A home robot trained to perform household tasks in a factory may fail to effectively scrub the sink or take out the trash when deployed in a user’s kitchen, since this new environment differs from its training space.

To avoid this, engineers often try to match the simulated training environment as closely as possible with the real world where the agent will be deployed.

However, researchers from MIT and elsewhere have now found that, despite this conventional wisdom, sometimes training in a completely different environment yields a better-performing artificial intelligence agent.

Their results indicate that, in some situations, training a simulated AI agent in a world with less uncertainty, or “noise,” enabled it to perform better than a competing AI agent trained in the same, noisy world they used to test both agents.

The researchers call this unexpected phenomenon the indoor training effect.

“If we learn to play tennis in an indoor environment where there is no noise, we might be able to more easily master different shots. Then, if we move to a noisier environment, like a windy tennis court, we could have a higher probability of playing tennis well than if we started learning in the windy environment,” explains Serena Bono, a research assistant in the MIT Media Lab and lead author of a paper on the indoor training effect.

The researchers studied this phenomenon by training AI agents to play Atari games, which they modified by adding some unpredictability. They were surprised to find that the indoor training effect consistently occurred across Atari games and game variations.

They hope these results fuel additional research toward developing better training methods for AI agents.

“This is an entirely new axis to think about. Rather than trying to match the training and testing environments, we may be able to construct simulated environments where an AI agent learns even better,” adds co-author Spandan Madan, a graduate student at Harvard University.

Bono and Madan are joined on the paper by Ishaan Grover, an MIT graduate student; Mao Yasueda, a graduate student at Yale University; Cynthia Breazeal, professor of media arts and sciences and leader of the Personal Robotics Group in the MIT Media Lab; Hanspeter Pfister, the An Wang Professor of Computer Science at Harvard; and Gabriel Kreiman, a professor at Harvard Medical School. The research will be presented at the Association for the Advancement of Artificial Intelligence Conference.

Training troubles

The researchers set out to explore why reinforcement learning agents tend to have such dismal performance when tested on environments that differ from their training space.

Reinforcement learning is a trial-and-error method in which the agent explores a training space and learns to take actions that maximize its reward.

The team developed a technique to explicitly add a certain amount of noise to one element of the reinforcement learning problem called the transition function. The transition function defines the probability an agent will move from one state to another, based on the action it chooses.

If the agent is playing Pac-Man, a transition function might define the probability that ghosts on the game board will move up, down, left, or right. In standard reinforcement learning, the AI would be trained and tested using the same transition function.

The researchers added noise to the transition function with this conventional approach and, as expected, it hurt the agent’s Pac-Man performance.

But when the researchers trained the agent with a noise-free Pac-Man game, then tested it in an environment where they injected noise into the transition function, it performed better than an agent trained on the noisy game.

“The rule of thumb is that you should try to capture the deployment condition’s transition function as well as you can during training to get the most bang for your buck. We really tested this insight to death because we couldn’t believe it ourselves,” Madan says.

Injecting varying amounts of noise into the transition function let the researchers test many environments, but it didn’t create realistic games. The more noise they injected into Pac-Man, the more likely ghosts would randomly teleport to different squares.

To see if the indoor training effect occurred in normal Pac-Man games, they adjusted underlying probabilities so ghosts moved normally but were more likely to move up and down, rather than left and right. AI agents trained in noise-free environments still performed better in these realistic games.

“It was not only due to the way we added noise to create ad hoc environments. This seems to be a property of the reinforcement learning problem. And that was even more surprising to see,” Bono says.

Exploration explanations

When the researchers dug deeper in search of an explanation, they saw some correlations in how the AI agents explore the training space.

When both AI agents explore mostly the same areas, the agent trained in the non-noisy environment performs better, perhaps because it is easier for the agent to learn the rules of the game without the interference of noise.

If their exploration patterns are different, then the agent trained in the noisy environment tends to perform better. This might occur because the agent needs to understand patterns it can’t learn in the noise-free environment.

“If I only learn to play tennis with my forehand in the non-noisy environment, but then in the noisy one I have to also play with my backhand, I won’t play as well in the non-noisy environment,” Bono explains.

In the future, the researchers hope to explore how the indoor training effect might occur in more complex reinforcement learning environments, or with other techniques like computer vision and natural language processing. They also want to build training environments designed to leverage the indoor training effect, which could help AI agents perform better in uncertain environments.

In 2014, a team of MIT students in course 15.366 (Climate and Energy Ventures) developed a plan to commercialize MIT research on how to move information between chips with light instead of electricity, reducing energy usage.

After completing the class, which challenges students to identify early customers and pitch their business plan to investors, the team went on to win both grand prizes at the MIT Clean Energy Prize. Today the company, Ayar Labs, has raised a total of $370 million from a group including chip leaders AMD, Intel, and NVIDIA, to scale the manufacturing of its optical chip interconnects.

Ayar Labs is one of many companies whose roots can be traced back to 15.366. In fact, more than 150 companies have been founded by alumni of the class since its founding in 2007.

In the class, student teams select a technology or idea and determine the best path for its commercialization. The semester-long project, which is accompanied by lectures and mentoring, equips students with real-world experience in launching a business.

“The goal is to educate entrepreneurs on how to start companies in the climate and energy space,” says Senior Lecturer Tod Hynes, who co-founded the course and has been teaching since 2008. “We do that through hands-on experience. We require students to engage with customers, talk to potential suppliers, partners, investors, and to practice their pitches to learn from that feedback.”

The class attracts hundreds of student applications each year. As one of the catalysts for MIT spinoffs, it is also one reason a 2015 report found that MIT alumni-founded companies had generated roughly $1.9 trillion in annual revenues. If MIT were a country, that figure that would make it the 10th largest economy in the world, according to the report.

“’Mens et manus’ (‘mind and hand’) is MIT's motto, and the hands-on experience we try to provide in this class is hard to beat,” Hynes says. “When you actually go through the process of commercialization in the real world, you learn more and you’re in a better spot. That experiential learning approach really aligns with MIT’s approach.”

Simulating a startup

The course was started by Bill Aulet, a professor of the practice at the MIT Sloan School of Management and the managing director of the Martin Trust Center for MIT Entrepreneurship. After serving as an advisor the first year and helping Aulet launch the class, Hynes began teaching the class with Aulet in the fall of 2008. The pair also launched the Climate and Energy Prize around the same time, which continues today and recently received over 150 applications from teams from around the world.

A core feature of the class is connecting students in different academic fields. Each year, organizers aim to enroll students with backgrounds in science, engineering, business, and policy.

“The class is meant to be accessible to anybody at MIT,” Hynes says, noting the course has also since opened to students from Harvard University. “We’re trying to pull across disciplines.”

The class quickly grew in popularity around campus. Over the last few years, the course has had about 150 students apply for 50 spots.

“I mentioned Climate and Energy Ventures in my application to MIT,” says Chris Johnson, a second-year graduate student in the Leaders for Global Operations (LGO) Program. “Coming into MIT, I was very interested in sustainability, and energy in particular, and also in startups. I had heard great things about the class, and I waited until my last semester to apply.”

The course’s organizers select mostly graduate students, whom they prefer to be in the final year of their program so they can more easily continue working on the venture after the class is finished.

“Whether or not students stick with the project from the class, it’s a great experience that will serve them in their careers,” says Jennifer Turliuk, the practice leader for climate and energy artificial intelligence at the Martin Trust Center for Entrepreneurship, who helped teach the class this fall.

Hynes describes the course as a venture-building simulation. Before it begins, organizers select up to 30 technologies and ideas that are in the right stage for commercialization. Students can also come into the class with ideas or technologies they want to work on.

After a few weeks of introductions and lectures, students form into multidisciplinary teams of about five and begin going through each of the 24 steps of building a startup described in Aulet’s book “Disciplined Entrepreneurship,” which includes things like engaging with potential early customers, quantifying a value proposition, and establishing a business model. Everything builds toward a one-hour final presentation that’s designed to simulate a pitch to investors or government officials.

“It’s a lot of work, and because it’s a team-based project, your grade is highly dependent on your team,” Hynes says. “You also get graded by your team; that’s about 10 percent of your grade. We try to encourage people to be proactive and supportive teammates.”

Students say the process is fast-paced but rewarding.

“It’s definitely demanding,” says Sofie Netteberg, a graduate student who is also in the LGO program at MIT. “Depending on where you’re at with your technology, you can be moving very quickly. That’s the stage that I was in, which I found really engaging. We basically just had a lab technology, and it was like, ‘What do we do next?’ You also get a ton of support from the professors.”

From the classroom to the world

This fall’s final presentations took place at the headquarters of the MIT-affiliated venture firm The Engine in front of an audience of professors, investors, members of foundations supporting entrepreneurship, and more.

“We got to hear feedback from people who would be the real next step for the technology if the startup gets up and running,” said Johnson, whose team was commercializing a method for storing energy in concrete. “That was really valuable. We know that these are not only people we might see in the next month or the next funding rounds, but they’re also exactly the type of people that are going to give us the questions we should be thinking about. It was clarifying.”

Throughout the semester, students treated the project like a real venture they’d be working on well beyond the length of the class.

“No one’s really thinking about this class for the grade; it’s about the learning,” says Netteberg, whose team was encouraged to keep working on their electrolyzer technology designed to more efficiently produce green hydrogen. “We’re not stressed about getting an A. If we want to keep working on this, we want real feedback: What do you think we did well? What do we need to keep working on?”

Hynes says several investors expressed interest in supporting the businesses coming out of the class. Moving forward, he hopes students embrace the test-bed environment his team has created for them and try bold new things.

“People have been very pragmatic over the years, which is good, but also potentially limiting,” Hynes says. “This is also an opportunity to do something that’s a little further out there — something that has really big potential impact if it comes together. This is the time where students get to experiment, so why not try something big?”

Robots have come a long way since the Roomba. Today, drones are starting to deliver door to door, self-driving cars are navigating some roads, robo-dogs are aiding first responders, and still more bots are doing backflips and helping out on the factory floor. Still, Luca Carlone thinks the best is yet to come.

Carlone, who recently received tenure as an associate professor in MIT’s Department of Aeronautics and Astronautics (AeroAstro), directs the SPARK Lab, where he and his students are bridging a key gap between humans and robots: perception. The group does theoretical and experimental research, all toward expanding a robot’s awareness of its environment in ways that approach human perception. And perception, as Carlone often says, is more than detection.

While robots have grown by leaps and bounds in terms of their ability to detect and identify objects in their surroundings, they still have a lot to learn when it comes to making higher-level sense of their environment. As humans, we perceive objects with an intuitive sense of not just of their shapes and labels but also their physics — how they might be manipulated and moved — and how they relate to each other, their larger environment, and ourselves.

That kind of human-level perception is what Carlone and his group are hoping to impart to robots, in ways that enable them to safely and seamlessly interact with people in their homes, workplaces, and other unstructured environments.

Since joining the MIT faculty in 2017, Carlone has led his team in developing and applying perception and scene-understanding algorithms for various applications, including autonomous underground search-and-rescue vehicles, drones that can pick up and manipulate objects on the fly, and self-driving cars. They might also be useful for domestic robots that follow natural language commands and potentially even anticipate human’s needs based on higher-level contextual clues.

“Perception is a big bottleneck toward getting robots to help us in the real world,” Carlone says. “If we can add elements of cognition and reasoning to robot perception, I believe they can do a lot of good.”

Expanding horizons

Carlone was born and raised near Salerno, Italy, close to the scenic Amalfi coast, where he was the youngest of three boys. His mother is a retired elementary school teacher who taught math, and his father is a retired history professor and publisher, who has always taken an analytical approach to his historical research. The brothers may have unconsciously adopted their parents’ mindsets, as all three went on to be engineers — the older two pursued electronics and mechanical engineering, while Carlone landed on robotics, or mechatronics, as it was known at the time.

He didn’t come around to the field, however, until late in his undergraduate studies. Carlone attended the Polytechnic University of Turin, where he focused initially on theoretical work, specifically on control theory — a field that applies mathematics to develop algorithms that automatically control the behavior of physical systems, such as power grids, planes, cars, and robots. Then, in his senior year, Carlone signed up for a course on robotics that explored advances in manipulation and how robots can be programmed to move and function.

“It was love at first sight. Using algorithms and math to develop the brain of a robot and make it move and interact with the environment is one of the most fulfilling experiences,” Carlone says. “I immediately decided this is what I want to do in life.”

He went on to a dual-degree program at the Polytechnic University of Turin and the Polytechnic University of Milan, where he received master’s degrees in mechatronics and automation engineering, respectively. As part of this program, called the Alta Scuola Politecnica, Carlone also took courses in management, in which he and students from various academic backgrounds had to team up to conceptualize, build, and draw up a marketing pitch for a new product design. Carlone’s team developed a touch-free table lamp designed to follow a user’s hand-driven commands. The project pushed him to think about engineering from different perspectives.

“It was like having to speak different languages,” he says. “It was an early exposure to the need to look beyond the engineering bubble and think about how to create technical work that can impact the real world.”

The next generation

Carlone stayed in Turin to complete his PhD in mechatronics. During that time, he was given freedom to choose a thesis topic, which he went about, as he recalls, “a bit naively.”

“I was exploring a topic that the community considered to be well-understood, and for which many researchers believed there was nothing more to say.” Carlone says. “I underestimated how established the topic was, and thought I could still contribute something new to it, and I was lucky enough to just do that.”

The topic in question was “simultaneous localization and mapping,” or SLAM — the problem of generating and updating a map of a robot’s environment while simultaneously keeping track of where the robot is within that environment. Carlone came up with a way to reframe the problem, such that algorithms could generate more precise maps without having to start with an initial guess, as most SLAM methods did at the time. His work helped to crack open a field where most roboticists thought one could not do better than the existing algorithms.

“SLAM is about figuring out the geometry of things and how a robot moves among those things,” Carlone says. “Now I’m part of a community asking, what is the next generation of SLAM?”

In search of an answer, he accepted a postdoc position at Georgia Tech, where he dove into coding and computer vision — a field that, in retrospect, may have been inspired by a brush with blindness: As he was finishing up his PhD in Italy, he suffered a medical complication that severely affected his vision.

“For one year, I could have easily lost an eye,” Carlone says. “That was something that got me thinking about the importance of vision, and artificial vision.”

He was able to receive good medical care, and the condition resolved entirely, such that he could continue his work. At Georgia Tech, his advisor, Frank Dellaert, showed him ways to code in computer vision and formulate elegant mathematical representations of complex, three-dimensional problems. His advisor was also one of the first to develop an open-source SLAM library, called GTSAM, which Carlone quickly recognized to be an invaluable resource. More broadly, he saw that making software available to all unlocked a huge potential for progress in robotics as a whole.

“Historically, progress in SLAM has been very slow, because people kept their codes proprietary, and each group had to essentially start from scratch,” Carlone says. “Then open-source pipelines started popping up, and that was a game changer, which has largely driven the progress we have seen over the last 10 years.”

Spatial AI

Following Georgia Tech, Carlone came to MIT in 2015 as a postdoc in the Laboratory for Information and Decision Systems (LIDS). During that time, he collaborated with Sertac Karaman, professor of aeronautics and astronautics, in developing software to help palm-sized drones navigate their surroundings using very little on-board power. A year later, he was promoted to research scientist, and then in 2017, Carlone accepted a faculty position in AeroAstro.

“One thing I fell in love with at MIT was that all decisions are driven by questions like: What are our values? What is our mission? It’s never about low-level gains. The motivation is really about how to improve society,” Carlone says. “As a mindset, that has been very refreshing.”

Today, Carlone’s group is developing ways to represent a robot’s surroundings, beyond characterizing their geometric shape and semantics. He is utilizing deep learning and large language models to develop algorithms that enable robots to perceive their environment through a higher-level lens, so to speak. Over the last six years, his lab has released more than 60 open-source repositories, which are used by thousands of researchers and practitioners worldwide. The bulk of his work fits into a larger, emerging field known as “spatial AI.”

“Spatial AI is like SLAM on steroids,” Carlone says. “In a nutshell, it has to do with enabling robots to think and understand the world as humans do, in ways that can be useful.”

It’s a huge undertaking that could have wide-ranging impacts, in terms of enabling more intuitive, interactive robots to help out at home, in the workplace, on the roads, and in remote and potentially dangerous areas. Carlone says there will be plenty of work ahead, in order to come close to how humans perceive the world.

“I have 2-year-old twin daughters, and I see them manipulating objects, carrying 10 different toys at a time, navigating across cluttered rooms with ease, and quickly adapting to new environments. Robot perception cannot yet match what a toddler can do,” Carlone says. “But we have new tools in the arsenal. And the future is bright.”

The MIT Press has announced that Direct to Open (D2O) will open access to over 80 new monographs and edited book collections in the spring and fall publishing seasons, after reaching its full funding goal for 2025.

“It has been one of the greatest privileges of my career to contribute to this program and demonstrate that our academic community can unite to publish high-quality open-access monographs at scale,” says Amy Harris, senior manager of library relations and sales at the MIT Press. “We are deeply grateful to all of the consortia that have partnered with us and to the hundreds of libraries that have invested in this program. Together, we are expanding the public knowledge commons in ways that benefit scholars, the academy, and readers around the world.”

Among the highlights from the MIT Press’s fourth D2O funding cycle is a new three-year, consortium-wide commitment from the Florida Virtual Campus (FLVC) and a renewed three-year commitment from the Big Ten Academic Alliance (BTAA). These long-term collaborations will play a pivotal role in supporting the press’s open-access efforts for years to come.

“The Florida Virtual Campus is honored to participate in D2O in order to provide this collection of high-quality scholarship to more than 1.2 million students and faculty at the 28 state colleges and 12 state universities of Florida,” says Elijah Scott, executive director of library services for the Florida Virtual Campus. “The D2O program allows FLVC to make this research collection available to our member libraries while concurrently fostering the larger global aspiration of sustainable and equitable access to information.”

“The libraries of the Big Ten Academic Alliance are committed to supporting the creation of open-access content,” adds Kate McCready, program director for open publishing at the Big Ten Academic Alliance Library. “We're thrilled that our participation in D2O contributes to the opening of this collection, as well as championing the exploration of new models for opening scholarly monographs.”

In 2025, hundreds of libraries renewed their support thanks to the teams at consortia around the world, including the Council of Australasian University Librarians, the CBB Library Consortium, the California Digital Library, the Canadian Research Knowledge Network, CRL/NERL, the Greater Western Library Alliance, Jisc, Lyrasis, MOBIUS, PALCI, SCELC, and the Tri-College Library Consortium.

Launched in 2021, D2O is an innovative sustainable framework for open-access monographs that shifts publishing from a solely market-based, purchase model where individuals and libraries buy single e-books, to a collaborative, library-supported open-access model. 

Many other models offer open-access opportunities on a title-by-title basis or within specific disciplines. D2O’s particular advantage is that it enables a press to provide open access to its entire list of scholarly books at scale, embargo-free, during each funding cycle. Thanks to D2O, all MIT Press monograph authors have the opportunity for their work to be published open access, with equal support to traditionally underserved and underfunded disciplines in the social sciences and humanities.  

The MIT Press will now turn its attention to its fifth funding cycle and invites libraries and library consortia to participate. For details, please visit the MIT Press website or contact the Library Relations team.

Melissa Smith PhD ’12 is an associate leader in the Advanced Materials and Microsystems Group at MIT Lincoln Laboratory. Her team, which is embedded within the laboratory’s Advanced Technology Division, drives innovation in fields including computation, aerospace, optical systems, and bioengineering by applying micro- and nanofabrication techniques. Smith, an inventor of 11 patents, strongly believes in the power of collaboration when it comes to her own work, the work of her Lincoln Laboratory colleagues, and the innovative research done by MIT professors and students. 

Lincoln Laboratory researches and develops advanced technologies in support of national security. Research done at the laboratory is applied, meaning staff members are given a specific problem to solve by a deadline. Divisions within the laboratory are made up of technical experts, ranging from biologists to cybersecurity researchers, working on different projects simultaneously. Smith appreciates the broad application space of her group’s work, which feeds into programs across the laboratory. “We are like a kitchen drawer full of indispensable gadgets,” she says, some of which are used to develop picosatellites, smart textiles, or microrobots. Their position as a catch-all team makes their work fun, somewhat open-ended, and always interesting.

In 2012, Smith received her PhD from the MIT Department of Materials Science & Engineering (DMSE). After graduation, she remained at the Institute for nine months as a postdoc before beginning her career as an engineer at IBM. While at IBM, Smith maintained a research affiliation with MIT to continue to work on patents and write papers. In 2015, she formally returned to MIT as a technical staff member at Lincoln Laboratory. In 2020, she was promoted to the position of assistant group leader and was awarded the laboratory’s Best Invention Award for “Electrospray devices and methods for fabricating electrospray devices” (U.S. Patent 11,708,182 B2). In 2024, she was promoted to associate group leader. 

Management is an important aspect of Smith’s role, and she credits the laboratory for cultivating people with both academic and technical backgrounds to learn how to effectively run programs and teams. Her demonstrated efficacy in the academic and corporate spaces — both of which contain deadlines and collaborative work — allows her to inspire her team to be innovative and efficient. She keeps her group running smoothly by removing potential roadblocks so they can adequately attend to their projects. Smith focuses on specific tasks that aid in her group’s success, including writing grant proposals, a skill she learned while working at the laboratory, which allows her staff to prioritize their technical work. That, she says, is the value of working as a team.

A true champion of teamwork, Smith advises new staff members to maintain an open mind because they can learn something from everyone they encounter, especially when first starting at the Institute. She notes that every colleague has something unique to offer, and taking time to understand the wealth of experience and knowledge around you will only help you succeed as a staff member at MIT. “Be who you are, do what you do, and run with it,” she says. 

Soundbytes 

Q: What project at MIT are you the proudest of?

Smith: We are building a wafer-scale satellite, which is a little bit out-there as an idea. It was thought up in the 1960s, but the technology wasn't to the point where it could be realized. Technology today is more than capable of making this small space microsystem. I was tasked with taking the idea further. Some people say that it is impossible, and for a lot of good reasons! Slowly addressing the technical issues to the point where people now say, “Oh, you could probably do this,” is exciting.

I never want to be someone who thinks something is impossible. I'll say, “I can't do it, but maybe somebody else can,” and I will also add, “Here is what I tried, here is all the data, and here is how I came to the point where I got stuck.” I like taking something that was initially met with disbelief and rendering it. Lincoln Laboratory is active with professors and students. I am collaborating with students from the Department of Aeronautics and Astronautics on the project, and we now have a patent on the technology that came from it. I am happy to have students assist, write papers, and occasionally get their names on patents. It is seeding additional innovation. We don't have the system quite yet, but I've converted a few skeptics!

Q: What are your favorite campus memories from when you were a student?

Smith: When I was a graduate student, I would go with friends to the Muddy Charles Pub in Walker Memorial. One of the things I really enjoy about Walker Memorial is the prime view over the Charles River, and I remember staring out of the windows at the top of Walker Memorial after exams. Also, during Independent Activities Period I learned how to snowboard. I'm from Illinois where there are no mountains. When I came to the East Coast and saw that there were a lot of mountains with people strapping metal to their feet in the snow, I thought, “OK, let's try it.” I love snowboarding to this day. MIT has this kind of unfettered freedom in a way that, even beyond the technical stuff, people can try things from a personal standpoint they maybe wouldn’t have tried somewhere else. 

Q: What do you like the most about the culture at MIT?

Smith: We help people grow professionally. The staff here are above average in terms of capability in what they do. When I interviewed for my job, I asked where people work when they leave MIT. People move on to other labs like the Jet Propulsion Laboratory or companies like Raytheon, they become professors, or they start their own companies. I make sure that people are learning what they want to do with their careers while they work at the laboratory. That is the cultural overlay that exists on campus. When I was a student, I interned at John Deere, 3M, Xerox, and IBM and saw how they are innovative in their own ways that define their corporate cultures. At MIT, you are supported to explore and play. At Lincoln Laboratory people are not pigeonholed into a particular role. If you have an idea, you are encouraged to explore it, as long as it aligns with the mission. There is a specific freedom you can experience at MIT that is above and beyond a typical academic environment.

Gerald E. Schneider, a professor emeritus of psychology and member of the MIT community for over 60 years, passed away on Dec. 11, 2024. He was 84.

Schneider was an authority on the relationships between brain structure and behavior, concentrating on neuronal development, regeneration or altered growth after brain injury, and the behavioral consequences of altered connections in the brain.

Using the Syrian golden hamster as his test subject of choice, Schneider made numerous contributions to the advancement of neuroscience. He laid out the concept of two visual systems — one for locating objects and one for the identification of objects — in a 1969 issue of Science, a milestone in the study of brain-behavior relationships. In 1973, he described a “pruning effect” in the optic tract axons of adult hamsters who had brain lesions early in life. In 2006, his lab reported a previously undiscovered nanobiomedical technology for tissue repair and restoration in Biological Sciences. The paper showed how a designed self-assembling peptide nanofiber scaffold could create a permissive environment for axons, not only to regenerate through the site of an acute injury in the optic tract of hamsters, but also to knit the brain tissue together.

His work shaped the research and thinking of numerous colleagues and trainees. Mriganka Sur, the Newton Professor of Neuroscience and former Department of Brain and Cognitive Sciences (BCS) department head, recalls how Schneider’s paper, “Is it really better to have your brain lesion early? A revision of the ‘Kennard Principle,’” published in 1979 in the journal Neuropsychologia, influenced his work on rewiring retinal projections to the auditory thalamus, which was used to derive principles of functional plasticity in the cortex.

“Jerry was an extremely innovative thinker. His hypothesis of two visual systems — for detailed spatial processing and for movement processing — based on his analysis of visual pathways in hamsters presaged and inspired later work on form and motion pathways in the primate brain,” Sur says. “His description of conservation of axonal arbor during development laid the foundation for later ideas about homeostatic mechanisms that co-regulate neuronal plasticity.”

Institute Professor Ann Graybiel was a colleague of Schneider’s for over five decades. She recalls early in her career being asked by Schneider to help make a map of the superior colliculus.

“I took it as an honor to be asked, and I worked very hard on this, with great excitement. It was my first such mapping, to be followed by much more in the future,” Graybiel recalls. “Jerry was fascinated by animal behavior, and from early on he made many discoveries using hamsters as his main animals of choice. He found that they could play. He found that they could operate in ways that seemed very sophisticated. And, yes, he mapped out pathways in their brains.”

Schneider was raised in Wheaton, Illinois, and graduated from Wheaton College in 1962 with a degree in physics. He was recruited to MIT by Hans-Lukas Teuber, one of the founders of the Department of Psychology, which eventually became the Department of Brain and Cognitive Sciences. Walle Nauta, another founder of the department, taught Schneider neuroanatomy. The pair were deeply influential in shaping his interests in neuroscience and his research.

“He admired them both very much and was very attached to them,” his daughter, Nimisha Schneider, says. “He was an interdisciplinary scholar and he liked that aspect of neuroscience, and he was fascinated by the mysteries of the human brain.”

Shortly after completing his PhD in psychology in 1966, he was hired as an assistant professor in 1967. He was named an associate professor in 1970, received tenure in 1975, and was appointed a full professor in 1977.

After his retirement in 2017, Schneider remained involved with the Department of BCS. Professor Pawan Sinha brought Schneider to campus for what would be his last on-campus engagement, as part of the “SilverMinds Series,” an initiative in the Sinha Lab to engage with scientists now in their “silver years.”

Schneider’s research made an indelible impact on Sinha, beginning as a graduate student when he was inspired by Schneider’s work linking brain structure and function. His work on nerve regeneration, which merged fundamental science and real-world impact, served as a “North Star” that guided Sinha’s own work as he established his lab as a junior faculty member.

“Even through the sadness of his loss, I am grateful for the inspiring example he has left for us of a life that so seamlessly combined brilliance, kindness, modesty, and tenacity,” Sinha says. “He will be missed.”

Schneider’s life centered around his research and teaching, but he also had many other skills and hobbies. Early in his life, he enjoyed painting, and as he grew older he was drawn to poetry. He was also skilled in carpentry and making furniture. He built the original hamster cages for his lab himself, along with numerous pieces of home furniture and shelving. He enjoyed nature anywhere it could be found, from the bees in his backyard to hiking and visiting state and national parks.

He was a Type 1 diabetic, and at the time of his death, he was nearing the completion of a book on the effects of hypoglycemia on the brain, which his family hopes to have published in the future. He was also the author of “Brain Structure and Its Origins,” published in 2014 by MIT Press.

He is survived by his wife, Aiping; his children, Cybele, Aniket, and Nimisha; and step-daughter Anna. He was predeceased by a daughter, Brenna. He is also survived by eight grandchildren and 10 great-grandchildren. A memorial in his honor was held on Jan. 11 at Saint James Episcopal Church in Cambridge.

In biology textbooks, the endoplasmic reticulum is often portrayed as a distinct, compact organelle near the nucleus, and is commonly known to be responsible for protein trafficking and secretion. In reality, the ER is vast and dynamic, spread throughout the cell and able to establish contact and communication with and between other organelles. These membrane contacts regulate processes as diverse as fat metabolism, sugar metabolism, and immune responses.

Exploring how pathogens manipulate and hijack essential processes to promote their own life cycles can reveal much about fundamental cellular functions and provide insight into viable treatment options for understudied pathogens.

New research from the Lamason Lab in the Department of Biology at MIT recently published in the Journal of Cell Biology has shown that Rickettsia parkeri, a bacterial pathogen that lives freely in the cytosol, can interact in an extensive and stable way with the rough endoplasmic reticulum, forming previously unseen contacts with the organelle.

It’s the first known example of a direct interkingdom contact site between an intracellular bacterial pathogen and a eukaryotic membrane.

The Lamason Lab studies R. parkeri as a model for infection of the more virulent Rickettsia rickettsii. R. rickettsii, carried and transmitted by ticks, causes Rocky Mountain Spotted Fever. Left untreated, the infection can cause symptoms as severe as organ failure and death.

Rickettsia is difficult to study because it is an obligate pathogen, meaning it can only live and reproduce inside living cells, much like a virus. Researchers must get creative to parse out fundamental questions and molecular players in the R. parkeri life cycle, and much remains unclear about how R. parkeri spreads.

Detour to the junction

First author Yamilex Acevedo-Sánchez, a BSG-MSRP-Bio program alum and a graduate student at the time, stumbled across the ER and R. parkeri interactions while trying to observe Rickettsia reaching a cell junction.

The current model for Rickettsia infection involves R. parkeri spreading cell to cell by traveling to the specialized contact sites between cells and being engulfed by the neighboring cell in order to spread. Listeria monocytogenes, which the Lamason Lab also studies, uses actin tails to forcefully propel itself into a neighboring cell. By contrast, R. parkeri can form an actin tail, but loses it before reaching the cell junction. Somehow, R. parkeri is still able to spread to neighboring cells.

After an MIT seminar about the ER’s lesser-known functions, Acevedo-Sánchez developed a cell line to observe whether Rickettsia might be spreading to neighboring cells by hitching a ride on the ER to reach the cell junction.

Instead, she saw an unexpectedly high percentage of R. parkeri surrounded and enveloped by the ER, at a distance of about 55 nanometers. This distance is significant because membrane contacts for interorganelle communication in eukaryotic cells form connections from 10-80 nanometers wide. The researchers ruled out that what they saw was not an immune response, and the sections of the ER interacting with the R. parkeri were still connected to the wider network of the ER.

“I’m of the mind that if you want to learn new biology, just look at cells,” Acevedo-Sánchez says. “Manipulating the organelle that establishes contact with other organelles could be a great way for a pathogen to gain control during infection.” 

The stable connections were unexpected because the ER is constantly breaking and reforming connections, lasting seconds or minutes. It was surprising to see the ER stably associating around the bacteria. As a cytosolic pathogen that exists freely in the cytosol of the cells it infects, it was also unexpected to see R. parkeri surrounded by a membrane at all.

Small margins

Acevedo-Sánchez collaborated with the Center for Nanoscale Systems at Harvard University to view her initial observations at higher resolution using focused ion beam scanning electron microscopy. FIB-SEM involves taking a sample of cells and blasting them with a focused ion beam in order to shave off a section of the block of cells. With each layer, a high-resolution image is taken. The result of this process is a stack of images.

From there, Acevedo-Sánchez marked what different areas of the images were — such as the mitochondria, Rickettsia, or the ER — and a program called ORS Dragonfly, a machine learning program, sorted through the thousand or so images to identify those categories. That information was then used to create 3D models of the samples. 

Acevedo-Sánchez noted that less than 5 percent of R. parkeri formed connections with the ER — but small quantities of certain characteristics are known to be critical for R. parkeri infection. R. parkeri can exist in two states: motile, with an actin tail, and nonmotile, without it. In mutants unable to form actin tails, R. parkeri are unable to progress to adjacent cells — but in nonmutants, the percentage of R. parkeri that have tails starts at about 2 percent in early infection and never exceeds 15 percent at the height of it.

The ER only interacts with nonmotile R. parkeri, and those interactions increased 25-fold in mutants that couldn’t form tails.

Creating connections

Co-authors Acevedo-Sánchez, Patrick Woida, and Caroline Anderson also investigated possible ways the connections with the ER are mediated. VAP proteins, which mediate ER interactions with other organelles, are known to be co-opted by other pathogens during infection.

During infection by R. parkeri, VAP proteins were recruited to the bacteria; when VAP proteins were knocked out, the frequency of interactions between R. parkeri and the ER decreased, indicating R. parkeri may be taking advantage of these cellular mechanisms for its own purposes during infection.

Although Acevedo-Sánchez now works as a senior scientist at AbbVie, the Lamason Lab is continuing the work of exploring the molecular players that may be involved, how these interactions are mediated, and whether the contacts affect the host or bacteria’s life cycle.

Senior author and associate professor of biology Rebecca Lamason noted that these potential interactions are particularly interesting because bacteria and mitochondria are thought to have evolved from a common ancestor. The Lamason Lab has been exploring whether R. parkeri could form the same membrane contacts that mitochondria do, although they haven’t proven that yet. So far, R. parkeri is the only cytosolic pathogen that has been observed behaving this way.

“It’s not just bacteria accidentally bumping into the ER. These interactions are extremely stable. The ER is clearly extensively wrapping around the bacterium, and is still connected to the ER network,” Lamason says. “It seems like it has a purpose — what that purpose is remains a mystery.” 

“There is no treatment available for your son. We can’t do anything to help him.”

When Fernando Goldsztein MBA ’03 heard those words, something inside him snapped.

“I refused to accept what the doctors were saying. I transformed my fear into my greatest strength and started fighting.”

Goldsztein’s 12-year-old son Frederico was diagnosed with relapsing medulloblastoma, a life-threatening pediatric brain tumor. Goldsztein's life — and career plan — changed in an instant. He had to learn to become a different kind of leader altogether.

While Goldsztein never set out to become a founder, the MIT Sloan School of Management taught him the importance of networking, building friendships, and making career connections with peers and faculty from all walks of life. He began using those skills in a new way — boldly reaching out to the top medulloblastoma doctors and scientists at hospitals around the world to ask for help.

“I knew that I had to do something to save Frederico, but also the other estimated 15,000 children diagnosed with the disease around the world each year,” he says.

In 2021, Goldsztein launched The Medulloblastoma Initiative (MBI), a nonprofit organization dedicated to finding a cure using a remarkable new model for funding rare disease research.

In just 18 months, the organization — which is still in startup mode — has raised $11 million in private funding and brought together 14 of the world’s most prestigious labs and hospitals from across North America, Europe, and Brazil.

Two promising trials will launch in the coming months, and three additional trials are in the pipeline and currently awaiting U.S. Food and Drug Administration approval.

All of this in an industry that is notorious for bureaucratic red tape, and where the timeline from an initial lab discovery to a patient receiving a first treatment averages seven to 15 years.

While government research grants typically allocate just 4 cents on the dollar toward pediatric cancer research — pennies doled out across multiple labs pursuing uncoordinated efforts — MBI is laser-focused on pushing 100 percent of their funding toward a singular goal, without any overhead or administrative costs.

“There is no time to lose,” Goldsztein says. “We are making science move faster than it ever has before.”

The MBI blueprint for funding cures for rare diseases is replicable, and likely to disrupt the standard way health care research is funded and carried out by radically shortening the timeline.

From despair to strength

After his initial diagnosis at age 9, Frederico went through a nine-hour brain surgery and came to the United States to receive standard treatment. Goldsztein looked on helplessly as his son received radiation and then nine grueling rounds of chemotherapy.

First pioneered in the 1980s, this standard treatment protocol cures 70 percent of children. Still, it leaves most of them with lifelong side effects like cognitive problems, endocrine issues that stunt growth, and secondary tumors. Frederico was on the wrong side of that statistic. Just three years later, his tumor relapsed.

Goldsztein grimaces as he recalls the prognosis he and his wife heard from the doctors.

“It was unbelievable to me that there had been almost no discoveries in 40 years,” he says.

Ultimately, he found hope and partnership in Roger Packer, the director of the Brain Tumor Institute and the Gilbert Family Neurofibromatosis Institute of Children’s National Hospital. He is also the very doctor who created the standard treatment years before.

Packer explains that finding effective therapies for medulloblastoma was complex for 30 years because it is an umbrella term for 13 types of tumors. Frederico suffers from the most common one, Group 4.

Part of the reason the treatment has not changed is that, until recently, medicine has not advanced enough to detect differences between the different tumor types. Packer explains, “Now with molecular genetic testing and methylation, which is a way to essentially sort tumors, that has changed.”

The problem for Frederico was that very few researchers were working on Group 4, the sub-type of medulloblastoma that is the most common tumor, yet also the one that scientists know the least about.

Goldsztein challenged Packer: “If I can get you the funding, what can your lab do to advance medulloblastoma research quickly?”

An open-source consortium model

Packer advised that they work together to “try something different,” instead of just throwing money at research without any guideposts.

“We set up a consortium of leading institutions around the world doing medulloblastoma research, asked them to change their lab approach to focus on the Group 4 tumor, and assigned each lab a question to answer. We charged them with coming up with therapy — not in seven to 10 years, which is the normal transition from discovery to developing a drug and getting it to a patient, but within a two-year timeline,” he says.

Initially, seven labs signed on. Today, the Cure Group 4 Consortium is made up of 14 partners and reads like a who’s who of medulloblastoma heavy hitters: Children’s National Hospital, SickKids, Hopp Children’s Cancer Center, and Texas Children’s Hospital.

Labs can only join the consortium if they agree to follow some unusual rules. As Goldsztein explains, “To be accepted into this group and receive funding, there are no silos, and there is no duplicated work. Everyone has a piece of the puzzle, and we work together to move fast. That is the magic of our model.”

Inspired by MIT’s open-source methods, researchers must share data freely with one another to accelerate the group’s overall progress. This kind of partnership across labs and borders is unprecedented in a highly competitive sector.

Mariano Gargiulo MBA ’03 met Goldsztein on the first day of their MIT Sloan Fellows MBA program orientation and has been his dear friend ever since. An early-stage donor to MBI and a Houston-based executive in the energy sector, Gargiulo sat down with Goldsztein as he first conceptualized MBI’s operating model.

“Usually, startup business models plot out the next 10-15 years; Fernando’s timeline was only two years, and his benchmarks were in three-month increments.” It was audaciously optimistic, says Gargiulo, but so was the founder.

“When I saw it, I did not doubt that he would achieve his goals. I’m seeing Fernando hit those first targets now and it’s amazing to watch,” Gargiulo says.

Children’s National Hospital endorsed MBI in 2023 and invited Goldsztein to sit on its foundation’s board, adding credibility to the initiative and his ability to fundraise more ambitiously.

According to Packer, in the next few months, the first two MBI protocols will reach patients for the first time: an immunotherapy protocol, which “leverages the body’s immune response to target cancer cells more effectively and safely than traditional therapies,” and a medulloblastoma vaccine, which “adapts similar methodologies used in Covid-19 vaccine development. This approach aims to provide a versatile and mobile treatment that could be distributed globally.”

A matter of when

When Goldsztein is not with his own family in Brazil, fundraising, or managing MBI, he is on Zoom with a network of more than 70 other families with children with relapsed medulloblastoma. “I’m not a doctor and I don’t give out medical advice, but with these trials, we are giving each other hope,” he explains.

Hope and purpose are commodities that Goldsztein has in spades. “I don’t understand the idea of doing business and accumulating assets, but not helping others,” he says. He shared that message with an auditorium of his fellow alumni at his 2023 MIT Sloan Reunion.

Frederico, who defied all odds and lived with the threat of recurrence, recently graduated high school. He is interested in international relations and passionate about photography. “This is about finding a cure for Frederico and for all kids,” Goldsztein says.

When asked how the world would be impacted if MBI found a cure for medulloblastoma, Goldsztein shakes his head.

“We are going to find the cure. It’s not if, it’s a matter of when.”

His next goal is to scale MBI and have it serve as a resource for groups that want to replicate its playbook to solve other childhood diseases.

“I’m never going to stop,” he says.

Buildings cost a lot these days. But when concrete buildings are being constructed, there’s another material that can make them less expensive: mud.

MIT researchers have developed a method to use lightly treated mud, including soil from a building site, as the “formwork” molds into which concrete is poured. The technique deploys 3D printing and can replace the more costly method of building elaborate wood formworks for concrete construction.

“What we’ve demonstrated is that we can essentially take the ground we’re standing on, or waste soil from a construction site, and transform it into accurate, highly complex, and flexible formwork for customized concrete structures,” says Sandy Curth, a PhD student in MIT’s Department of Architecture who has helped spearhead the project.

The approach could help concrete-based construction take place more quickly and efficiently. It could also reduce costs and carbon emissions.

“It has the potential for immediate impact and doesn’t require changing the nature of the construction industry,” says Curth, who doubles as director of the Programmable Mud Initiative.

Curth has co-authored multiple papers about the method, most recently, “EarthWorks: Zero waste 3D printed earthen formwork for shape-optimized, reinforced concrete construction,” published in the journal Construction and Building Materials. Curth wrote that paper with nine co-authors, including Natalie Pearl, Emily Wissemann, Tim Cousin, Latifa Alkhayat, Vincent Jackow, Keith Lee, and Oliver Moldow, all MIT students; and Mohamed Ismail of the University of Virginia.

The paper’s final two co-authors are Lawrence Sass, professor and chair of the Computation Group in MIT’s Department of Architecture, and Caitlin Mueller, an associate professor at MIT in the Department of Architecture and the Department of Civil and Environmental Engineering. Sass is Curth’s graduate advisor.

Building a structure once, not twice

Constructing wooden formwork for a building is costly and time-consuming. There is saying in the industry that concrete structures have to be built twice — once through the wooden formwork, then again in the concrete poured into the forms.

Using soil for the formwork could change that process. While it might seem like an unusual material compared to the solidity of wooden formwork, soil is firm enough to handle poured concrete. The EarthWorks method, as its known, introduces some additive materials, such as straw, and a wax-like coating for the soil material to prevent any water from draining out of the concrete. Using large-scale 3D printing, the researchers can take soil from a construction site and print it into a custom-designed formwork shape.

“What we’ve done is make a system where we are using what is largely straightforward, large-scale 3D printing technology, and making it highly functional for the material,” Curth says. “We found a way to make formwork that is infinitely recyclable. It’s just dirt.”

Beyond cost and ease of acquiring the materials, the method offers at least two other interrelated advantages. One is environmental: Concrete construction accounts for as much as 8 percent of global carbon emissions, and this approach supports substantial emissions reductions, both through the formwork material itself and the ease of shaping the resulting concrete to only use what is structurally required. Using a method called shape optimization, developed for reinforced concrete in previous research by Ismail and Mueller, it is possible to reduce the carbon emissions of concrete structural frames by more than 50 percent.  

“The EarthWorks technique brings these complex, optimized structures much closer to built reality by offering a low-cost, low-carbon fabrication technique for formwork that can be deployed anywhere in the world,” Mueller says.

“It’s an enabling technology to make reinforced concrete buildings much, much more materially efficient, which has a direct impact on global carbon emissions,” Curth adds.

More generally, the EarthWorks method allows architects and engineers to create customized concrete shapes more easily, due to the flexibility of the formwork material. It is easier to cast concrete in an unusual shape when molding it with soil, not wood.

“What’s cool here is we’re able to make shape-optimized building elements for the same amount of time and energy it would take to make rectilinear building elements,” Curth says.

Group project

As Curth notes, the projects developed by the Programmable Mud group are highly collaborative. He emphasizes the roles played by both Sass, a leader in using computation to help develop low-cost housing, and Mueller, whose work also deploys new computational methods to assess innovative structural ideas in architecture.

“Concrete is a wonderful material when it is used thoughtfully and efficiently, which is inherently connected to how it is shaped,” Mueller says. “However, the minimal forms that emerge from optimization are at odds with conventional construction logics. It is very exciting to advance a technique that subverts this supposed tradeoff, showing that performance-driven complexity can be achieved with low carbon emissions and low cost.”

While finishing his doctorate at MIT, Curth has also founded a firm, FORMA Systems, through which he hopes to take the EarthWorks method into the construction industry. Using this approach does mean builders would need to have a large 3D printer on-site. However, they would also save significantly on materials costs, he says.

Further in the future, Curth envisions a time when the method could be used not just for formworks, but to construct templates for, say, two-story residential building made entirely out of earth. Of course, some parts of the world, including the U.S., extensively use adobe architecture already, but the idea here would be to systematize the production of such homes and make them inexpensive in the process.

In either case, Curth says, as formwork for concrete or by itself, we now have new ways to apply soil to construction.

“People have built with earth for as long as we’ve had buildings, but given contemporary demands for urban concrete buildings, this approach basically decouples cost from complexity,” Curth says. “I guarantee you we can start to make higher-performance buildings for less money.”

The project  was supported by the Sidara Urban Research Seed Fund administered by MIT’s Leventhal Center for Advanced Urbanism.

Several years ago, the residents of a manufactured-home neighborhood in southeast suburban Houston, not far from the Buffalo Bayou, took a major step in dealing with climate problems: They bought the land under their homes. Then they installed better drainage and developed strategies to share expertise and tools for home repairs. The result? The neighborhood made it through Hurricane Harvey in 2017 and a winter freeze in 2021 without major damage.

The neighborhood is part of a U.S. movement toward the Resident Owned Community (ROC) model for manufactured home parks. Many people in manufactured homes — mobile homes — do not own the land under them. But if the residents of a manufactured-home park can form an ROC, they can take action to adapt to climate risks — and ease the threat of eviction. With an ROC, manufactured-home residents can be there to stay.

That speaks to a larger issue: In cities, lower-income residents are often especially vulnerable to natural hazards, such as flooding, extreme heat, and wildfire. But efforts aimed at helping cities as a whole withstand these disasters can lead to interventions that displace already-disadvantaged residents — by turning a low-lying neighborhood into a storm buffer, for instance.

“The global climate crisis has very differential effects on cities, and neighborhoods within cities,” says Lawrence Vale, a professor of urban studies at MIT and co-author of a new book on the subject, “The Equitably Resilient City,” published by the MIT Press and co-authored with Zachary B. Lamb PhD ’18, an assistant professor at the University of California at Berkeley.

In the book, the scholars delve into 12 case studies from around the globe which, they believe, have it both ways: Low- and middle-income communities have driven climate progress through tangible built projects, while also keeping people from being displaced, and indeed helping them participate in local governance and neighborhood decision-making.

“We can either dive into despair about climate issues, or think they’re solvable and ask what it takes to succeed in a more equitable way,” says Vale, who is the Ford Professor of Urban Design and Planning at MIT. “This book is asking how people look at problems more holistically — to show how environmental impacts are integrated with their livelihoods, with feeling they can have security from displacement, and feeling they’re not going to be displaced, with being empowered to share in the governance where they live.”

As Lamb notes, “Pursuing equitable urban climate adaptation requires both changes in the physical built environment of cities and innovations in institutions and governance practices to address deep-seated causes of inequality.”

Twelve projects, four elements

Research for “The Equitably Resilient City” began with exploration of about 200 potential cases, and ultimately focused on 12 projects from around the globe, including the U.S., Brazil, Thailand, and France. Vale and Lamb, coordinating with locally-based research teams, visited these diverse sites and conducted interviews in nine languages.

All 12 projects work on multiple levels at once: They are steps toward environmental progress that also help local communities in civic and economic terms. The book uses the acronym LEGS (“livelihood, environment, governance, and security”) to encapsulate this need to make equitable progress on four different fronts.

“Doing one of those things well is worth recognition, and doing all of them well is exciting,” Vale says. “It’s important to understand not just what these communities did, but how they did it and whose views were involved. These 12 cases are not a random sample. The book looks for people who are partially succeeding at difficult things in difficult circumstances.”

One case study is set in São Paolo, Brazil, where low-income residents of a hilly favela benefitted from new housing in the area on undeveloped land that is less prone to slides. In San Juan, Puerto Rico, residents of low-lying neighborhoods abutting a water channel formed a durable set of community groups to create a fairer solution to flooding: Although the channel needed to be re-widened, the local coalition insisted on limiting displacement, supporting local livelihoods and improving environmental conditions and public space.

“There is a backlash to older practices,” Vale says, referring to the large-scale urban planning and infrastructure projects of the mid-20th century, which often ignored community input. “People saw what happened during the urban renewal era and said, ‘You’re not going to do that to us again.’”

Indeed, one through-line in “The Equitably Resilient City” is that cities, like all places, can be contested political terrain. Often, solid solutions emerge when local groups organize, advocate for new solutions, and eventually gain enough traction to enact them.

“Every one of our examples and cases has probably 15 or 20 years of activity behind it, as well as engagements with a much deeper history,” Vale says. “They’re all rooted in a very often troubled [political] context. And yet these are places that have made progress possible.”

Think locally, adapt anywhere

Another motif of “The Equitably Resilient City” is that local progress matters greatly, for a few reasons — including the value of having communities develop projects that meet their own needs, based on their input. Vale and Lamb are interested in projects even if they are very small-scale, and devote one chapter of the book to the Paris OASIS program, which has developed a series of cleverly designed, heavily tree-dotted school playgrounds across Paris. These projects provide environmental education opportunities and help mitigate flooding and urban heat while adding CO2-harnessing greenery to the cityscape.

An individual park, by itself, can only do so much, but the concept behind it can be adopted by anyone.

“This book is mostly centered on local projects rather than national schemes,” Vale says. “The hope is they serve as an inspiration for people to adapt to their own situations.”

After all, the urban geography and governance of places such as Paris or São Paulo will differ widely. But efforts to make improvements to public open space or to well-located inexpensive housing stock applies in cities across the world.

Similarly, the authors devote a chapter to work in the Cully neighborhood in Portland, Oregon, where community leaders have instituted a raft of urban environmental improvements while creating and preserving more affordable housing. The idea in the Cully area, as in all these cases, is to make places more resistant to climate change while enhancing them as good places to live for those already there.

“Climate adaptation is going to mobilize enormous public and private resources to reshape cities across the globe,” Lamb notes. “These cases suggest pathways where those resources can make cities both more resilient in the face of climate change and more equitable. In fact, these projects show how making cities more equitable can be part of making them more resilient.”

Other scholars have praised the book. Eric Klinenberg, director of New York University’s Institute for Public Knowledge has called it “at once scholarly, constructive, and uplifting, a reminder that better, more just cities remain within our reach.”

Vale also teaches some of the book’s concepts in his classes, finding that MIT students, wherever they are from, enjoy the idea of thinking creatively about climate resilience.

“At MIT, students want to find ways of applying technical skills to urgent global challenges,” Vale says. “I do think there are many opportunities, especially at a time of climate crisis. We try to highlight some of the solutions that are out there. Give us an opportunity, and we’ll show you what a place can be.”

Businesses and developers often face a steep learning curve when installing clean energy technologies, such as solar installations and EV chargers. To get a fair deal, they need to navigate a complex bidding process that involves requesting proposals, evaluating bids, and ultimately contracting with a provider.

Now the startup Station A, founded by a pair of MIT alumni and their colleagues, is streamlining the process of deploying clean energy. The company has developed a marketplace for clean energy that helps real estate owners and businesses analyze properties to calculate returns on clean energy projects, create detailed project listings, collect and compare bids, and select a provider.

The platform helps real estate owners and businesses adopt clean energy technologies like solar panels, batteries, and EV chargers at the lowest possible prices, in places with the highest potential to reduce energy costs and emissions.

“We do a lot to make adopting clean energy simple,” explains Manos Saratsis SMArchS ’15, who co-founded Station A with Kevin Berkemeyer MBA ’14. “Imagine if you were trying to buy a plane ticket and your travel agent only used one carrier. It would be more expensive, and you couldn’t even get to some places. Our customers want to have multiple options and easily learn about the track record of whoever they’re working with.”

Station A has already partnered with some of the largest real estate companies in the country, some with thousands of properties, to reduce the carbon footprint of their buildings. The company is also working with grocery chains, warehouses, and other businesses to accelerate the clean energy transition.

“Our platform uses a lot of AI and machine learning to turn addresses into building footprints and to understand their electricity costs, available incentives, and where they can expect the highest ROI,” says Saratsis, who serves as Station A’s head of product. “This would normally require tens or hundreds of thousands of dollars’ worth of consulting time, and we can do it for next to no money very quickly.”

Building the foundation

As a graduate student in MIT’s Department of Architecture, Saratsis studied environmental design modeling, using data from sources like satellite imagery to understand how communities consume energy and to propose the most impactful potential clean energy solutions. He says classes with professors Christoph Reinhart and Kent Larson were particularly eye-opening.

“My ability to build a thermal energy model and simulate electricity usage in a building started at MIT,” Saratsis says.

Berkemeyer served as president of the MIT Energy Club while at the MIT Sloan School of Management. He was also a research assistant at the MIT Energy Initiative as part of the Future of Solar report and a teacher’s assistant for course 15.366 (Climate and Energy Ventures). He says classes in entrepreneurship with professor of the practice Bill Aulet and in sustainability with Senior Lecturer Jason Jay were formative. Prior to his studies at MIT, Berkemeyer had extensive experience developing solar and storage projects and selling clean energy products to commercial customers. The eventual co-founders didn’t cross paths at MIT, but they ended up working together at the utility NRG Energy after graduation.

“As co-founders, we saw an opportunity to transform how businesses approach clean energy,” said Berkemeyer, who is now Station A’s CEO. “Station A was born out of a shared belief that data and transparency could unlock the full potential of clean energy technologies for everyone.”

At NRG, the founders built software to help identify decarbonization opportunities for customers without having to send analysts to the sites for in-person audits.

“If they worked with a big grocery chain or a big retailer, we would use proprietary analytics to evaluate that portfolio and come up with recommendations for things like solar projects, energy efficiency, and demand response that would yield positive returns within a year,” Saratsis explains.

The tools were a huge success within the company. In 2018, the pair, along with co-founders Jeremy Lucas and Sam Steyer, decided to spin out the technology into Station A.

The founders started by working with energy companies but soon shifted their focus to real estate owners with huge portfolios and large businesses with long-term leasing contracts. Many customers have hundreds or even thousands of addresses to evaluate. Using just the addresses, Station A can provide detailed financial return estimates for clean energy investments.

In 2020, the company widened its focus from selling access to its analytics to creating a marketplace for clean energy transactions, helping businesses run the competitive bidding process for clean energy projects. After a project is installed, Station A can also evaluate whether it’s achieving its expected performance and track financial returns.

“When I talk to people outside the industry, they’re like, ‘Wait, this doesn’t exist already?’” Saratsis says. “It’s kind of crazy, but the industry is still very nascent, and no one’s been able to figure out a way to run the bidding process transparently and at scale.”

From the campus to the world

Today, about 2,500 clean energy developers are active on Station A’s platform. A number of large real estate investment trusts also use its services, in addition to businesses like HP, Nestle, and Goldman Sachs. If Station A were a developer, Saratsis says it would now rank in the top 10 in terms of annual solar deployments.

The founders credit their time at MIT with helping them scale.

“A lot of these relationships originated within the MIT network, whether through folks we met at Sloan or through engagement with MIT,” Saratsis says. “So much of this business is about reputation, and we’ve established a really good reputation.”

Since its founding, Station A has also been sponsoring classes at the Sustainability Lab at MIT, where Saratsis conducted research as a student. As they work to grow Station A’s offerings, the founders say they use the skills they gained as students every day.

“Everything we do around building analysis is inspired in some ways by the stuff that I did when I was at MIT,” Saratsis says.

“Station A is just getting started,” Berkemeyer says. “Clean energy adoption isn’t just about technology — it’s about making the process seamless and accessible. That’s what drives us every day, and we’re excited to lead this transformation.”

A new experimental vaccine developed by researchers at MIT and Caltech could offer protection against emerging variants of SARS-CoV-2, as well as related coronaviruses, known as sarbecoviruses, that could spill over from animals to humans.

In addition to SARS-CoV-2, the virus that causes COVID-19, sarbecoviruses — a subgenus of coronaviruses — include the virus that led to the outbreak of the original SARS in the early 2000s. Sarbecoviruses that currently circulate in bats and other mammals may also hold the potential to spread to humans in the future.

By attaching up to eight different versions of sarbecovirus receptor-binding proteins (RBDs) to nanoparticles, the researchers created a vaccine that generates antibodies that recognize regions of RBDs that tend to remain unchanged across all strains of the viruses. That makes it much more difficult for viruses to evolve to escape vaccine-induced antibodies.

“This work is an example of how bringing together computation and immunological experiments can be fruitful,” says Arup K. Chakraborty, the John M. Deutch Institute Professor at MIT and a member of MIT’s Institute for Medical Engineering and Science and the Ragon Institute of MIT, MGH and Harvard University.

Chakraborty and Pamela Bjorkman, a professor of biology and biological engineering at Caltech, are the senior authors of the study, which appears today in Cell. The paper’s lead authors are Eric Wang PhD ’24, Caltech postdoc Alexander Cohen, and Caltech graduate student Luis Caldera.

Mosaic nanoparticles

The new study builds on a project begun in Bjorkman’s lab, in which she and Cohen created a “mosaic” 60-mer nanoparticle that presents eight different sarbecovirus RBD proteins. The RBD is the part of the viral spike protein that helps the virus get into host cells. It is also the region of the coronavirus spike protein that is usually targeted by antibodies against sarbecoviruses.

RBDs contain some regions that are variable and can easily mutate to escape antibodies. Most of the antibodies generated by mRNA COVID-19 vaccines target those variable regions because they are more easily accessible. That is one reason why mRNA vaccines need to be updated to keep up with the emergence of new strains.

If researchers could create a vaccine that stimulates production of antibodies that target RBD regions that can’t easily change and are shared across viral strains, it could offer broader protection against a variety of sarbecoviruses.

Such a vaccine would have to stimulate B cells that have receptors (which then become antibodies) that target those shared, or “conserved,” regions. When B cells circulating in the body encounter a vaccine or other antigen, their B cell receptors, each of which have two “arms,” are more effectively activated if two copies of the antigen are available for binding to each arm. The conserved regions tend to be less accessible to B cell receptors, so if a nanoparticle vaccine presents just one type of RBD, B cells with receptors that bind to the more accessible variable regions, are most likely to be activated.

To overcome this, the Caltech researchers designed a nanoparticle vaccine that includes 60 copies of RBDs from eight different related sarbecoviruses, which have different variable regions but similar conserved regions. Because eight different RBDs are displayed on each nanoparticle, it’s unlikely that two identical RBDs will end up next to each other. Therefore, when a B cell receptor encounters the nanoparticle immunogen, the B cell is more likely to become activated if its receptor can recognize the conserved regions of the RBD.

“The concept behind the vaccine is that by co-displaying all these different RBDs on the nanoparticle, you are selecting for B cells that recognize the conserved regions that are shared between them,” Cohen says. “As a result, you’re selecting for B cells that are more cross-reactive. Therefore, the antibody response would be more cross-reactive and you could potentially get broader protection.”

In studies conducted in animals, the researchers showed that this vaccine, known as mosaic-8, produced strong antibody responses against diverse strains of SARS-CoV-2 and other sarbecoviruses and protected from challenges by both SARS-CoV-2 and SARS-CoV (original SARS).

Broadly neutralizing antibodies

After these studies were published in 2021 and 2022, the Caltech researchers teamed up with Chakraborty’s lab at MIT to pursue computational strategies that could allow them to identify RBD combinations that would generate even better antibody responses against a wider variety of sarbecoviruses.

Led by Wang, the MIT researchers pursued two different strategies — first, a large-scale computational screen of many possible mutations to the RBD of SARS-CoV-2, and second, an analysis of naturally occurring RBD proteins from zoonotic sarbecoviruses.

For the first approach, the researchers began with the original strain of SARS-CoV-2 and generated sequences of about 800,000 RBD candidates by making substitutions in locations that are known to affect antibody binding to variable portions of the RBD. Then, they screened those candidates for their stability and solubility, to make sure they could withstand attachment to the nanoparticle and injection as a vaccine.

From the remaining candidates, the researchers chose 10 based on how different their variable regions were. They then used these to create mosaic nanoparticles coated with either two or five different RBD proteins (mosaic-2COM and mosaic-5COM).

In their second approach, instead of mutating the RBD sequences, the researchers chose seven naturally occurring RBD proteins, using computational techniques to select RBDs that were different from each other in regions that are variable, but retained their conserved regions. They used these to create another vaccine, mosaic-7COM.

Once the researchers produced the RBD-nanoparticles, they evaluated each one in mice. After each mouse received three doses of one of the vaccines, the researchers analyzed how well the resulting antibodies bound to and neutralized seven variants of SARS-CoV-2 and four other sarbecoviruses. 

They also compared the mosaic nanoparticle vaccines to a nanoparticle with only one type of RBD displayed, and to the original mosaic-8 particle from their 2021, 2022, and 2024 studies. They found that mosaic-2COM and mosaic-5COM outperformed both of those vaccines, and mosaic-7COM showed the best responses of all. Mosaic-7COM elicited antibodies with binding to most of the viruses tested, and these antibodies were also able to prevent the viruses from entering cells.

The researchers saw similar results when they tested the new vaccines in mice that were previously vaccinated with a bivalent mRNA COVID-19 vaccine.

“We wanted to simulate the fact that people have already been infected and/or vaccinated against SARS-CoV-2,” Wang says. “In pre-vaccinated mice, mosaic-7COM is consistently giving the highest binding titers for both SARS-CoV-2 variants and other sarbecoviruses.”

Bjorkman’s lab has received funding from the Coalition for Epidemic Preparedness Innovations to do a clinical trial of the mosaic-8 RBD-nanoparticle. They also hope to move mosaic-7COM, which performed better in the current study, into clinical trials. The researchers plan to work on redesigning the vaccines so that they could be delivered as mRNA, which would make them easier to manufacture.

The research was funded by a National Science Foundation Graduate Research Fellowship, the National Institutes of Health, Wellcome Leap, the Bill and Melinda Gates Foundation, the Coalition for Epidemic Preparedness Innovations, and the Caltech Merkin Institute for Translational Research.

As the capabilities of generative AI models have grown, you've probably seen how they can transform simple text prompts into hyperrealistic images and even extended video clips.

More recently, generative AI has shown potential in helping chemists and biologists explore static molecules, like proteins and DNA. Models like AlphaFold can predict molecular structures to accelerate drug discovery, and the MIT-assisted “RFdiffusion,” for example, can help design new proteins. One challenge, though, is that molecules are constantly moving and jiggling, which is important to model when constructing new proteins and drugs. Simulating these motions on a computer using physics — a technique known as molecular dynamics — can be very expensive, requiring billions of time steps on supercomputers.

As a step toward simulating these behaviors more efficiently, MIT Computer Science and Artificial Intelligence Laboratory (CSAIL) and Department of Mathematics researchers have developed a generative model that learns from prior data. The team’s system, called MDGen, can take a frame of a 3D molecule and simulate what will happen next like a video, connect separate stills, and even fill in missing frames. By hitting the “play button” on molecules, the tool could potentially help chemists design new molecules and closely study how well their drug prototypes for cancer and other diseases would interact with the molecular structure it intends to impact.

Co-lead author Bowen Jing SM ’22 says that MDGen is an early proof of concept, but it suggests the beginning of an exciting new research direction. “Early on, generative AI models produced somewhat simple videos, like a person blinking or a dog wagging its tail,” says Jing, a PhD student at CSAIL. “Fast forward a few years, and now we have amazing models like Sora or Veo that can be useful in all sorts of interesting ways. We hope to instill a similar vision for the molecular world, where dynamics trajectories are the videos. For example, you can give the model the first and 10th frame, and it’ll animate what’s in between, or it can remove noise from a molecular video and guess what was hidden.”

The researchers say that MDGen represents a paradigm shift from previous comparable works with generative AI in a way that enables much broader use cases. Previous approaches were “autoregressive,” meaning they relied on the previous still frame to build the next, starting from the very first frame to create a video sequence. In contrast, MDGen generates the frames in parallel with diffusion. This means MDGen can be used to, for example, connect frames at the endpoints, or “upsample” a low frame-rate trajectory in addition to pressing play on the initial frame.

This work was presented in a paper shown at the Conference on Neural Information Processing Systems (NeurIPS) this past December. Last summer, it was awarded for its potential commercial impact at the International Conference on Machine Learning’s ML4LMS Workshop.

Some small steps forward for molecular dynamics

In experiments, Jing and his colleagues found that MDGen’s simulations were similar to running the physical simulations directly, while producing trajectories 10 to 100 times faster.

The team first tested their model’s ability to take in a 3D frame of a molecule and generate the next 100 nanoseconds. Their system pieced together successive 10-nanosecond blocks for these generations to reach that duration. The team found that MDGen was able to compete with the accuracy of a baseline model, while completing the video generation process in roughly a minute — a mere fraction of the three hours that it took the baseline model to simulate the same dynamic.

When given the first and last frame of a one-nanosecond sequence, MDGen also modeled the steps in between. The researchers’ system demonstrated a degree of realism in over 100,000 different predictions: It simulated more likely molecular trajectories than its baselines on clips shorter than 100 nanoseconds. In these tests, MDGen also indicated an ability to generalize on peptides it hadn’t seen before.

MDGen’s capabilities also include simulating frames within frames, “upsampling” the steps between each nanosecond to capture faster molecular phenomena more adequately. It can even ​​“inpaint” structures of molecules, restoring information about them that was removed. These features could eventually be used by researchers to design proteins based on a specification of how different parts of the molecule should move.

Toying around with protein dynamics

Jing and co-lead author Hannes Stärk say that MDGen is an early sign of progress toward generating molecular dynamics more efficiently. Still, they lack the data to make these models immediately impactful in designing drugs or molecules that induce the movements chemists will want to see in a target structure.

The researchers aim to scale MDGen from modeling molecules to predicting how proteins will change over time. “Currently, we’re using toy systems,” says Stärk, also a PhD student at CSAIL. “To enhance MDGen’s predictive capabilities to model proteins, we’ll need to build on the current architecture and data available. We don’t have a YouTube-scale repository for those types of simulations yet, so we’re hoping to develop a separate machine-learning method that can speed up the data collection process for our model.”

For now, MDGen presents an encouraging path forward in modeling molecular changes invisible to the naked eye. Chemists could also use these simulations to delve deeper into the behavior of medicine prototypes for diseases like cancer or tuberculosis.

“Machine learning methods that learn from physical simulation represent a burgeoning new frontier in AI for science,” says Bonnie Berger, MIT Simons Professor of Mathematics, CSAIL principal investigator, and senior author on the paper. “MDGen is a versatile, multipurpose modeling framework that connects these two domains, and we’re very excited to share our early models in this direction.”

“Sampling realistic transition paths between molecular states is a major challenge,” says fellow senior author Tommi Jaakkola, who is the MIT Thomas Siebel Professor of electrical engineering and computer science and the Institute for Data, Systems, and Society, and a CSAIL principal investigator. “This early work shows how we might begin to address such challenges by shifting generative modeling to full simulation runs.”

Researchers across the field of bioinformatics have heralded this system for its ability to simulate molecular transformations. “MDGen models molecular dynamics simulations as a joint distribution of structural embeddings, capturing molecular movements between discrete time steps,” says Chalmers University of Technology associate professor Simon Olsson, who wasn’t involved in the research. “Leveraging a masked learning objective, MDGen enables innovative use cases such as transition path sampling, drawing analogies to inpainting trajectories connecting metastable phases.”

The researchers’ work on MDGen was supported, in part, by the National Institute of General Medical Sciences, the U.S. Department of Energy, the National Science Foundation, the Machine Learning for Pharmaceutical Discovery and Synthesis Consortium, the Abdul Latif Jameel Clinic for Machine Learning in Health, the Defense Threat Reduction Agency, and the Defense Advanced Research Projects Agency.

MIT physicists have created a new ultrathin, two-dimensional material with unusual magnetic properties that initially surprised the researchers before they went on to solve the complicated puzzle behind those properties’ emergence. As a result, the work introduces a new platform for studying how materials behave at the most fundamental level — the world of quantum physics.

Ultrathin materials made of a single layer of atoms have riveted scientists’ attention since the discovery of the first such material — graphene, composed of carbon — about 20 years ago. Among other advances since then, researchers have found that stacking individual sheets of the 2D materials, and sometimes twisting them at a slight angle to each other, can give them new properties, from superconductivity to magnetism. Enter the field of twistronics, which was pioneered at MIT by Pablo Jarillo-Herrero, the Cecil and Ida Green Professor of Physics at MIT.

In the current research, reported in the Jan. 7 issue of Nature Physics, the scientists, led by Jarillo-Herrero, worked with three layers of graphene. Each layer was twisted on top of the next at the same angle, creating a helical structure akin to the DNA helix or a hand of three cards that are fanned apart.

“Helicity is a fundamental concept in science, from basic physics to chemistry and molecular biology. With 2D materials, one can create special helical structures, with novel properties which we are just beginning to understand. This work represents a new twist in the field of twistronics, and the community is very excited to see what else we can discover using this helical materials platform!” says Jarillo-Herrero, who is also affiliated with MIT’s Materials Research Laboratory.

Do the twist

Twistronics can lead to new properties in ultrathin materials because arranging sheets of 2D materials in this way results in a unique pattern called a moiré lattice. And a moiré pattern, in turn, has an impact on the behavior of electrons.

“It changes the spectrum of energy levels available to the electrons and can provide the conditions for interesting phenomena to arise,” says Sergio C. de la Barrera, one of three co-first authors of the recent paper. De la Barrera, who conducted the work while a postdoc at MIT, is now an assistant professor at the University of Toronto.

In the current work, the helical structure created by the three graphene layers forms two moiré lattices. One is created by the first two overlapping sheets; the other is formed between the second and third sheets.

The two moiré patterns together form a third moiré, a supermoiré, or “moiré of a moiré,” says Li-Qiao Xia, a graduate student in MIT physics and another of the three co-first authors of the Nature Physics paper. “It’s like a moiré hierarchy.” While the first two moiré patterns are only nanometers, or billionths of a meter, in scale, the supermoiré appears at a scale of hundreds of nanometers superimposed over the other two. You can only see it if you zoom out to get a much wider view of the system.

A major surprise

The physicists expected to observe signatures of this moiré hierarchy. They got a huge surprise, however, when they applied and varied a magnetic field. The system responded with an experimental signature for magnetism, one that arises from the motion of electrons. In fact, this orbital magnetism persisted to -263 degrees Celsius — the highest temperature reported in carbon-based materials to date.

But that magnetism can only occur in a system that lacks a specific symmetry — one that the team’s new material should have had. “So the fact that we saw this was very puzzling. We didn’t really understand what was going on,” says Aviram Uri, an MIT Pappalardo postdoc in physics and the third co-first author of the new paper.

Other authors of the paper include MIT professor of physics Liang Fu; Aaron Sharpe of Sandia National Laboratories; Yves H. Kwan of Princeton University; Ziyan Zhu, David Goldhaber-Gordon, and Trithep Devakul of Stanford University; and Kenji Watanabe and Takashi Taniguchi of the National Institute for Materials Science in Japan.

What was happening?

It turns out that the new system did indeed break the symmetry that prohibits the orbital magnetism the team observed, but in a very unusual way. “What happens is that the atoms in this system aren’t very comfortable, so they move in a subtle orchestrated way that we call lattice relaxation,” says Xia. And the new structure formed by that relaxation does indeed break the symmetry locally, on the moiré length scale.

This opens the possibility for the orbital magnetism the team observed. However, if you zoom out to view the system on the supermoiré scale, the symmetry is restored. “The moiré hierarchy turns out to support interesting phenomena at different length scales,” says de la Barrera.

Concludes Uri: “It’s a lot of fun when you solve a riddle and it’s such an elegant solution. We’ve gained new insights into how electrons behave in these complex systems, insights that we couldn’t have had unless our experimental observations forced to think about these things.”

This work was supported by the Army Research Office, the National Science Foundation, the Gordon and Betty Moore Foundation, the Ross M. Brown Family Foundation, an MIT Pappalardo Fellowship, the VATAT Outstanding Postdoctoral Fellowship in Quantum Science and Technology, the JSPS KAKENHI, and a Stanford Science Fellowship.

MIT.nano has announced seven new companies to join START.nano, a program aimed at speeding the transition of hard-tech innovation to market. The program supports new ventures through discounted use of MIT.nano’s facilities and access to the MIT innovation ecosystem.

The advancements pursued by the newly engages startups include wearables for health care, green alternatives to fossil fuel-based energy, novel battery technologies, enhancements in data systems, and interconnecting nanofabrication knowledge networks, among others.

“The transition of the grand idea that is imagined in the laboratory to something that a million people can use in their hands is a journey fraught with many challenges,” MIT.nano Director Vladimir Bulović said at the 2024 Nano Summit, where nine START.nano companies presented their work. The program provides resources to ease startups over the first two hurdles — finding stakeholders and building a well-developed prototype.

In addition to access to laboratory tools necessary to advance their technologies, START.nano companies receive advice from MIT.nano expert staff, are connected to MIT.nano Consortium companies, gain a broader exposure at MIT conferences and community events, and are eligible to join the MIT Startup Exchange.

“MIT.nano has allowed us to push our project to the frontiers of sensing by implementing advanced fabrication techniques using their machinery,” said Uroš Kuzmanović, CEO and founder of Biosens8. “START.nano has surrounded us with exciting peers, a strong support system, and a spotlight to present our work. By taking advantage of all that the program has to offer, BioSens8 is moving faster than we could anywhere else.”

Here are the seven new START.nano participants:

Analog Photonics is developing lidar and optical communications technology using silicon photonics.

Biosens8 is engineering novel devices to enable health ownership. Their research focuses on multiplexed wearables for hormones, neurotransmitters, organ health markers, and drug use that will give insight into the body's health state, opening the door to personalized medicine and proactive, data-driven health decisions.

Casimir, Inc. is working on power-generating nanotechnology that interacts with quantum fields to create a continuous source of power. The team compares their technology to a solar panel that works in the dark or a battery that never needs to be recharged.

Central Spiral focuses on lossless data compression. Their technology allows for the compression of any type of data, including those that are already compressed, reducing data storage and transmission costs, lowering carbon dioxide emissions, and enhancing efficiency.

FabuBlox connects stakeholders across the nanofabrication ecosystem and resolves issues of scattered, unorganized, and isolated fab knowledge. Their cloud-based platform combines a generative process design and simulation interface with GitHub-like repository building capabilities.

Metal Fuels is converting industrial waste aluminum to onsite energy and high-value aluminum/aluminum-oxide powders. Their approach combines existing mature technologies of molten metal purification and water atomization to develop a self-sustaining reactor that produces alumina of higher value than our input scrap aluminum feedstock, while also collecting the hydrogen off-gas.

PolyJoule, Inc. is an energy storage startup working on conductive polymer battery technology. The team’s goal is a grid battery of the future that is ultra-safe, sustainable, long living, and low-cost.

In addition to the seven startups that are actively using MIT.nano, nine other companies have been invited to join the latest START.nano cohort:

• Acorn Genetics
• American Boronite Corp.
• Copernic Catalysts
• Envoya Bio
• Helix Carbon
• Minerali
• Plaid Semiconductors
• Quantum Network Technologies
• Wober Tech

Launched in 2021, START.nano now comprises over 20 companies and eight graduates — ventures that have moved beyond the initial startup stages and some into commercialization. 

Steven Strang, a writer and literary scholar who founded MIT’s Writing and Communication Center in 1981 and directed it for 40 years, died with family at his side on Dec. 29, 2024. He was 77.

His vision for the center was ambitious. After an MIT working group identified gaps between the students’ technical knowledge and their ability to communicate it — particularly once in positions of leadership — Strang advocated an even broader approach rarely used at other universities. Rather than student-tutors working with peers, Strang hired instructors with doctorates, subject matter expertise, and teaching experience to help train all MIT community members for the current and future careers becoming increasingly reliant on persuasion and the need to communicate with varied audiences.

“He made an indelible mark on the MIT community,” wrote current director Elena Kallestinova in a message to WCC staff soon after Strang’s death. “He was deeply respected as a leader, educator, mentor, and colleague.”

Beginning his professional life as a journalist with the Bangor Daily News, Strang soon shifted to academia, receiving a PhD in English from Brown University and over the decades publishing countless pieces of fiction, poetry, and criticism, in addition to his pedagogical articles on writing and rhetoric. 

But the Writing and Communication Center is his legacy. At his Jan. 11 memorial, longtime MIT lecturer and colleague Thalia Rubio called the WCC “Steve’s creation,” pointing out that it went on to serve many thousands of students and others. Another colleague, Bob Irwin, described in a note Strang’s commitment to making the WCC “a place that offered both friendliness and the highest professional standards of advice and consultation on all communication tasks and issues. Steve himself was conscientious, a respectful director, and a warm and reliable mentor to me and others. I think he was exemplary in his job.”

MIT recognized Strang’s major contributions with a Levitan Teaching Award, an Infinite Mile Award, and an Excellence Award. In nomination letters and testimonials, students and peers alike told of a “tireless commitment,” that “they might not have graduated, or been hired to the job they have today, or gained admittance to graduate school had it not been for the help of The Writing Center.” 

Strang is also remembered for his work founding the MIT Writers Group, which he first offered as a creative writing workshop for Independent Activities Period in 2002. In yet another example of Strang recognizing and meeting a community need, about 70 people from across the Institute showed up that first year.

Strang is survived by a large extended family, including his wife Ayni and her two children, Elly and Marta, whom Strang adopted as his own. Donations in his memory can be made to The Rhode Island Society for the Prevention of Cruelty to Animals.

Materials like car tires, human tissues, and spider webs are diverse in composition, but all contain networks of interconnected strands. A long-standing question about the durability of these materials asks: What is the energy required to fracture these diverse networks? A recently published paper by MIT researchers offers new insights.

“Our findings reveal a simple, general law that governs the fracture energy of networks across various materials and length scales,” says Xuanhe Zhao, the Uncas and Helen Whitaker Professor and professor of mechanical engineering and civil and environmental engineering at MIT. “This discovery has significant implications for the design of new materials, structures, and metamaterials, allowing for the creation of systems that are incredibly tough, soft, and stretchable.”

Despite an established understanding of the importance of failure resistance in design of such networks, no existing physical model effectively linked strand mechanics and connectivity to predict bulk fracture — until now. This new research reveals a universal scaling law that bridges length scales and makes it possible to predict the intrinsic fracture energy of diverse networks.

“This theory helps us predict how much energy it takes to break these networks by advancing a crack,” says graduate student Chase Hartquist, one of the paper’s lead authors. “It turns out that you can design tougher versions of these materials by making the strands longer, more stretchable, or resistant to higher forces before breaking.”

To validate their results, the team 3D-printed a giant, stretchable network, allowing them to demonstrate fracture properties in practice. They found that despite the differences in the networks, they all followed a simple and predictable rule. Beyond the changes to the strands themselves, a network can also be toughened by connecting the strands into larger loops.

“By adjusting these properties, car tires could last longer, tissues could better resist injury, and spider webs could become more durable,” says Hartquist.

Shu Wang, a postdoc in Zhao’s lab and fellow lead author of the paper, called the research findings “an extremely fulfilling moment ... it meant that the same rules could be applied to describe a wide variety of materials, making it easier to design the best material for a given situation.”

The researchers explain that this work represents progress in an exciting and emerging field called “architected materials,” where the structure within the material itself gives it unique properties. They say the discovery sheds light on how to make these materials even tougher, by focusing on designing the segments within the architecture stronger and more stretchable. The strategy is adaptable for materials across fields and can be applied to improve durability of soft robotic actuators, enhance the toughness of engineered tissues, or even create resilient lattices for aerospace technology.

Their open-access paper, “Scaling Law for Intrinsic Fracture Energy of Diverse Stretchable Networks,” is available now in Physical Review X, a leading journal in interdisciplinary physics.

Bia Adams, a London-based neuropsychologist, former professional ballet dancer, and MIT Open Learning learner, has built her career across decades of diverse, interconnected experiences and an emphasis on lifelong learning. She earned her bachelor’s degree in clinical and behavioral psychology, and then worked as a psychologist and therapist for several years before taking a sabbatical in her late 20s to study at the London Contemporary Dance School and The Royal Ballet — fulfilling a long-time dream.

“In hindsight, I think what drew me most to ballet was not so much the form itself,” says Adams, “but more of a subconscious desire to make sense of my body moving through space and time, my emotions and motivations — all within a discipline that is rigorous, meticulous, and routine-based. It’s an endeavor to make sense of the world and myself.”

After acquiring some dance-related injuries, Adams returned to psychology. She completed an online certificate program specializing in medical neuroscience via Duke University, focusing on how pathology arises out of the way the brain computes information and generates behavior.

In addition to her clinical practice, she has also worked at a data science and AI consultancy for neural network research.

In 2022, in search of new things to learn and apply to both her work and personal life, Adams discovered MIT OpenCourseWare within MIT Open Learning. She was drawn to class 8.04 (Quantum Physics I), which specifically focuses on quantum mechanics, as she was hoping to finally gain some understanding of complex topics that she had tried to teach herself in the past with limited success. She credits the course’s lectures, taught by Allan Adams (physicist and principal investigator of the MIT Future Ocean Lab), with finally making these challenging topics approachable.

“I still talk to my friends at length about exciting moments in these lectures,” says Adams. “After the first class, I was hooked.”

Adams’s journey through MIT Open Learning’s educational resources quickly led to a deeper interest in computational neuroscience. She learned how to use tools from mathematics and computer science to better understand the brain, nervous system, and behavior.

She says she gained many new insights from class 6.034 (Artificial Intelligence), particularly in watching the late Professor Patrick Winston’s lectures. She appreciated learning more about the cognitive psychology aspect of AI, including how pioneers in the field looked at how the brain processes information and aimed to build programs that could solve problems. She further enhanced her understanding of AI with the Minds and Machines course on MITx Online, part of Open Learning.

Adams is now in the process of completing Introduction to Computer Science and Programming Using Python, taught by John Guttag; Eric Grimson, former interim vice president for Open Learning; and Ana Bell.

“I am multilingual, and I think the way my brain processes code is similar to the way computers code,” says Adams. “I find learning to code similar to learning a foreign language: both exhilarating and intimidating. Learning the rules, deciphering the syntax, and building my own world through code is one of the most fascinating challenges of my life.”

Adams is also pursuing a master’s degree at Duke and the University College of London, focusing on the neurobiology of sleep and looking particularly at how the biochemistry of the brain can affect this critical function. As a complement to this research, she is currently exploring class 9.40 (Introduction to Neural Computation), taught by Michale Fee and Daniel Zysman, which introduces quantitative approaches to understanding brain and cognitive functions and neurons and covers foundational quantitative tools of data analysis in neuroscience.

In addition to the courses related more directly to her field, MIT Open Learning also provided Adams an opportunity to explore other academic areas. She delved into philosophy for the first time, taking Paradox and Infinity, taught by Professor Agustín Rayo, the Kenan Sahin Dean of the MIT School of Humanities, Arts, and Social Sciences, and Digital Learning Lab Fellow David Balcarras, which looks at the intersection of philosophy and mathematics. She also was able to explore in more depth immunology, which had always been of great interest to her, through Professor Adam Martin’s lectures on this topic in class 7.016 (Introductory Biology).

“I am forever grateful for MIT Open Learning,” says Adams, “for making knowledge accessible and fostering a network of curious minds, all striving to share, expand, and apply this knowledge for the greater good.”

Faith Brooks, a graduate student in the MIT-WHOI Joint Program, has had a clear dream since the age of 4: to become a pilot.

“At around 8 years old, my neighbor knew I wanted to fly and showed me pictures of her dad landing a jet on an aircraft carrier, and I was immediately captivated,” says Brooks. Further inspired by her grandfather’s experience in the U.S. Navy (USN), and owing to a lifelong fascination with aviation, she knew nothing would stand in her way.

Brooks explored several different paths to becoming a pilot, but she says one conversation with her longtime mentor, Capt. Matt Skone, USN (Ret.), changed the trajectory of her life.

“He asked if I had heard of the Naval Academy,” she recalls. “At the time, I hadn’t … I immediately knew that that was where I wanted to go, and everything else I learned about United States Naval Academy (USNA) reinforced that for me.”

In her “firstie” (senior) year at the USNA, Brooks was selected to go to Pensacola, Florida, and train to become a naval pilot as a student naval aviator, taking her one step closer to her dream. The USNA also helped guide her path to MIT. Her journey to joining the MIT-WHOI Joint Program began with the USNA’s professional knowledge curriculum, where she read about retired Capt. Wendy Lawrence SM ’88, a naval aviator and astronaut.

“Reading her bio prompted me to look into the program, and it sounded like the perfect program for me — where else could you get a better education in ocean engineering than MIT and Woods Hole Oceanographic Institution [WHOI]?”

In the MIT-WHOI Joint Program, Brooks is researching the impact of coastal pond breaching on preventing and mitigating harmful algal blooms. Her work focuses on the biannual mechanical breaching of Nantucket’s Sesachacha Pond to the ocean and the resultant impact on the pond’s water quality. This practice aims to improve water quality and mitigate harmful algal blooms (HABs), especially in summer.

Breaching in coastal ponds is a process that was initially used to enhance salinity for herring and shellfish habitats, but has since shifted to address water quality concerns. Traditionally, an excavator creates a breach in the pond, which naturally closes within one to five days, influenced by sediment transport and weather conditions. High winds and waves can accelerate sediment movement, limiting ocean water exchange and potentially increasing eutrophication, where excessive nutrients lead to dense plant growth and depletion of oxygen. In brackish water environments, harmful algal blooms are often driven by elevated nitrogen levels and higher temperatures, with higher nitrogen concentrating leading to more frequent and severe blooms as temperatures rise.

The Nantucket Natural Resources Department (NRD) has been collaborating with local homeowners to investigate the pond breaching process. Existing data are mainly anecdotal evidence and NRD’s monthly sampling since 2022, which has not shown the expected decrease in eutrophication. Brooks’ research will focus on data before, during, and after the breach at two pond sites to assess water changes to evaluate its effectiveness in improving water quality.

When Brooks isn’t knee-deep in the waters of the Sesachacha or training with her MIT Triathlon team, she takes additional opportunities to further her education. Last year, Brooks participated in the MIT-Portugal Marine Robotics Summer School in Faial, Azores, in Portugal, and immersed herself in a combination of a hands-on design projects and lectures on a variety of topics related to oceanography, engineering, and marine robotics.

“My favorite part of the program was how interdisciplinary it was. We had a combination of mechanical engineers, electrical engineers, computer scientists, marine biologists, and oceanographers, and we had teams that included each of these specialties,” she says. “Our project involved designing a lander equipped with an underwater camera connected to a surface buoy that would transmit the footage. Having worked in mostly just engineering teams previously, it was a great experience to work with a more diverse group and I gained a much better understanding of how to design instruments and systems in accordance with what the marine biologists need.”

Brooks also earned her Part 107 Small Unmanned Aircraft System (UAS) license to operate the lab’s drone with a multispectral camera for her upcoming fieldwork. When she graduates from the MIT-WHOI Joint Program next September, she’ll report to the Naval Aviation Schools Command in Pensacola, Florida, to begin flight training.

While she says she’ll miss Boston’s charm and history, as well as the Shining Sea Bikeway on crisp fall days in Woods Hole, Brooks is looking forward to putting her uniform back on, and starting her naval career and flight school. The time Brooks has spent at MIT will support her in these future endeavors. She advises others interested in a similar path to focus on research within their areas of interest.

“The biggest lesson that I’ve learned from both research theses is that any research project will change over time, and it’s often a good idea to take a step back and look at how your work fits into the larger picture,” she says. “I couldn’t recommend doing research more; it’s such a great opportunity to dig into something that you’re interested in, and is also very fulfilling.” 

According to the International Energy Agency, aviation accounts for about 2 percent of global carbon dioxide emissions, and aviation emissions are expected to double by mid-century as demand for domestic and international air travel rises. To sharply reduce emissions in alignment with the Paris Agreement’s long-term goal to keep global warming below 1.5 degrees Celsius, the International Air Transport Association (IATA) has set a goal to achieve net-zero carbon emissions by 2050. Which raises the question: Are there technologically feasible and economically viable strategies to reach that goal within the next 25 years?

To begin to address that question, a team of researchers at the MIT Center for Sustainability Science and Strategy (CS3) and the MIT Laboratory for Aviation and the Environment has spent the past year analyzing aviation decarbonization options in Latin America, where air travel is expected to more than triple by 2050 and thereby double today’s aviation-related emissions in the region.

Chief among those options is the development and deployment of sustainable aviation fuel. Currently produced from low- and zero-carbon sources (feedstock) including municipal waste and non-food crops, and requiring practically no alteration of aircraft systems or refueling infrastructure, sustainable aviation fuel (SAF) has the potential to perform just as well as petroleum-based jet fuel with as low as 20 percent of its carbon footprint.

Focused on Brazil, Chile, Colombia, Ecuador, Mexico and Peru, the researchers assessed SAF feedstock availability, the costs of corresponding SAF pathways, and how SAF deployment would likely impact fuel use, prices, emissions, and aviation demand in each country. They also explored how efficiency improvements and market-based mechanisms could help the region to reach decarbonization targets. The team’s findings appear in a CS3 Special Report.

SAF emissions, costs, and sources

Under an ambitious emissions mitigation scenario designed to cap global warming at 1.5 C and raise the rate of SAF use in Latin America to 65 percent by 2050, the researchers projected aviation emissions to be reduced by about 60 percent in 2050 compared to a scenario in which existing climate policies are not strengthened. To achieve net-zero emissions by 2050, other measures would be required, such as improvements in operational and air traffic efficiencies, airplane fleet renewal, alternative forms of propulsion, and carbon offsets and removals.

As of 2024, jet fuel prices in Latin America are around $0.70 per liter. Based on the current availability of feedstocks, the researchers projected SAF costs within the six countries studied to range from $1.11 to $2.86 per liter. They cautioned that increased fuel prices could affect operating costs of the aviation sector and overall aviation demand unless strategies to manage price increases are implemented.

Under the 1.5 C scenario, the total cumulative capital investments required to build new SAF producing plants between 2025 and 2050 were estimated at $204 billion for the six countries (ranging from $5 billion in Ecuador to $84 billion in Brazil). The researchers identified sugarcane- and corn-based ethanol-to-jet fuel, palm oil- and soybean-based hydro-processed esters and fatty acids as the most promising feedstock sources in the near term for SAF production in Latin America.

“Our findings show that SAF offers a significant decarbonization pathway, which must be combined with an economy-wide emissions mitigation policy that uses market-based mechanisms to offset the remaining emissions,” says Sergey Paltsev, lead author of the report, MIT CS3 deputy director, and senior research scientist at the MIT Energy Initiative.

Recommendations

The researchers concluded the report with recommendations for national policymakers and aviation industry leaders in Latin America.

They stressed that government policy and regulatory mechanisms will be needed to create sufficient conditions to attract SAF investments in the region and make SAF commercially viable as the aviation industry decarbonizes operations. Without appropriate policy frameworks, SAF requirements will affect the cost of air travel. For fuel producers, stable, long-term-oriented policies and regulations will be needed to create robust supply chains, build demand for establishing economies of scale, and develop innovative pathways for producing SAF.

Finally, the research team recommended a region-wide collaboration in designing SAF policies. A unified decarbonization strategy among all countries in the region will help ensure competitiveness, economies of scale, and achievement of long-term carbon emissions-reduction goals.

“Regional feedstock availability and costs make Latin America a potential major player in SAF production,” says Angelo Gurgel, a principal research scientist at MIT CS3 and co-author of the study. “SAF requirements, combined with government support mechanisms, will ensure sustainable decarbonization while enhancing the region’s connectivity and the ability of disadvantaged communities to access air transport.”

Financial support for this study was provided by LATAM Airlines and Airbus.