than just in in vitro and ex-vivo tissues. The technical challenge there is that the microphone can no longer be on the opposite side of the sample from the light source (as it was in the current study). It has to be on top, just like the light source.

Lee says he expects that full imaging at depths of 2 milimeters in live brains is entirely feasible, given the results in the new study.

“In principle, it should work,” he says.

Mercedes Balcells and Elazer Edelman are also authors of the paper. Funding for the research came from sources including the National Institutes of Health, the Simon Center for the Social Brain, the lab of Peter So, The Picower Institute for Learning and Memory, and the Freedom Together Foundation.

Marcus Stergio will join the MIT Ombuds Office on Aug. 25, bringing over a decade of experience as a mediator and conflict-management specialist. Previously an ombuds at the U.S. Department of Labor, Stergio will be part of MIT’s ombuds team, working alongside Judi Segall.

The MIT Ombuds Office provides a confidential, independent resource for all members of the MIT community to constructively manage concerns and conflicts related to their experiences at MIT.

Established in 1980, the office played a key role in the early development of the profession, helping to develop and establish standards of practice for organizational ombuds offices. The ombudspersons help MIT community members analyze concerns, clarify policies and procedures, and identify options to constructively manage conflicts.

“There’s this aura and legend around MIT’s Ombuds Office that is really exciting,” Stergio says.

Among other types of conflict resolution, the work of an ombuds is particularly appealing for its versatility, according to Stergio. “We can be creative and flexible in figuring out which types of processes work for the people seeking support, whether that’s having one-on-one, informal, confidential conversations or exploring more active and involved ways of getting their issues addressed,” he says.

Prior to coming to MIT, Stergio worked for six years at the Department of Labor, where he established a new externally facing ombuds office for the Office of Federal Contract Compliance Programs (OFCCP). There, he operated in accordance with the International Ombuds Association’s standards of practice, offering ombuds services to both external stakeholders and OFCCP employees.

He has also served as ombudsperson or in other conflict-management roles for a variety of organizations across multiple sectors. These included the Centers for Disease Control and Prevention, the United Nations Population Fund, General Motors, BMW of North America, and the U.S. Department of Treasury, among others. From 2013 to 2019, Stergio was a mediator and the manager of commercial and corporate programs for the Boston-based dispute resolution firm MWI.

Stergio has taught conflict resolution courses and delivered mediation and negotiation workshops at multiple universities, including MIT, where he says the interest in his subject matter was palpable. “There was something about the MIT community, whether it was students or staff or faculty. People seemed really energized by the conflict management skills that I was presenting to them,” he recalls. “There was this eagerness to perfect things that was inspiring and contagious.”

“I’m honored to be joining such a prestigious institution, especially one with such a rich history in the ombuds field,” Stergio adds. “I look forward to building on that legacy and working with the MIT community to navigate challenges together.”

Stergio earned a bachelor’s degree from Northeastern University in 2008 and a master’s in conflict resolution from the University of Massachusetts at Boston in 2012. He has served on the executive committee of the Coalition of Federal Ombuds since 2022, as co-chair of the American Bar Association’s ombuds day subcommittee, and as an editor for the newsletter of the ABA’s Dispute Resolution Section. He is also a member of the International Ombuds Association.

A fast radio burst is an immense flash of radio emission that lasts for just a few milliseconds, during which it can momentarily outshine every other radio source in its galaxy. These flares can be so bright that their light can be seen from halfway across the universe, several billion light years away.

The sources of these brief and dazzling signals are unknown. But scientists now have a chance to study a fast radio burst (FRB) in unprecedented detail. An international team of scientists including physicists at MIT have detected a near and ultrabright fast radio burst some 130 million light-years from Earth in the constellation Ursa Major. It is one of the closest FRBs detected to date. It is also the brightest — so bright that the signal has garnered the informal moniker, RBFLOAT, for “radio brightest flash of all time.”

The burst’s brightness, paired with its proximity, is giving scientists the closest look yet at FRBs and the environments from which they emerge.

“Cosmically speaking, this fast radio burst is just in our neighborhood,” says Kiyoshi Masui, associate professor of physics and affiliate of MIT’s Kavli Institute for Astrophysics and Space Research. “This means we get this chance to study a pretty normal FRB in exquisite detail.”

Masui and his colleagues report their findings today in the Astrophysical Journal Letters.

Diverse bursts

The clarity of the new detection is thanks to a significant upgrade to The Canadian Hydrogen Intensity Mapping Experiment (CHIME), a large array of halfpipe-shaped antennae based in British Columbia. CHIME was originally designed to detect and map the distribution of hydrogen across the universe. The telescope is also sensitive to ultrafast and bright radio emissions. Since it started observations in 2018, CHIME has detected about 4,000 fast radio bursts, from all parts of the sky. But the telescope had not been able to precisely pinpoint the location of each fast radio burst, until now.

CHIME recently got a significant boost in precision, in the form of CHIME Outriggers — three miniature versions of CHIME, each sited in different parts of North America. Together, the telescopes work as one continent-sized system that can focus in on any bright flash that CHIME detects, to pin down its location in the sky with extreme precision.

“Imagine we are in New York and there’s a firefly in Florida that is bright for a thousandth of a second, which is usually how quick FRBs are,” says MIT Kavli graduate student Shion Andrew. “Localizing an FRB to a specific part of its host galaxy is analogous to figuring out not just what tree the firefly came from, but which branch it’s sitting on.”

The new fast radio burst is the first detection made using the combination of CHIME and the completed CHIME Outriggers. Together, the telescope array identified the FRB and determined not only the specific galaxy, but also the region of the galaxy from where the burst originated. It appears that the burst arose from the edge of the galaxy, just outside of a star-forming region. The precise localization of the FRB is allowing scientists to study the environment around the signal for clues to what brews up such bursts.

“As we’re getting these much more precise looks at FRBs, we’re better able to see the diversity of environments they’re coming from,” says MIT physics postdoc Adam Lanman.

Lanman, Andrew, and Masui are members of the CHIME Collaboration — which includes scientists from multiple institutions around the world — and are authors of the new paper detailing the discovery of the new FRB detection.

An older edge

Each of CHIME’s Outrigger stations continuously monitors the same swath of sky as the parent CHIME array. Both CHIME and the Outriggers “listen” for radio flashes, at incredibly short, millisecond timescales. Even over several minutes, such precision monitoring can amount to a huge amount of data. If CHIME detects no FRB signal, the Outriggers automatically delete the last 40 seconds of data to make room for the next span of measurements.

On March 16, 2025, CHIME detected an ultrabright flash of radio emissions, which automatically triggered the CHIME Outriggers to record the data. Initially, the flash was so bright that astronomers were unsure whether it was an FRB or simply a terrestrial event caused, for instance, by a burst of cellular communications.

That notion was put to rest as the CHIME Outrigger telescopes focused in on the flash and pinned down its location to NGC4141 — a spiral galaxy in the constellation Ursa Major about 130 million light years away, which happens to be surprisingly close to our own Milky Way. The detection is one of the closest and brightest fast radio bursts detected to date.

Follow-up observations in the same region revealed that the burst came from the very edge of an active region of star formation. While it’s still a mystery as to what source could produce FRBs, scientists’ leading hypothesis points to magnetars — young neutron stars with extremely powerful magnetic fields that can spin out high-energy flares across the electromagnetic spectrum, including in the radio band. Physicists suspect that magnetars are found in the center of star formation regions, where the youngest, most active stars are forged. The location of the new FRB, just outside a star-forming region in its galaxy, may suggest that the source of the burst is a slightly older magnetar.

“These are mostly hints,” Masui says. “But the precise localization of this burst is letting us dive into the details of how old an FRB source could be. If it were right in the middle, it would only be thousands of years old — very young for a star. This one, being on the edge, may have had a little more time to bake.”

No repeats

In addition to pinpointing where the new FRB was in the sky, the scientists also looked back through CHIME data to see whether any similar flares occurred in the same region in the past. Since the first FRB was discovered in 2007, astronomers have detected over 4,000 radio flares. Most of these bursts are one-offs. But a few percent have been observed to repeat, flashing every so often. And an even smaller fraction of these repeaters flash in a pattern, like a rhythmic heartbeat, before flaring out. A central question surrounding fast radio bursts is whether repeaters and nonrepeaters come from different origins.

The scientists looked through CHIME’s six years of data and came up empty: This new FRB appears to be a one-off, at least in the last six years. The findings are particularly exciting, given the burst’s proximity. Because it is so close and so bright, scientists can probe the environment in and around the burst for clues to what might produce a nonrepeating FRB.

“Right now we’re in the middle of this story of whether repeating and nonrepeating FRBs are different. These observations are putting together bits and pieces of the puzzle,” Masui says.

“There’s evidence to suggest that not all FRB progenitors are the same,” Andrew adds. “We’re on track to localize hundreds of FRBs every year. The hope is that a larger sample of FRBs localized to their host environments can help reveal the full diversity of these populations.”

The construction of the CHIME Outriggers was funded by the Gordon and Betty Moore Foundation and the U.S. National Science Foundation. The construction of CHIME was funded by the Canada Foundation for Innovation and provinces of Quebec, Ontario, and British Columbia.

Rising global temperatures affect human activity in many ways. Now, a new study illuminates an important dimension of the problem: Very hot days are associated with more negative moods, as shown by a large-scale look at social media postings.

Overall, the study examines 1.2 billion social media posts from 157 countries over the span of a year. The research finds that when the temperature rises above 95 degrees Fahrenheit, or 35 degrees Celsius, expressed sentiments become about 25 percent more negative in lower-income countries and about 8 percent more negative in better-off countries. Extreme heat affects people emotionally, not just physically.

“Our study reveals that rising temperatures don’t just threaten physical health or economic productivity — they also affect how people feel, every day, all over the world,” says Siqi Zheng, a professor in MIT’s Department of Urban Studies and Planning (DUSP) and Center for Real Estate (CRE), and co-author of a new paper detailing the results. “This work opens up a new frontier in understanding how climate stress is shaping human well-being at a planetary scale.”

The paper, “Unequal Impacts of Rising Temperatures on Global Human Sentiment,” is published today in the journal One Earth. The authors are Jianghao Wang, of the Chinese Academy of Sciences; Nicolas Guetta-Jeanrenaud SM ’22, a graduate of MIT’s Technology and Policy Program (TPP) and Institute for Data, Systems, and Society; Juan Palacios, a visiting assistant professor at MIT’s Sustainable Urbanization Lab (SUL) and an assistant professor Maastricht University; Yichun Fan, of SUL and Duke University; Devika Kakkar, of Harvard University; Nick Obradovich, of SUL and the Laureate Institute for Brain Research in Tulsa; and Zheng, who is the STL Champion Professor of Urban and Real Estate Sustainability at CRE and DUSP. Zheng is also the faculty director of CRE and founded the Sustainable Urbanization Lab in 2019.

Social media as a window

To conduct the study, the researchers evaluated 1.2 billion posts from the social media platforms Twitter and Weibo, all of which appeared in 2019. They used a natural language processing technique called Bidirectional Encoder Representations from Transformers (BERT), to analyze 65 languages across the 157 countries in the study.

Each social media post was given a sentiment rating from 0.0 (for very negative posts) to 1.0 (for very positive posts). The posts were then aggregated geographically to 2,988 locations and evaluated in correlation with area weather. From this method, the researchers could then deduce the connection between extreme temperatures and expressed sentiment.

“Social media data provides us with an unprecedented window into human emotions across cultures and continents,” Wang says. “This approach allows us to measure emotional impacts of climate change at a scale that traditional surveys simply cannot achieve, giving us real-time insights into how temperature affects human sentiment worldwide.”

To assess the effects of temperatures on sentiment in higher-income and middle-to-lower-income settings, the scholars also used a World Bank cutoff level of gross national income per-capita annual income of $13,845, finding that in places with incomes below that, the effects of heat on mood were triple those found in economically more robust settings.

“Thanks to the global coverage of our data, we find that people in low- and middle-income countries experience sentiment declines from extreme heat that are three times greater than those in high-income countries,” Fan says. “This underscores the importance of incorporating adaptation into future climate impact projections.”

In the long run

Using long-term global climate models, and expecting some adaptation to heat, the researchers also produced a long-range estimate of the effects of extreme temperatures on sentiment by the year 2100. Extending the current findings to that time frame, they project a 2.3 percent worsening of people’s emotional well-being based on high temperatures alone by then — although that is a far-range projection.

“It's clear now, with our present study adding to findings from prior studies, that weather alters sentiment on a global scale,” Obradovich says. “And as weather and climates change, helping individuals become more resilient to shocks to their emotional states will be an important component of overall societal adaptation.”

The researchers note that there are many nuances to the subject, and room for continued research in this area. For one thing, social media users are not likely to be a perfectly representative portion of the population, with young children and the elderly almost certainly using social media less than other people. However, as the researchers observe in the paper, the very young and elderly are probably particularly vulnerable to heat shocks, making the response to hot weather possible even larger than their study can capture.

The research is part of the Global Sentiment project led by the MIT Sustainable Urbanization Lab, and the study’s dataset is publicly available. Zheng and other co-authors have previously investigated these dynamics using social media, although never before at this scale.

“We hope this resource helps researchers, policymakers, and communities better prepare for a warming world,” Zheng says.

The research was supported, in part, by Zheng’s chaired professorship research fund, and grants Wang received from the National Natural Science Foundation of China and the Chinese Academy of Sciences. 

Many things account for Haiti’s modern troubles. A good perspective on them comes from going back in time to 1715 or so — and grappling with a far-flung narrative involving the French monarchy, a financial speculator named John Law, and a stock-market crash called the “Mississippi Bubble.”

To condense: After the death of Louis XIV in 1715, France was mired in debt following decades of war. The country briefly turned over its economic policy to Law, a Scotsman who implemented a system in which, among other things, French debt was retired while private monopoly companies expanded overseas commerce.

This project did not go entirely as planned. Stock-market speculation created the “Mississippi Bubble” and crash of 1719-20. Amid the chaos, Law lost a short-lived fortune and left France.

Yet Law’s system had lasting effects. French expansionism helped spur Haiti’s “sugar revolution” of the early 1700s, in which the country’s economy first became oriented around labor-intensive sugar plantations. Using enslaved workers and deploying violence against political enemies, plantation owners helped define Haiti’s current-day geography and place within the global economy, creating an extractive system benefitting a select few.

While there has been extensive debate about how the Haitian Revolution of 1789-1804 (and the 1825 “indemnity” Haiti agreed to pay France) has influenced the country’s subsequent path, the events of the early 1700s help illuminate the whole picture.

“This is a moment of transformation for Haiti’s history that most people don’t know much about,” says MIT historian Malick Ghachem. “And it happened well before independence. It goes back to the 18th century when Haiti began to be enmeshed in the debtor-creditor relationships from which it has never really escaped. The 1720s was the period when those relationships crystallized.”

Ghachem examines the economic transformations and multi-sided power struggles of that time in a new book, “The Colony and the Company: Haiti after the Mississippi Bubble,” published this summer by Princeton University Press.

“How did Haiti come to be the way it is today? This is the question everybody asks about it,” says Ghachem. “This book is an intervention in that debate.”

Enmeshed in the crisis

Ghachem is both a professor and head of MIT’s program in history. A trained lawyer, his work ranges across France’s global history and American legal history. His 2012 book “The Old Regime and the Haitian Revolution,” also situated in pre-revolutionary Haiti, examines the legal backdrop of the drive for emancipation.

“The Colony and the Company” draws on original archival research while arriving at two related conclusions: Haiti was a big part of the global bubble of the 1710s, and that bubble and its aftermath is a big part of Haiti’s history.

After all, until the late 1600s, Haiti, then known as Saint Domingue, was “a fragile, mostly ungoverned, and sparsely settled place of uncertain direction,” as Ghachem writes in the book. The establishment of Haiti’s economy is not just the background of later events, but a formative event on its own.

And while the “sugar revolution” may have reached Haiti sooner or later, it was amplified by France’s quest for new sources of revenue. Louis XIV’s military agenda had been a fiscal disaster for the French. Law — a convicted murderer, and evidently a persuasive salesman — proposed a restructuring scheme that concentrated revenue-raising and other fiscal powers in a monopoly overseas trading company and bank overseen by Law himself.

As France sought economic growth beyond its borders, that led the company to Haiti, to tap its agricultural potential. For that matter, as Ghachem details, multiple countries were expanding their overseas activities — and France, Britain, and Spain also increased slave-trading activities markedly. Within a few decades, Haiti was a center of global sugar production, based on slave labor.

“When the company is seen as the answer to France’s own woes, Haiti becomes enmeshed in the crisis,” Ghachem says. “The Mississippi Bubble of 1719-20 was really a global event. And one of the theaters where it played out most dramatically was Haiti.”

As it happens, in Haiti, the dynamics of this were complex. Local planters did not want to be answerable to Law’s company, and fended it off, but, as Ghachem writes,  they “internalized and privatized the financial and economic logic of the System against which they had re­belled, making of it a script for the management of plantation society.”

That society was complex. One of the main elements of “The Colony and the Company” is the exploration of its nuances. Haiti was home to a variety of people, including Jesuit missionaries, European women who had been re-settled there, and maroons (freed or escaped slaves living apart from plantations), among others. Plantation life came with violence, civic instability, and a lack of economic alternatives.

“What’s called the ‘success’ of the colony as a French economic force is really inseparable from the conditions that make it hard for Haiti to survive as an independent nation after the revolution,” Ghachem observes.

Stories in a new light

In public discourse, questions about Haiti’s past are often considered highly relevant to its present, as a near-failed state whose capital city is now substantially controlled by gangs, with no end to violence in sight. Some people draw a through line between the present and Haiti’s revolutionary-era condition. But to Ghachem, the revolution changed some political dynamics, but not the underlying conditions of life in the country.

“One [view] is that it’s the Haitian Revolution that leads to Haiti’s immiseration and violence and political dysfunction and its economic underdevelopment,” Ghachem says. “I think that argument is wrong. It’s an older problem that goes back to Haiti’s relationship with France in the late 17th and early 18th centuries. The revolution compounds that problem, and does so significantly, because of how France responds. But the terms of Haiti’s subordination are already set.”

Other scholars have praised “The Colony and the Company.” Pernille Røge of the University of Pittsburgh has called it “a multilayered and deeply compelling history rooted in a careful analysis of both familiar and unfamiliar primary sources.”

For his part, Ghachem hopes to persuade anyone interested in Haiti’s past and present to look more expansively at the subject, and consider how the deep roots of Haiti’s economy have helped structure its society.

“I’m trying to keep up with the day job of a historian,” Ghachem says. “Which includes finding stories that aren’t well-known, or are well-known and have aspects that are underappreciated, and telling them in a new light.”

A multiyear program at MIT Lincoln Laboratory to characterize how biological and chemical vapors and aerosols disperse through the New York City subway system is coming to a close. The program, part of the U.S. Department of Homeland Security (DHS) Science and Technology Directorate's Urban Area Security Initiative, builds on other efforts at Lincoln Laboratory to detect chemical and biological threats, validate air dispersion models, and improve emergency protocols in urban areas in case of an airborne attack. The results of this program will inform the New York Metropolitan Transportation Authority (MTA) on how best to install an efficient, cost-effective system for airborne threat detection and mitigation throughout the subway. On a broader scale, the study will help the national security community understand pragmatic chemical and biological defense options for mass transit, critical facilities, and special events.

Trina Vian from the laboratory's Counter–Weapons of Mass Destruction (WMD) Systems Group led this project, which she says had as much to do with air flow and sensors as it did with MTA protocols and NYC commuters. "There are real dangers associated with panic during an alarm. People can get hurt during mass evacuation, or lose trust in a system and the authorities that administer that system, if there are false alarms," she says. "A novel aspect of our project was to investigate effective low-regret response options, meaning those with little operational consequence to responding to a false alarm."

Currently, depending on the severity of the alarm, the MTA's response can include stopping service and evacuating passengers and employees.

A complex environment for testing

For the program, which started in 2019, Vian and her team collected data on how chemical and biological sensors performed in the subway, what factors affected sensor accuracy, and how different mitigation protocols fared in stopping an airborne threat from spreading and removing the threat from a contaminated location. For their tests, they released batches of a safe, custom-developed aerosol simulant within Grand Central Station that they could track with DNA barcodes. Each batch had a different barcode, which allowed the team to differentiate among them and quantitatively assess different combinations of mitigation strategies.

To control and isolate air flow, the team tested static air curtains as well as air filtration systems. They also tested a spray knockdown system developed by Sandia National Laboratories designed to reduce and isolate particulate hazards in large volume areas. The system sprays a fine water mist into the tunnels that attaches to threat particulates and uses gravity to rain out the threat material. The spray contains droplets of a particular size and concentration, and with an applied electrostatic field. The original idea for the system was adapted from the coal mining industry, which used liquid sprayers to reduce the amount of inhalable soot.

The tests were done in a busy environment, and the team was required to complete trainings on MTA protocols such as track safety and how to interact with the public.

"We had long and sometimes very dirty days," says Jason Han of the Counter–WMD Systems Group, who collected measurements in the tunnels and analyzed the data. "We all wore bright orange contractor safety vests, which made people think we were official employees of the MTA. We would often get approached by people asking for directions!"

At times, issues such as power outages or database errors could disrupt data capture.

"We learned fairly early on that we had to capture daily data backups and keep a daily evolving master list of unique sensor identifiers and locations," says fellow team member Cassie Smith. "We developed workflows and wrote scripts to help automate the process, which ensured successful sensor data capture and attribution."

The team also worked closely with the MTA to make sure their tests and data capture ran smoothly. "The MTA was great at helping us maintain the test bed, doing as much as they could in our physical absence," Vian says.

Calling on industry

Another crucial aspect of the program was to connect with the greater chemical and biological industrial community to solicit their sensors for testing. These partnerships reduced the cost for DHS to bring new sensing technologies into the project, and, in return, participants gained a testing and data collection opportunity within the challenging NYC subway environment.

The team ultimately fielded 16 different sensors, each with varying degrees of maturity, that operated through a range of methods, such as ultraviolet laser–induced fluorescence, polymerase chain reaction, and long-wave infrared spectrometry.

"The partners appreciated the unique data they got and the opportunity to work with the MTA and experience an environment and customer base that they may not have anticipated before," Vian says.

The team finished testing in 2024 and has delivered the final report to the DHS. The MTA will use the report to help expand their PROTECT chemical detection system (originally developed by Argonne National Laboratory) from Grand Central Station into adjacent stations. They expect to complete this work in 2026.

"The value of this program cannot be overstated. This partnership with DHS and MIT Lincoln Laboratory has led to the identification of the best-suited systems for the MTA’s unique operating environment," says Michael Gemelli, director of chemical, biological, radiological, and nuclear/WMD detection and mitigation at the New York MTA.

"Other transit authorities can leverage these results to start building effective chemical and biological defense systems for their own specific spaces and threat priorities," adds Benjamin Ervin, leader of Lincoln Laboratory's Counter–WMD Systems Group. "Specific test and evaluation within the operational environment of interest, however, is always recommended to ensure defense system objectives are met."

Building these types of decision-making reports for airborne chemical and biological sensing has been a part of Lincoln Laboratory's mission since the mid-1990s. The laboratory also helped to define priorities in the field when DHS was forming in the early 2000s.

Beyond this study, the Lincoln Laboratory is leading several other projects focused on forecasting the impact of novel chemical and biological threats within multiple domains — military, space, agriculture, health, etc. — and on prototyping rapid, autonomous, high-confidence biological identification capabilities for the homeland to provide actionable evidence of hazardous environments.

From toddlers’ timeouts to criminals’ prison sentences, punishment reinforces social norms, making it known that an offender has done something unacceptable. At least, that is usually the intent — but the strategy can backfire. When a punishment is perceived as too harsh, observers can be left with the impression that an authority figure is motivated by something other than justice.

It can be hard to predict what people will take away from a particular punishment, because everyone makes their own inferences not just about the acceptability of the act that led to the punishment, but also the legitimacy of the authority who imposed it. A new computational model developed by scientists at MIT’s McGovern Institute for Brain Research makes sense of these complicated cognitive processes, recreating the ways people learn from punishment and revealing how their reasoning is shaped by their prior beliefs.

Their work, reported Aug. 4 in the journal PNAS, explains how a single punishment can send different messages to different people, and even strengthen the opposing viewpoints of groups who hold different opinions about authorities or social norms.

“The key intuition in this model is the fact that you have to be evaluating simultaneously both the norm to be learned and the authority who’s punishing,” says McGovern investigator and John W. Jarve Professor of Brain and Cognitive Sciences Rebecca Saxe, who led the research. “One really important consequence of that is even where nobody disagrees about the facts — everybody knows what action happened, who punished it, and what they did to punish it — different observers of the same situation could come to different conclusions.”

For example, she says, a child who is sent to timeout after biting a sibling might interpret the event differently than the parent. One might see the punishment as proportional and important, teaching the child not to bite. But if the biting, to the toddler, seemed a reasonable tactic in the midst of a squabble, the punishment might be seen as unfair, and the lesson will be lost.

People draw on their own knowledge and opinions when they evaluate these situations — but to study how the brain interprets punishment, Saxe and graduate student Setayesh Radkani wanted to take those personal ideas out of the equation. They needed a clear understanding of the beliefs that people held when they observed a punishment, so they could learn how different kinds of information altered their perceptions. So Radkani set up scenarios in imaginary villages where authorities punished individuals for actions that had no obvious analog in the real world.

Participants observed these scenarios in a series of experiments, with different information offered in each one. In some cases, for example, participants were told that the person being punished was either an ally or a competitor of the authority, whereas in other cases, the authority’s possible bias was left ambiguous.

“That gives us a really controlled setup to vary prior beliefs,” Radkani explains. “We could ask what people learn from observing punitive decisions with different severities, in response to acts that vary in their level of wrongness, by authorities that vary in their level of different motives.”

For each scenario, participants were asked to evaluate four factors: how much the authority figure cared about justice; the selfishness of the authority; the authority’s bias for or against the individual being punished; and the wrongness of the punished act. The research team asked these questions when participants were first introduced to the hypothetical society, then tracked how their responses changed after they observed the punishment. Across the scenarios, participants’ initial beliefs about the authority and the wrongness of the act shaped the extent to which those beliefs shifted after they observed the punishment.

Radkani was able to replicate these nuanced interpretations using a cognitive model framed around an idea that Saxe’s team has long used to think about how people interpret the actions of others. That is, to make inferences about others’ intentions and beliefs, we assume that people choose actions that they expect will help them achieve their goals.

To apply that concept to the punishment scenarios, Radkani developed a model that evaluates the meaning of a punishment (an action aimed at achieving a goal of the authority) by considering the harm associated with that punishment; its costs or benefits to the authority; and its proportionality to the violation. By assessing these factors, along with prior beliefs about the authority and the punished act, the model was able to predict people’s responses to the hypothetical punishment scenarios, supporting the idea that people use a similar mental model. “You need to have them consider those things, or you can’t make sense of how people understand punishment when they observe it,” Saxe says.

Even though the team designed their experiments to preclude preconceived ideas about the people and actions in their imaginary villages, not everyone drew the same conclusions from the punishments they observed. Saxe’s group found that participants’ general attitudes toward authority influenced their interpretation of events. Those with more authoritarian attitudes — assessed through a standard survey — tended to judge punished acts as more wrong and authorities as more motivated by justice than other observers.

“If we differ from other people, there’s a knee-jerk tendency to say, ‘either they have different evidence from us, or they’re crazy,’” Saxe says. Instead, she says, “It’s part of the way humans think about each other’s actions.”

“When a group of people who start out with different prior beliefs get shared evidence, they will not end up necessarily with shared beliefs. That’s true even if everybody is behaving rationally,” says Saxe.

This way of thinking also means that the same action can simultaneously strengthen opposing viewpoints. The Saxe lab’s modeling and experiments showed that when those viewpoints shape individuals’ interpretations of future punishments, the groups’ opinions will continue to diverge. For instance, a punishment that seems too harsh to a group who suspects an authority is biased can make that group even more skeptical of the authority’s future actions. Meanwhile, people who see the same punishment as fair and the authority as just will be more likely to conclude that the authority figure’s future actions are also just. 

“You will get a vicious cycle of polarization, staying and actually spreading to new things,” says Radkani.

The researchers say their findings point toward strategies for communicating social norms through punishment. “It is exactly sensible in our model to do everything you can to make your action look like it’s coming out of a place of care for the long-term outcome of this individual, and that it’s proportional to the norm violation they did,” Saxe says. “That is your best shot at getting a punishment interpreted pedagogically, rather than as evidence that you’re a bully.”

Nevertheless, she says that won’t always be enough. “If the beliefs are strong the other way, it’s very hard to punish and still sustain a belief that you were motivated by justice.”

Joining Saxe and Radkani on the paper is Joshua Tenenbaum, MIT professor of brain and cognitive sciences. The study was funded, in part, by the Patrick J McGovern Foundation.

The U.S. Food and Drug Administration’s recent approval of the first CRISPR-Cas9–based gene therapy has marked a major milestone in biomedicine, validating genome editing as a promising treatment strategy for disorders like sickle cell disease, muscular dystrophy, and certain cancers.

CRISPR-Cas9, often likened to “molecular scissors,” allows scientists to cut DNA at targeted sites to snip, repair, or replace genes. But despite its power, Cas9 poses a critical safety risk: The active enzyme can linger in cells and cause unintended DNA breaks — so-called off-target effects — which may trigger harmful mutations in healthy genes.

Now, researchers in the labs of Ronald T. Raines, MIT professor of chemistry, and Amit Choudhary, professor of medicine at Harvard Medical School, have engineered a precise way to turn Cas9 off after its job is done — significantly reducing off-target effects and improving the clinical safety of gene editing. Their findings are detailed in a new paper published in the Proceedings of the National Academy of Sciences (PNAS).

“To ‘turn off’ Cas9 after it achieves its intended genome-editing outcome, we developed the first cell-permeable anti-CRISPR protein system,” says Raines, the Roger and Georges Firmenich Professor of Natural Products Chemistry. “Our technology reduces the off-target activity of Cas9 and increases its genome-editing specificity and clinical utility.”

The new tool — called LFN-Acr/PA — uses a protein-based delivery system to ferry anti-CRISPR proteins into human cells rapidly and efficiently. While natural Type II anti-CRISPR proteins (Acrs) are known to inhibit Cas9, their use in therapy has been limited because they’re often too bulky or charged to enter cells, and conventional delivery methods are too slow or ineffective.

LFN-Acr/PA overcomes these hurdles using a component derived from anthrax toxin to introduce Acrs into cells within minutes. Even at picomolar concentrations, the system shuts down Cas9 activity with remarkable speed and precision — boosting genome-editing specificity up to 40 percent.

Bradley L. Pentelute, MIT professor of chemistry, is an expert on the anthrax delivery system, and is also an author of the paper.

The implications of this advance are wide-ranging. With patent applications filed, LFN-Acr/PA represents a faster, safer, and more controllable means of harnessing CRISPR-Cas9, opening the door to more-refined gene therapies with fewer unintended consequences.

The research was supported by the National Institutes of Health and a Gilliam Fellowship from the Howard Hughes Medical Institute awarded to lead author Axel O. Vera, a graduate student in the Department of Chemistry.

Materials research thrives across MIT, spanning disciplines and departments. Recent breakthroughs include strategies for securing sustainable supplies of nickel — critical to clean-energy technologies (Department of Materials Science and Engineering); the discovery of unexpected magnetism in atomically thin quantum materials (Department of Physics); and the development of adhesive coatings that reduce scarring around medical implants (departments of Mechanical Engineering and Civil and Environmental Engineering).

Beyond individual projects, the MIT Materials Research Laboratory (MRL) fosters broad collaboration through strategic initiatives such as the Materials Systems Laboratory and SHINE (Sustainability and Health Initiative for Net Positive Enterprise). These efforts bring together academia, government, and industry to accelerate innovation in sustainability, energy use, and advanced materials.

MRL, a hub that connects and supports the Institute’s materials research community, is at the center of these efforts. “MRL serves as a home for the entire materials research community at MIT,” says C. Cem Tasan, the POSCO Associate Professor of Metallurgy in the Department of Materials Science and Engineering who became MRL director in April. “Our goal is to make it easier for our faculty to conduct their extraordinary research.”

A storied history

Established in 2017, the MRL brings together more than 30 researchers and builds on a 48-year legacy of innovation. It was formed through the merger of the MIT Materials Processing Center (MPC) and the Center for Materials Science and Engineering (CMSE), two institutions that helped lay the foundation for MIT’s global leadership in materials science.

Over the years, research supported by MPC and CMSE has led to transformative technologies and successful spinout companies. Notable examples include amsc, based on advances in superconductivity; OmniGuide, which developed cutting-edge optical fiber technologies; and QD Vision, a pioneer in quantum dot technology acquired by Samsung in 2016. Another landmark achievement was the development of the first germanium laser to operate at room temperature — a breakthrough now used in optical communications.

Enabling research through partnership and support

MRL is launching targeted initiatives to connect MIT researchers with industry partners around specific technical challenges. Each initiative will be led by a junior faculty member working closely with MRL to identify a problem that aligns with their research expertise and is relevant to industry needs.

Through multi-year collaborations with participating companies, faculty can explore early-stage solutions in partnership with postdocs or graduate students. These initiatives are designed to be agile and interdisciplinary, with the potential to grow into major, long-term research programs.

Behind-the-scenes support, front-line impact

MRL provides critical infrastructure that enables faculty to focus on discovery, not logistics. “MRL works silently in the background, where every problem a principal investigator has related to the administration of materials research is solved with efficiency, good organization, and minimum effort,” says Tasan.

This quiet but powerful support spans multiple areas:

• The finance team manages grants and helps secure new funding opportunities.
• The human resources team supports the hiring of postdocs.
• The communications team amplifies the lab’s impact through compelling stories shared with the public and funding agencies.
• The events team plans and coordinates conferences, seminars, and symposia that foster collaboration within the MIT community and with external partners.

Together, these functions ensure that research at MRL runs smoothly and effectively — from initial idea to lasting innovation.

Leadership with a vision

Tasan, who also leads a research group focused on metallurgy, says he took on the directorship because “I thrive on new challenges.” He also saw the role as an opportunity to contribute more broadly to MIT. 

“I believe MRL can play an even greater role in advancing materials research across the Institute, and I’m excited to help make that happen,” he says.

Recent MRL initiatives

MRL has supported a wide range of research programs in partnership with major industry leaders, including Apple, Ford, Microsoft,  Rio Tinto, IBM, Samsung, and Texas Instruments, as well as organizations such as Advanced Functional Fabrics of America, Allegheny Technologies, Ericsson, and the Semiconductor Research Corp.

MRL researchers are addressing critical global challenges in energy efficiency, environmental sustainability, and the development of next-generation material systems.

• Professor Antoine Allanore is advancing a direct process for wire production from sulfide concentrates, offering a more efficient and sustainable alternative to traditional methods.
• Professor Joe Checkelsky is leading pioneering research on scalable, high-temperature quantum materials, in the realm of quantum transport.
• Professor Pablo Jarillo-Herrero is making significant progress with two-dimensional materials and their heterostructures.
• Professor Nuh Gedik explores ultrafast electronic and structural dynamics and light-matter interactions.
• Professor Gregory Rutledge spearheaded a National Institute of Standards and Technology Rapid Assistance for Coronavirus Economic Response (NIST RACER)-sponsored initiative to develop biodegradable nanofiber-based personal protective equipment, aimed at improving manufacturing automation, diversifying supply chains, and reducing environmental impact.
• Professor Elsa Olivetti serves as the lead principal investigator at MIT for REMADE: the Institute for Reducing Embodied-energy and Decreasing Emissions. Her research on fiber recovery and post-consumer resin processing directly supports REMADE’s mission to enhance material circularity and reduce energy use by 50 percent by 2027.
• Randy Kirchain is modeling metals markets under decarbonization, and developing greener construction materials.
• Anu Agarwal is spearheading efforts to build a sustainable microchip manufacturing ecosystem. 

Optical frequency combs are specially designed lasers that act like rulers to accurately and rapidly measure specific frequencies of light. They can be used to detect and identify chemicals and pollutants with extremely high precision.

Frequency combs would be ideal for remote sensors or portable spectrometers because they can enable accurate, real-time monitoring of multiple chemicals without complex moving parts or external equipment.

But developing frequency combs with high enough bandwidth for these applications has been a challenge. Often, researchers must add bulky components that limit scalability and performance.

Now, a team of MIT researchers has demonstrated a compact, fully integrated device that uses a carefully crafted mirror to generate a stable frequency comb with very broad bandwidth. The mirror they developed, along with an on-chip measurement platform, offers the scalability and flexibility needed for mass-producible remote sensors and portable spectrometers. This development could enable more accurate environmental monitors that can identify multiple harmful chemicals from trace gases in the atmosphere.

“The broader the bandwidth a spectrometer has, the more powerful it is, but dispersion is in the way. Here we took the hardest problem that limits bandwidth and made it the centerpiece of our study, addressing every step to ensure robust frequency comb operation,” says Qing Hu, Distinguished Professor in Electrical Engineering and Computer Science at MIT, principal investigator in the Research Laboratory of Electronics, and senior author on an open-access paper describing the work.

He is joined on the paper by lead author Tianyi Zeng PhD ’23; as well as Yamac Dikmelik of General Dynamics Mission Systems; Feng Xie and Kevin Lascola of Thorlabs Quantum Electronics; and David Burghoff SM ’09, PhD ’14, an assistant professor at the University of Texas at Austin. The research appears today in Light: Science and Applications.

Broadband combs

An optical frequency comb produces a spectrum of equally spaced laser lines, which resemble the teeth of a comb.

Scientists can generate frequency combs using several types of lasers for different wavelengths. By using a laser that produces long wave infrared radiation, such as a quantum cascade laser, they can use frequency combs for high-resolution sensing and spectroscopy.

In dual-comb spectroscopy (DCS), the beam of one frequency comb travels straight through the system and strikes a detector at the other end. The beam of the second frequency comb passes through a chemical sample before striking the same detector. Using the results from both combs, scientists can faithfully replicate the chemical features of the sample at much lower frequencies, where signals can be easily analyzed.

The frequency combs must have high bandwidth, or they will only be able to detect a small frequency range of chemical compounds, which could lead to false alarms or inaccurate results.

Dispersion is the most important factor that limits a frequency comb’s bandwidth. If there is dispersion, the laser lines are not evenly spaced, which is incompatible with the formation of frequency combs.

“With long wave infrared radiation, the dispersion will be very high. There is no way to get around it, so we have to find a way to compensate for it or counteract it by engineering our system,” Hu says.

Many existing approaches aren’t flexible enough to be used in different scenarios or don’t enable high enough bandwidth.

Hu’s group previously solved this problem in a different type of frequency comb, one that used terahertz waves, by developing a double-chirped mirror (DCM).

A DCM is a special type of optical mirror that has multiple layers with thicknesses that change gradually from one end to the other. They found that this DCM, which has a corrugated structure, could effectively compensate for dispersion when used with a terahertz laser.

“We tried to borrow this trick and apply it to an infrared comb, but we ran into lots of challenges,” Hu says.

Because infrared waves are 10 times shorter than terahertz waves, fabricating the new mirror required an extreme level of precision. At the same time, they needed to coat the entire DCM in a thick layer of gold to remove the heat under laser operation. Plus, their dispersion measurement system, designed for terahertz waves, wouldn’t work with infrared waves, which have frequencies that are about 10 times higher than terahertz.

“After more than two years of trying to implement this scheme, we reached a dead end,” Hu says.

A new solution

Ready to throw in the towel, the team realized something they had missed. They had designed the mirror with corrugation to compensate for the lossy terahertz laser, but infrared radiation sources aren’t as lossy.

This meant they could use a standard DCM design to compensate for dispersion, which is compatible with infrared radiation. However, they still needed to create curved mirror layers to capture the beam of the laser, which made fabrication much more difficult than usual.

“The adjacent layers of mirror differ only by tens of nanometers. That level of precision precludes standard photolithography techniques. On top of that, we still had to etch very deeply into the notoriously stubborn material stacks. Achieving those critical dimensions and etch depths was key to unlocking broadband comb performance,” Zeng says. In addition to precisely fabricating the DCM, they integrated the mirror directly onto the laser, making the device extremely compact. The team also developed a high-resolution, on-chip dispersion measurement platform that doesn’t require bulky external equipment.

“Our approach is flexible. As long as we can use our platform to measure the dispersion, we can design and fabricate a DCM that compensates for it,” Hu adds.

Taken together, the DCM and on-chip measurement platform enabled the team to generate stable infrared laser frequency combs that had far greater bandwidth than can usually be achieved without a DCM.

In the future, the researchers want to extend their approach to other laser platforms that could generate combs with even greater bandwidth and higher power for more demanding applications.

“These researchers developed an ingenious nanophotonic dispersion compensation scheme based on an integrated air–dielectric double-chirped mirror. This approach provides unprecedented control over dispersion, enabling broadband comb formation at room temperature in the long-wave infrared. Their work opens the door to practical, chip-scale frequency combs for applications ranging from chemical sensing to free-space communications,” says Jacob B. Khurgin, a professor at the Johns Hopkins University Whiting School of Engineering, who was not involved with this paper.

This work is funded, in part, by the U.S. Defense Advanced Research Projects Agency (DARPA) and the Gordon and Betty Moore Foundation.