When you’re challenging a century-old assumption, you’re bound to meet a bit of resistance. That’s exactly what John Joannopoulos and his group at MIT faced in 1998, when they put forth a new theory on how materials can be made to bend light in entirely new ways.

“Because it was such a big difference in what people expected, we wrote down the theory for this, but it was very difficult to get it published,” Joannopoulos told a capacity crowd in MIT’s Huntington Hall on Friday, as he delivered MIT’s James R. Killian, Jr. Faculty Achievement Award Lecture.

Joannopoulos’ theory offered a new take on a type of material known as a one-dimensional photonic crystal. Photonic crystals are made from alternating layers of refractive structures whose arrangement can influence how incoming light is reflected or absorbed.

In 1887, the English physicist John William Strutt, better known as the Lord Rayleigh, established a theory for how light should bend through a similar structure composed of multiple refractive layers. Rayleigh predicted that such a structure could reflect light, but only if that light is coming from a very specific angle. In other words, such a structure could act as a mirror for light shining from a specific direction only.

More than a century later, Joannopoulos and his group found that, in fact, quite the opposite was true. They proved in theoretical terms that, if a one-dimensional photonic crystal were made from layers of materials with certain “refractive indices,” bending light to different degrees, then the crystal as a whole should be able to reflect light coming from any and all directions. Such an arrangement could act as a “perfect mirror.”

The idea was a huge departure from what scientists had long assumed, and as such, when Joannopoulos submitted the research for peer review, it took some time for the journal, and the community, to come around. But he and his students kept at it, ultimately verifying the theory with experiments.

That work led to a high-profile publication, which helped the group focus the idea into a device: Using the principles that they laid out, they effectively fabricated a perfect mirror and folded it into a tube to form a hollow-core fiber. When they shone light through, the inside of the fiber reflected all the light, trapping it entirely in the core as the light pinged through the fiber. In 2000, the team launched a startup to further develop the fiber into a flexible, highly precise and minimally invasive “photonics scalpel,” which has since been used in hundreds of thousands of medical procedures including a surgeries of the brain and spine.

“And get this: We have estimated more than 500,000 procedures across hospitals in the U.S. and abroad,” Joannopoulos proudly stated, to appreciative applause.

Joannopoulos is the recipient of the 2024-2025 James R. Killian, Jr. Faculty Achievement Award, and is the Francis Wright Davis Professor of Physics and director of the Institute for Soldier Nanotechnologies at MIT. In response to an audience member who asked what motivated him in the face of initial skepticism, he replied, “You have to persevere if you believe what you have is correct.”

Immeasurable impact

The Killian Award was established in 1971 to honor MIT’s 10th president, James Killian. Each year, a member of the MIT faculty is honored with the award in recognition of their extraordinary professional accomplishments.

Joannopoulos received his PhD from the University of California at Berkeley in 1974, then immediately joined MIT’s physics faculty. In introducing his lecture, Mary Fuller, professor of literature and chair of the MIT faculty, noted: “If you do the math, you’ll know he just celebrated 50 years at MIT.” Throughout that remarkable tenure, Fuller noted Joannopoulos’ profound impact on generations of MIT students.

“We recognize you as a leader, a visionary scientist, beloved mentor, and a believer in the goodness of people,” Fuller said. “Your legendary impact at MIT and the broader scientific community is immeasurable.”

Bending light

In his lecture, which he titled “Working at the Speed of Light,” Joannopoulos took the audience through the basic concepts underlying photonic crystals, and the ways in which he and others have shown that these materials can bend and twist incoming light in a controlled way.

As he described it, photonic crystals are “artificial materials” that can be designed to influence the properties of photons in a way that’s similar to how physical features in semiconductors affect the flow of electrons. In the case of semiconductors, such materials have a specific “band gap,” or a range of energies in which electrons cannot exist.

In the 1990s, Joannopoulos and others wondered whether the same effects could be realized for optical materials, to intentionally reflect, or keep out, some kinds of light while letting others through. And even more intriguing: Could a single material be designed such that incoming light pinballs away from certain regions in a material in predesigned paths?

“The answer was a resounding yes,” he said.

Joannopoulos described the excitement within the emerging field by quoting an editor from the journal Nature, who wrote at the time: “If only it were possible to make materials in which electromagnetic waves cannot propagate at certain frequencies, all kinds of almost-magical things would be possible.”

Joannopoulos and his group at MIT began in earnest to elucidate the ways in which light interacts with matter and air. The team worked first with two-dimensional photonic crystals made from a horizontal matrix-like pattern of silicon dots surrounded by air. Silicon has a high refractive index, meaning it can greatly bend or reflect light, while air has a much lower index. Joannopoulos predicted that the silicon could be patterned to ping light away, forcing it to travel through the air in predetermined paths.

In multiple works, he and his students showed through theory and experiments that they could design photonic crystals to, for instance, bend incoming light by 90 degrees and force light to circulate only at the edges of a crystal under an applied magnetic field.

“Over the years there have been quite a few examples we’ve discovered of very anomalous, strange behavior of light that cannot exist in normal objects,” he said.

In 1998, after showing that light can be reflected from all directions from a stacked, one-dimensional photonic crystal, he and his students rolled the crystal structure into a fiber, which they tested in a lab. In a video that Joannopoulos played for the audience, a student carefully aimed the end of the long, flexible fiber at a sheet of material made from the same material as the fiber’s casing. As light pumped through the multilayered photonic lining of the fiber and out the other end, the student used the light to slowly etch a smiley face design in the sheet, drawing laughter from the crowd.

As the video demonstrated, although the light was intense enough to melt the material of the fiber’s coating, it was nevertheless entirely contained within the fiber’s core, thanks to the multilayered design of its photonic lining. What’s more, the light was focused enough to make precise patterns when it shone out of the fiber.

“We had originally developed this [optical fiber] as a military device,” Joannopoulos said. “But then the obvious choice to use it for the civilian population was quite clear.”

“Believing in the goodness of people and what they can do”

He and others co-founded Omniguide in 2000, which has since grown into a medical device company that develops and commercializes minimally invasive surgical tools such as the fiber-based “photonics scalpel.” In illustrating the fiber’s impact, Joannopoulos played a news video, highlighting the fiber’s use in performing precise and effective neurosurgery. The optical scalpel has also been used to perform procedures in larynology, head and neck surgery, and gynecology, along with brain and spinal surgeries.

Omniguide is one of several startups that Joannopoulos has helped found, along with Luminus Devices, Inc., WiTricity Corporation, Typhoon HIL, Inc., and Lightelligence. He is author or co-author of over 750 refereed journal articles, four textbooks, and 126 issued U.S. patents. He has earned numerous recognitions and awards, including his election to the National Academy of Sciences and the American Academy of Arts and Sciences.

The Killian Award citation states: “Professor Joannopoulos has been a consistent role model not just in what he does, but in how he does it. … Through all these individuals he has impacted — not to mention their academic descendants — Professor Joannopoulos has had a vast influence on the development of science in recent decades.”

At the end of the talk, Yoel Fink, Joannopoulos’ former student and frequent collaborator, who is now professor of materials science, asked Joannopoulos how, particularly in current times, he has been able to “maintain such a positive and optimistic outlook, of humans and human nature.”

“It’s a matter of believing in the goodness of people and what they can do, what they accomplish, and giving an environment where they’re working in, where they feel extermely comfortable,” Joannopoulos offered. “That includes creating a sense of trust between the faculty and the students, which is key. That helps enormously.”

Olivier Blanchard PhD ’77, the Robert M. Solow Professor of Economics Emeritus, has been named a winner of the 2025 BBVA Foundation Frontiers of Knowledge Award in Economics, Finance and Management for “profoundly influencing modern macroeconomic analysis by establishing rigorous foundations for the study of business cycle fluctuations,” as described in the BBVA Foundation’s award citation.

Blanchard, who is also senior fellow at the Peterson Institute for International Economics, shares the award with MIT alumni Jordi Galí PhD ’89 of the Centre de Recerca en Economia Internacional and Pompeu Fabra University in Spain and Michael Woodford PhD ’83 of Columbia University. The three economists were instrumental in developing the New Keynesian model, now widely taught and applied in central banking policy around the world.

The framework builds on classical Keynesian models in part by introducing the role of consumer expectations to macroeconomic policy analysis — in short, using the public’s perception of the future to help inform current policy. The model’s unconventional tools, including greater transparency around monetary policy, were tested by policymakers following the burst of the dotcom bubble in the early 2000s and applied by the Federal Reserve and European Central Bank in response to the 2008 financial crisis.

Blanchard played a foundational role in the development of New Keynesian economics, beginning with a 1987 paper coauthored with Princeton University’s Nobuhiro Kiyotaki (also a Frontiers of Knowledge laureate) on the effects of monetary policy under monopolistic competition. A decade later, Woodford described optimal monetary policy within the New Keynesian framework, laying key theoretical groundwork for the model, and Galí extended and synthesized the framework, ultimately resulting in a blueprint for designing optimal monetary policy.

Blanchard, who joined the MIT faculty in 1983 and served as head of the Department of Economics from 1998 to 2003, advised and taught decades of macroeconomics students at MIT, including Galí. As chief economist of the International Monetary Fund from 2008 to 2015, Blanchard used his framework to help design policy during the Global Financial Crisis and the Euro debt crisis. Blanchard’s leadership as a scholar, student advisor, teacher, and policy advisor is at the heart of the trio’s prize-winning research.

MIT Professor Jonathan Gruber, current head of the economics department, praises Blanchard’s multifaceted contributions.

“Olivier is not only an amazing macroeconomist whose work continues to have profound influence in this time of global macroeconomic uncertainty,” says Gruber, “but also a pillar of the department. His leadership in research and enormous dedication to our program were central in carrying forward the legacy of the department’s early greats and making MIT Economics what it is today.”

Blanchard, Galí, and Woodford share the award’s 400,000-euro prize and will be formally honored at a ceremony in Bilbao, Spain, in June.

The BBVA Foundation works to support scientific research and cultural creation, disseminate knowledge and culture, and recognize talent and innovation, focusing on five strategic areas: environment, biomedicine and health, economy and society, basic sciences and technology, and culture. The Frontiers of Knowledge Awards, spanning eight prize categories, recognize world-class research and cultural creation and aim to celebrate and promote the value of knowledge as a global public good.

Since 2009, the BBVA has given awards to more than a dozen MIT faculty members, including MIT economist Daron Acemoglu, as well as to the Abdul Latif Jameel Poverty Action Lab (J-PAL), led by MIT economists Abhijit Banerjee, Esther Duflo, and Ben Olken.

We move thanks to coordination among many skeletal muscle fibers, all twitching and pulling in sync. While some muscles align in one direction, others form intricate patterns, helping parts of the body move in multiple ways.

In recent years, scientists and engineers have looked to muscles as potential actuators for “biohybrid” robots — machines powered by soft, artificially grown muscle fibers. Such bio-bots could squirm and wiggle through spaces where traditional machines cannot. For the most part, however, researchers have only been able to fabricate artificial muscle that pulls in one direction, limiting any robot’s range of motion.

Now MIT engineers have developed a method to grow artificial muscle tissue that twitches and flexes in multiple coordinated directions. As a demonstration, they grew an artificial, muscle-powered structure that pulls both concentrically and radially, much like how the iris in the human eye acts to dilate and constrict the pupil.

The researchers fabricated the artificial iris using a new “stamping” approach they developed. First, they 3D-printed a small, handheld stamp patterned with microscopic grooves, each as small as a single cell. Then they pressed the stamp into a soft hydrogel and seeded the resulting grooves with real muscle cells. The cells grew along these grooves within the hydrogel, forming fibers. When the researchers stimulated the fibers, the muscle contracted in multiple directions, following the fibers’ orientation.

“With the iris design, we believe we have demonstrated the first skeletal muscle-powered robot that generates force in more than one direction. That was uniquely enabled by this stamp approach,” says Ritu Raman, the Eugene Bell Career Development Professor of Tissue Engineering in MIT’s Department of Mechanical Engineering.

The team says the stamp can be printed using tabletop 3D printers and fitted with different patterns of microscopic grooves. The stamp can be used to grow complex patterns of muscle — and potentially other types of biological tissues, such as neurons and heart cells — that look and act like their natural counterparts.

“We want to make tissues that replicate the architectural complexity of real tissues,” Raman says. “To do that, you really need this kind of precision in your fabrication.”

She and her colleagues published their open-access results Friday in the journal Biomaterials Science. Her MIT co-authors include first author Tamara Rossy, Laura Schwendeman, Sonika Kohli, Maheera Bawa, and Pavankumar Umashankar, along with Roi Habba, Oren Tchaicheeyan, and Ayelet Lesman of Tel Aviv University in Israel.

Training space

Raman’s lab at MIT aims to engineer biological materials that mimic the sensing, activity, and responsiveness of real tissues in the body. Broadly, her group seeks to apply these bioengineered materials in areas from medicine to machines. For instance, she is looking to fabricate artificial tissue that can restore function to people with neuromuscular injury. She is also exploring artificial muscles for use in soft robotics, such as muscle-powered swimmers that move through the water with fish-like flexibility.

Raman has previously developed what could be seen as gym platforms and workout routines for lab-grown muscle cells. She and her colleagues designed a hydrogel “mat” that encourages muscle cells to grow and fuse into fibers without peeling away. She also derived a way to “exercise” the cells by genetically engineering them to twitch in response to pulses of light. And, her group has come up with ways to direct muscle cells to grow in long, parallel lines, similar to natural, striated muscles. However, it’s been a challenge, for her group and others, to design artificial muscle tissue that moves in multiple, predictable directions.

“One of the cool things about natural muscle tissues is, they don’t just point in one direction. Take for instance, the circular musculature in our iris and around our trachea. And even within our arms and legs, muscle cells don’t point straight, but at an angle,” Raman notes. “Natural muscle has multiple orientations in the tissue, but we haven’t been able to replicate that in our engineered muscles.”

Muscle blueprint

In thinking of ways to grow multidirectional muscle tissue, the team hit on a surprisingly simple idea: stamps. Inspired in part by the classic Jell-O mold, the team looked to design a stamp, with microscopic patterns that could be imprinted into a hydrogel, similar to the muscle-training mats that the group has previously developed. The patterns of the imprinted mat could then serve as a roadmap along which muscle cells might follow and grow.

“The idea is simple. But how do you make a stamp with features as small as a single cell? And how do you stamp something that’s super soft? This gel is much softer than Jell-O, and it’s something that’s really hard to cast, because it could tear really easily,” Raman says.

The team tried variations on the stamp design and eventually landed on an approach that worked surprisingly well. The researchers fabricated a small, handheld stamp using high-precision printing facilities in MIT.nano, which enabled them to print intricate patterns of grooves, each about as wide as a single muscle cell, onto the bottom of the stamp. Before pressing the stamp into a hydrogel mat, they coated the bottom with a protein that helped the stamp imprint evenly into the gel and peel away without sticking or tearing.

As a demonstration, the researchers printed a stamp with a pattern similar to the microscopic musculature in the human iris. The iris comprises a ring of muscle surrounding the pupil. This ring of muscle is made up of an inner circle of muscle fibers arranged concentrically, following a circular pattern, and an outer circle of fibers that stretch out radially, like the rays of the sun.  Together, this complex architecture acts to constrict or dilate the pupil.

Once Raman and her colleagues pressed the iris pattern into a hydrogel mat, they coated the mat with cells that they genetically engineered to respond to light. Within a day, the cells fell into the microscopic grooves and began to fuse into fibers, following the iris-like patterns and eventually growing into a whole muscle, with an architecture and size similar to a real iris.

When the team stimulated the artificial iris with pulses of light, the muscle contracted in multiple directions, similar to the iris in the human eye. Raman notes that the team’s artificial iris is fabricated with skeletal muscle cells, which are involved in voluntary motion, whereas the muscle tissue in the real human iris is made up of smooth muscle cells, which are a type of involuntary muscle tissue. They chose to pattern skeletal muscle cells in an iris-like pattern to demonstrate the ability to fabricate complex, multidirectional muscle tissue.

“In this work, we wanted to show we can use this stamp approach to make a ‘robot’ that can do things that previous muscle-powered robots can’t do,” Raman says. “We chose to work with skeletal muscle cells. But there’s nothing stopping you from doing this with any other cell type.”

She notes that while the team used precision-printing techniques, the stamp design can also be made using conventional tabletop 3D printers. Going forward, she and her colleagues plan to apply the stamping method to other cell types, as well as explore different muscle architectures and ways to activate artificial, multidirectional muscle to do useful work.

“Instead of using rigid actuators that are typical in underwater robots, if we can use soft biological robots, we can navigate and be much more energy-efficient, while also being completely biodegradable and sustainable,” Raman says. “That’s what we hope to build toward.”

This work was supported, in part, by the U.S. Office of Naval Research, the U.S. Army Research Office, the U.S. National Science Foundation, and the U.S. National Institutes of Health.

A decade after scientists in The Picower Institute for Learning and Memory at MIT first began testing whether sensory stimulation of the brain’s 40Hz “gamma” frequency rhythms could treat Alzheimer’s disease in mice, a growing evidence base supporting the idea that it can improve brain health — in humans as well as animals — has emerged from the work of labs all over the world. A new open-access review article in PLOS Biology describes the state of research so far and presents some of the fundamental and clinical questions at the forefront of the noninvasive gamma stimulation now.

“As we’ve made all our observations, many other people in the field have published results that are very consistent,” says Li-Huei Tsai, Picower professor of neuroscience at MIT, director of MIT’s Aging Brain Initiative, and senior author of the new review, with postdoc Jung Park. “People have used many different ways to induce gamma including sensory stimulation, transcranial alternating current stimulation, or transcranial magnetic stimulation, but the key is delivering stimulation at 40 hertz. They all see beneficial effects.”

A decade of discovery at MIT

Starting with a paper in Nature in 2016, a collaboration led by Tsai has produced a series of studies showing that 40Hz stimulation via light, sound, the two combined, or tactile vibration reduces hallmarks of Alzheimer’s pathology such as amyloid and tau proteins, prevents neuron death, decreases synapse loss, and sustains memory and cognition in various Alzheimer’s mouse models. The collaboration’s investigations of the underlying mechanisms that produce these benefits have so far identified specific cellular and molecular responses in many brain cell types including neurons, microglia, astrocytes, oligodendrocytes, and the brain’s blood vessels. Last year, for instance, the lab reported in Nature that 40Hz audio and visual stimulation induced interneurons in mice to increase release of the peptide VIP, prompting increased clearance of amyloid from brain tissue via the brain’s glymphatic “plumbing” system.

Meanwhile, at MIT and at the MIT spinoff company Cognito Therapeutics, phase II clinical studies have shown that people with Alzheimer’s exposed to 40Hz light and sound experienced a significant slowing of brain atrophy and improvements on some cognitive measures, compared to untreated controls. Cognito, which has also measured significant preservation of the brain’s “white matter” in volunteers, has been conducting a pivotal, nationwide phase III clinical trial of sensory gamma stimulation for more than a year.

“Neuroscientists often lament that it is a great time to have AD [Alzheimer’s disease] if you are a mouse,” Park and Tsai wrote in the review. “Our ultimate goal, therefore, is to translate GENUS discoveries into a safe, accessible, and noninvasive therapy for AD patients.” The MIT team often refers to 40Hz stimulation as “GENUS” for Gamma Entrainment Using Sensory Stimulation.

A growing field

As Tsai’s collaboration, which includes MIT colleagues Edward Boyden and Emery N. Brown, has published its results, many other labs have produced studies adding to the evidence that various methods of noninvasive gamma sensory stimulation can combat Alzheimer’s pathology. Among many examples cited in the new review, in 2024 a research team in China independently corroborated that 40Hz sensory stimulation increases glymphatic fluid flows in mice. In another example, a Harvard Medical School-based team in 2022 showed that 40Hz gamma stimulation using Transcranial Alternating Current Stimulation significantly reduced the burden of tau in three out of four human volunteers. And in another study involving more than 100 people, researchers in Scotland in 2023 used audio and visual gamma stimulation (at 37.5Hz) to improve memory recall.

Open questions

Amid the growing number of publications describing preclinical studies with mice and clinical trials with people, open questions remain, Tsai and Park acknowledge. The MIT team and others are still exploring the cellular and molecular mechanisms that underlie GENUS’s effects. Tsai says her lab is looking at other neuropeptide and neuromodulatory systems to better understand the cascade of events linking sensory stimulation to the observed cellular responses. Meanwhile, the nature of how some cells, such as microglia, respond to gamma stimulation and how that affects pathology remains unclear, Tsai adds.

Even with a national phase III clinical trial underway, it is still important to investigate these fundamental mechanisms, Tsai says, because new insights into how noninvasive gamma stimulation affects the brain could improve and expand its therapeutic potential.

“The more we understand the mechanisms, the more we will have good ideas about how to further optimize the treatment,” Tsai says. “And the more we understand its action and the circuits it affects, the more we will know beyond Alzheimer’s disease what other neurological disorders will benefit from this.”

Indeed, the review points to studies at MIT and other institutions providing at least some evidence that GENUS might be able to help with Parkinson’s disease, stroke, anxiety, epilepsy, and the cognitive side effects of chemotherapy and conditions that reduce myelin, such as multiple sclerosis. Tsai’s lab has been studying whether it can help with Down syndrome as well.

The open questions may help define the next decade of GENUS research.

It is a deep question, from deep in our history: When did human language as we know it emerge? A new survey of genomic evidence suggests our unique language capacity was present at least 135,000 years ago. Subsequently, language might have entered social use 100,000 years ago.

Our species, Homo sapiens, is about 230,000 years old. Estimates of when language originated vary widely, based on different forms of evidence, from fossils to cultural artifacts. The authors of the new analysis took a different approach. They reasoned that since all human languages likely have a common origin — as the researchers strongly think — the key question is how far back in time regional groups began spreading around the world.

“The logic is very simple,” says Shigeru Miyagawa, an MIT professor and co-author of a new paper summarizing the results. “Every population branching across the globe has human language, and all languages are related.” Based on what the genomics data indicate about the geographic divergence of early human populations, he adds, “I think we can say with a fair amount of certainty that the first split occurred about 135,000 years ago, so human language capacity must have been present by then, or before.”

The paper, “Linguistic capacity was present in the Homo sapiens population 135 thousand years ago,” appears in Frontiers in Psychology. The co-authors are Miyagawa, who is a professor emeritus of linguistics and the Kochi-Manjiro Professor of Japanese Language and Culture at MIT; Rob DeSalle, a principal investigator at the American Museum of Natural History’s Institute for Comparative Genomics; Vitor Augusto Nóbrega, a faculty member in linguistics at the University of São Paolo; Remo Nitschke, of the University of Zurich, who worked on the project while at the University of Arizona linguistics department; Mercedes Okumura of the Department of Genetics and Evolutionary Biology at the University of São Paulo; and Ian Tattersall, curator emeritus of human origins at the American Museum of Natural History.

The new paper examines 15 genetic studies of different varieties, published over the past 18 years: Three used data about the inherited Y chromosome, three examined mitochondrial DNA, and nine were whole-genome studies.

All told, the data from these studies suggest an initial regional branching of humans about 135,000 years ago. That is, after the emergence of Homo sapiens, groups of people subsequently moved apart geographically, and some resulting genetic variations have developed, over time, among the different regional subpopulations. The amount of genetic variation shown in the studies allows researchers to estimate the point in time at which Homo sapiens was still one regionally undivided group.

Miyagawa says the studies collectively provide increasingly converging evidence about when these geographic splits started taking place. The first survey of this type was performed by other scholars in 2017, but they had fewer existing genetic studies to draw upon. Now, there are much more published data available, which when considered together point to 135,000 years ago as the likely time of the first split.

The new meta-analysis was possible because “quantity-wise we have more studies, and quality-wise, it’s a narrower window [of time],” says Miyagawa, who also holds an appointment at the University of São Paolo.

Like many linguists, Miyagawa believes all human languages are demonstrably related to each other, something he has examined in his own work. For instance, in his 2010 book, “Why Agree? Why Move?” he analyzed previously unexplored similarities between English, Japanese, and some of the Bantu languages. There are more than 7,000 identified human languages around the globe.

Some scholars have proposed that language capacity dates back a couple of million years, based on the physiological characteristics of other primates. But to Miyagawa, the question is not when primates could utter certain sounds; it is when humans had the cognitive ability to develop language as we know it, combining vocabulary and grammar into a system generating an infinite amount of rules-based expression.

“Human language is qualitatively different because there are two things, words and syntax, working together to create this very complex system,” Miyagawa says. “No other animal has a parallel structure in their communication system. And that gives us the ability to generate very sophisticated thoughts and to communicate them to others.”

This conception of human language origins also holds that humans had the cognitive capacity for language for some period of time before we constructed our first languages.

“Language is both a cognitive system and a communication system,” Miyagawa says. “My guess is prior to 135,000 years ago, it did start out as a private cognitive system, but relatively quickly that turned into a communications system.”

So, how can we know when distinctively human language was first used? The archaeological record is invaluable in this regard. Roughly 100,000 years ago, the evidence shows, there was a widespread appearance of symbolic activity, from meaningful markings on objects to the use of fire to produce ochre, a decorative red color.

Like our complex, highly generative language, these symbolic activities are engaged in by people, and no other creatures. As the paper notes, “behaviors compatible with language and the consistent exercise of symbolic thinking are detectable only in the archaeological record of H. sapiens.”

Among the co-authors, Tattersall has most prominently propounded the view that language served as a kind of ignition for symbolic thinking and other organized activities.

“Language was the trigger for modern human behavior,” Miyagawa says. “Somehow it stimulated human thinking and helped create these kinds of behaviors. If we are right, people were learning from each other [due to language] and encouraging innovations of the types we saw 100,000 years ago.”

To be sure, as the authors acknowledge in the paper, other scholars believe there was a more incremental and broad-based development of new activities around 100,000 years ago, involving materials, tools, and social coordination, with language playing a role in this, but not necessarily being the central force.

For his part, Miyagawa recognizes that there is considerable room for further progress in this area of research, but thinks efforts like the current paper are at least steps toward filling out a more detailed picture of language’s emergence.

“Our approach is very empirically based, grounded in the latest genetic understanding of early homo sapiens,” Miyagawa says. “I think we are on a good research arc, and I hope this will encourage people to look more at human language and evolution.”

This research was, in part, supported by the São Paolo Excellence Chair awarded to Miyagawa by the São Paolo Research Foundation.

More than 60,000 tons of plastic makes the journey down the Amazon River to the Atlantic Ocean every year. And that doesn’t include what finds its way to the river’s banks, or the microplastics ingested by the region’s abundant and diverse wildlife.

It’s easy to demonize plastic, but it has been crucial in developing the society we live in today. Creating materials that have the benefits of plastics while reducing the harms of traditional production methods is a goal of chemical engineering and materials science labs the world over, including that of Bradley Olsen, the Alexander and I. Michael Kasser (1960) Professor of Chemical Engineering at MIT.

Olsen, a Fulbright Amazonia scholar and the faculty lead of MIT-Brazil, works with communities to develop alternative plastics solutions that can be derived from resources within their own environments.

“The word that we use for this is co-design,” says Olsen. “The idea is, instead of engineers just designing something independently, they engage and jointly design the solution with the stakeholders.”

In this case, the stakeholders were small businesses around Manaus in the Brazilian state of Amazonas curious about the feasibility of bioplastics and other alternative packaging.

“Plastics are inherent to modern life and actually perform key functions and have a really beautiful chemistry that we want to be able to continue to leverage, but we want to do it in a way that is more earth-compatible,” says Desirée Plata, MIT associate professor of civil and environmental engineering.

That’s why Plata joined Olsen in creating the course 1.096/10.496 (Design of Sustainable Polymer Systems) in 2021. Now, as a Global Classroom offering under the umbrella of MISTI since 2023, the class brings MIT students to Manaus during the three weeks of Independent Activities Period (IAP).

“In my work running the Global Teaching Labs in Brazil since 2016, MIT students collaborate closely with Brazilian undergraduates,” says Rosabelli Coelho-Keyssar, managing director of MIT-Brazil and MIT-Amazonia, who also runs MIT’s Global Teaching Labs program in Brazil. “This peer-learning model was incorporated into the Global Classroom in Manaus, ensuring that MIT and Brazilian students worked together throughout the course.”

The class leadership worked with climate scientist and MIT alumnus Carlos Nobre PhD ’83, who facilitated introductions to faculty at the Universidade Estadual de Amazonas (UAE), the state university of Amazonas. The group then scouted businesses in the Amazonas region who would be interested in partnering with the students.

“In the first year, it was Comunidade Julião, a community of people living on the edge of the Tarumã Mirim River west of Manaus,” says Olsen. “This year, we worked with Comunidade Para Maravilha, a community living in the dry land forest east of Manaus.”

A tailored solution

Plastic, by definition, is made up of many small carbon-based molecules, called monomers, linked by strong bonds into larger molecules called polymers. Linking different monomers and polymers in different ways creates different plastics — from trash bags to a swimming pool float to the dashboard of a car. Plastics are traditionally made from petroleum byproducts that are easy to link together, stable, and plentiful.

But there are ways to reduce the use of petroleum-based plastics. Packaging can be made from materials found within the local ecosystem, as was the focus of the 2024 class. Or carbon-based monomers can be extracted from high-starch plant matter through a number of techniques, the goal of the 2025 cohort. But plants that grow well in one location might not in another. And bioplastic production facilities can be tricky to install if the necessary resources aren’t immediately available.

“We can design a whole bunch of new sustainable chemical processes, use brand new top-of-the-line catalysts, but if you can’t actually implement them sustainably inside an environment, it falls short on a lot of the overall goals,” says Brian Carrick, a PhD candidate in the Olsen lab and a teaching assistant for the 2025 course offering.

So, identifying local candidates and tailoring the process is key. The 2025 MIT cohort collaborated with students from throughout the Amazonas state to explore the local flora, study its starch content in the lab, and develop a new plastic-making process — all within the three weeks of IAP.

“It’s easy when you have projects like this to get really locked into the MIT vacuum of just doing what sounds really cool, which isn’t always effective or constructive for people actually living in that environment,” says Claire Underwood, a junior chemical-biological engineering major who took the class. “That’s what really drew me into the project, being able to work with people in Brazil.”

The 31 students visited a protected area of the Amazon rainforest on Day One. They also had chances throughout IAP to visit the Amazon River, where the potential impact of their work became clear as they saw plastic waste collecting on its banks.

“That was a really cool aspect to the class, for sure, being able to actually see what we were working towards protecting and what the goal was,” says Underwood.

They interviewed stakeholders, such as farmers who could provide the feedstock and plastics manufacturers who could incorporate new techniques. Then, they got into the classroom, where massive intellectual ground was covered in a crash course on the sustainable design process, the nitty gritty of plastic production, and the Brazilian cultural context on how building such an industry would affect the community. For the final project, they separated into teams to craft preliminary designs of process and plant using a simplified model of these systems.

Connecting across boundaries

Working in another country brought to the fore how interlinked policy, culture, and technical solutions are.

“I know nothing about economics, and especially not Brazilian economics and politics,” says Underwood. But one of the Brazilian students in her group was a management and finance major. “He was super helpful when we were trying to source things and account for inflation and things like that — knowing what was feasible, and not just academically feasible.”

Before they parted at the end of IAP, each team presented their proposals to a panel of company representatives and Brazilian MIT alumni who chose first-, second-, and third-place winners. While more research is needed before comfortably implementing the ideas, the experience seemed to generate legitimate interest in creating a local bioplastics production facility.

Understanding sustainable design concepts and how to do interdisciplinary work is an important skill to learn. Even if these students don’t wind up working on bioplastics in the heart of the Amazon, being able to work with people of different perspectives — be it a different discipline or a different culture — is valuable in virtually every field.

“The exchange of knowledge across different fields and cultures is essential for developing innovative and sustainable solutions to global challenges such as climate change, waste management, and the development of eco-friendly materials,” says Taisa Sampaio, a PhD candidate in materials chemistry at UEA and a co-instructor for the course. “Programs like this are crucial in preparing professionals who are more aware and better equipped to tackle future challenges.”

Right now, Olsen and Plata are focused on harnessing the deep well of connections and resources they have around Manaus, but they hope to develop that kind of network elsewhere to expand this sustainable design exploration to other regions of the world.

“A lot of sustainability solutions are hyperlocal,” says Plata. “Understanding that not all locales are exactly the same is really powerful and important when we’re thinking about sustainability challenges. And it’s probably where we've gone wrong with the one-size-fits-all or silver-bullet solution — seeking that we’ve been doing for the past many decades.”

Collaborations for the 2026 trip are still in development but, as Olsen says, “we hope this is an experience we can continue to offer long into the future, based on how positive it has been for our students and our Brazilian partners.”

Many companies invest heavily in hiring talent to create the high-performance library code that underpins modern artificial intelligence systems. NVIDIA, for instance, developed some of the most advanced high-performance computing (HPC) libraries, creating a competitive moat that has proven difficult for others to breach.

But what if a couple of students, within a few months, could compete with state-of-the-art HPC libraries with a few hundred lines of code, instead of tens or hundreds of thousands?

That’s what researchers at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) have shown with a new programming language called Exo 2.

Exo 2 belongs to a new category of programming languages that MIT Professor Jonathan Ragan-Kelley calls “user-schedulable languages” (USLs). Instead of hoping that an opaque compiler will auto-generate the fastest possible code, USLs put programmers in the driver's seat, allowing them to write “schedules” that explicitly control how the compiler generates code. This enables performance engineers to transform simple programs that specify what they want to compute into complex programs that do the same thing as the original specification, but much, much faster.

One of the limitations of existing USLs (like the original Exo) is their relatively fixed set of scheduling operations, which makes it difficult to reuse scheduling code across different “kernels” (the individual components in a high-performance library).

In contrast, Exo 2 enables users to define new scheduling operations externally to the compiler, facilitating the creation of reusable scheduling libraries. Lead author Yuka Ikarashi, an MIT PhD student in electrical engineering and computer science and CSAIL affiliate, says that Exo 2 can reduce total schedule code by a factor of 100 and deliver performance competitive with state-of-the-art implementations on multiple different platforms, including Basic Linear Algebra Subprograms (BLAS) that power many machine learning applications. This makes it an attractive option for engineers in HPC focused on optimizing kernels across different operations, data types, and target architectures.

“It’s a bottom-up approach to automation, rather than doing an ML/AI search over high-performance code,” says Ikarashi. “What that means is that performance engineers and hardware implementers can write their own scheduling library, which is a set of optimization techniques to apply on their hardware to reach the peak performance.”

One major advantage of Exo 2 is that it reduces the amount of coding effort needed at any one time by reusing the scheduling code across applications and hardware targets. The researchers implemented a scheduling library with roughly 2,000 lines of code in Exo 2, encapsulating reusable optimizations that are linear-algebra specific and target-specific (AVX512, AVX2, Neon, and Gemmini hardware accelerators). This library consolidates scheduling efforts across more than 80 high-performance kernels with up to a dozen lines of code each, delivering performance comparable to, or better than, MKL, OpenBLAS, BLIS, and Halide.

Exo 2 includes a novel mechanism called “Cursors” that provides what they call a “stable reference” for pointing at the object code throughout the scheduling process. Ikarashi says that a stable reference is essential for users to encapsulate schedules within a library function, as it renders the scheduling code independent of object-code transformations.

“We believe that USLs should be designed to be user-extensible, rather than having a fixed set of operations,” says Ikarashi. “In this way, a language can grow to support large projects through the implementation of libraries that accommodate diverse optimization requirements and application domains.”

Exo 2’s design allows performance engineers to focus on high-level optimization strategies while ensuring that the underlying object code remains functionally equivalent through the use of safe primitives. In the future, the team hopes to expand Exo 2’s support for different types of hardware accelerators, like GPUs. Several ongoing projects aim to improve the compiler analysis itself, in terms of correctness, compilation time, and expressivity.

Ikarashi and Ragan-Kelley co-authored the paper with graduate students Kevin Qian and Samir Droubi, Alex Reinking of Adobe, and former CSAIL postdoc Gilbert Bernstein, now a professor at the University of Washington. This research was funded, in part, by the U.S. Defense Advanced Research Projects Agency (DARPA) and the U.S. National Science Foundation, while the first author was also supported by Masason, Funai, and Quad Fellowships.

Converting one type of cell to another — for example, a skin cell to a neuron — can be done through a process that requires the skin cell to be induced into a “pluripotent” stem cell, then differentiated into a neuron. Researchers at MIT have now devised a simplified process that bypasses the stem cell stage, converting a skin cell directly into a neuron.

Working with mouse cells, the researchers developed a conversion method that is highly efficient and can produce more than 10 neurons from a single skin cell. If replicated in human cells, this approach could enable the generation of large quantities of motor neurons, which could potentially be used to treat patients with spinal cord injuries or diseases that impair mobility.

“We were able to get to yields where we could ask questions about whether these cells can be viable candidates for the cell replacement therapies, which we hope they could be. That’s where these types of reprogramming technologies can take us,” says Katie Galloway, the W. M. Keck Career Development Professor in Biomedical Engineering and Chemical Engineering.

As a first step toward developing these cells as a therapy, the researchers showed that they could generate motor neurons and engraft them into the brains of mice, where they integrated with host tissue.

Galloway is the senior author of two papers describing the new method, which appear today in Cell Systems. MIT graduate student Nathan Wang is the lead author of both papers.

From skin to neurons

Nearly 20 years ago, scientists in Japan showed that by delivering four transcription factors to skin cells, they could coax them to become induced pluripotent stem cells (iPSCs). Similar to embryonic stem cells, iPSCs can be differentiated into many other cell types. This technique works well, but it takes several weeks, and many of the cells don’t end up fully transitioning to mature cell types.

“Oftentimes, one of the challenges in reprogramming is that cells can get stuck in intermediate states,” Galloway says. “So, we’re using direct conversion, where instead of going through an iPSC intermediate, we’re going directly from a somatic cell to a motor neuron.”

Galloway’s research group and others have demonstrated this type of direct conversion before, but with very low yields — fewer than 1 percent. In Galloway’s previous work, she used a combination of six transcription factors plus two other proteins that stimulate cell proliferation. Each of those eight genes was delivered using a separate viral vector, making it difficult to ensure that each was expressed at the correct level in each cell.

In the first of the new Cell Systems papers, Galloway and her students reported a way to streamline the process so that skin cells can be converted to motor neurons using just three transcription factors, plus the two genes that drive cells into a highly proliferative state.

Using mouse cells, the researchers started with the original six transcription factors and experimented with dropping them out, one at a time, until they reached a combination of three — NGN2, ISL1, and LHX3 — that could successfully complete the conversion to neurons.

Once the number of genes was down to three, the researchers could use a single modified virus to deliver all three of them, allowing them to ensure that each cell expresses each gene at the correct levels.

Using a separate virus, the researchers also delivered genes encoding p53DD and a mutated version of HRAS. These genes drive the skin cells to divide many times before they start converting to neurons, allowing for a much higher yield of neurons, about 1,100 percent.

“If you were to express the transcription factors at really high levels in nonproliferative cells, the reprogramming rates would be really low, but hyperproliferative cells are more receptive. It’s like they’ve been potentiated for conversion, and then they become much more receptive to the levels of the transcription factors,” Galloway says.

The researchers also developed a slightly different combination of transcription factors that allowed them to perform the same direct conversion using human cells, but with a lower efficiency rate — between 10 and 30 percent, the researchers estimate. This process takes about five weeks, which is slightly faster than converting the cells to iPSCs first and then turning them into neurons.

Implanting cells

Once the researchers identified the optimal combination of genes to deliver, they began working on the best ways to deliver them, which was the focus of the second Cell Systems paper.

They tried out three different delivery viruses and found that a retrovirus achieved the most efficient rate of conversion. Reducing the density of cells grown in the dish also helped to improve the overall yield of motor neurons. This optimized process, which takes about two weeks in mouse cells, achieved a yield of more than 1,000 percent.

Working with colleagues at Boston University, the researchers then tested whether these motor neurons could be successfully engrafted into mice. They delivered the cells to a part of the brain known as the striatum, which is involved in motor control and other functions.

After two weeks, the researchers found that many of the neurons had survived and seemed to be forming connections with other brain cells. When grown in a dish, these cells showed measurable electrical activity and calcium signaling, suggesting the ability to communicate with other neurons. The researchers now hope to explore the possibility of implanting these neurons into the spinal cord.

The MIT team also hopes to increase the efficiency of this process for human cell conversion, which could allow for the generation of large quantities of neurons that could be used to treat spinal cord injuries or diseases that affect motor control, such as ALS. Clinical trials using neurons derived from iPSCs to treat ALS are now underway, but expanding the number of cells available for such treatments could make it easier to test and develop them for more widespread use in humans, Galloway says.

The research was funded by the National Institute of General Medical Sciences and the National Science Foundation Graduate Research Fellowship Program.

Sports analytics is fueled by fans, and funded by teams. The 19th annual MIT Sloan Sports Analytics Conference (SSAC), held last Friday and Saturday, showed more clearly than ever how both groups can join forces.

After all, for decades, the industry’s main energy source has been fans weary of bad strategies: too much bunting in baseball, too much punting in football, and more. The most enduring analytics icon, Bill James, was a teacher and night watchman until his annual “Baseball Abstract” books began to upend a century of conventional wisdom, in the 1980s. After that, sports analytics became a profession.

Meanwhile, franchise valuations keep rising, women’s sports are booming, and U.S. college sports are professionalizing. All of it should create more analytics jobs, as “Moneyball” author Michael Lewis noted during a Friday panel.

“This whole analytics movement is a byproduct of the decisions becoming really expensive decisions,” Lewis said. “It didn’t matter if you got it wrong if you were paying someone $50,000 a year. But if you’re going to pay them $50 million, you better get it right. So, all of a sudden, someone who can give you a little bit more of an edge in that decision-making has more value.”

Would you like to be a valued sports analytics professional? Here are five ideas, gleaned from MIT’s industry-leading event, about how to gain traction in the field.

1. You can jump into this industry.

Bill James, as it happens, was the first speaker on the opening Friday-morning panel at SSAC, held at the Hynes Convention Center in Boston. His theme: the value of everyone’s work, since today’s amateurs become tomorrow’s professionals.

“Time will reveal that the people doing really important work here are not the people sitting on the stages, but the people in the audience,” James said.

This year, that audience had 2,500 attendees, from 44 U.S. states, 42 countries, and over 220 academic institutions, along with dozens of panels, a research paper competition, and thousands of hallway conversations among networking attendees. SSAC was co-founded in 2007 by Daryl Morey SM ’00, president of basketball operations for the Philadelphia 76ers, and Jessica Gelman, CEO of KAGR, the Kraft Analytics Group. The first three conferences were held in MIT classrooms.

But even now, sports analytics remains largely a grassroots thing. Why? Because fans can observe sports intensively, without being bound to its conventions, then study it quantitatively.

“The driving thing for a lot of people is they want to take this [analytical] way of thinking and apply it to sports,” soccer journalist Ryan O’Hanlon of ESPN said to MIT News, in one of those hallway conversations.

O’Hanlon’s 2022 book, “Net Gains,” chronicles the work of several people who held non-sports jobs, made useful advances in soccer analytics, then jumped into the industry. Soon, the sport may have more landing spots, between the growth of Major League Soccer in the U.S. and women’s soccer everywhere. Also, in O’Hanlon’s estimation, only three of the 20 clubs in England’s Premier League are deeply invested in analytics: Brentford, Brighton, and (league-leading) Liverpool. That could change.

In any case, most of the people who leap from fandom to professional status are willing to examine issues that others take for granted.

“I think it’s not being afraid to question the way everyone is doing things,” O’Hanlon added. “Whether that’s how a game is played, how we acquire players, how we think about anything. Pretty much anyone who gets to a high level and has impact [in analytics] has asked those questions and found a way to answer some.”

2. Make friends with the video team.

Suppose you love a sport, start analyzing it, produce good work that gets some attention, and — jackpot! — get hired by a pro team to do analytics.

Well, as former NBA player Shane Battier pointed out during a basketball panel at SSAC, you still won’t spend any time talking to players about your beloved data. That just isn’t how professional teams work, not even stat-savvy ones.

But there is good news: Analysts can still reach coaches and athletes through skilled use of video clips. Most European soccer managers ignore data, but will pay attention to the team’s video analysts. Basketball coaches love video. In American football, film study is essential. And technology has made it easier than ever to link data to video clips.

So analysts should become buddies with the video group. Importantly, analytics professionals now grasp this better than ever, something evident at SSAC across sports.

“Video in football [soccer] is the best way to communicate and get on the same page,” said Sarah Rudd, co-founder and CTO of src | ftbl, and a former analyst for Arsenal, at Friday’s panel on soccer analytics.

3. Seek opportunities in women’s sports analytics.

Have we mentioned that women’s sports is booming? The WNBA is expanding, the size of the U.S. transfer market in women’s soccer has doubled for three straight years, and you can now find women’s college volleyball in a basic cable package.

That growth is starting to fund greater data collection, in the WNBA and elsewhere, a frequent conversation topic at SSAC.

As Jennifer Rizzotti, president of the WNBA’s Connecticut Sun, noted of her own playing days in the 1990s: “We didn’t have statistics, we didn’t have [opponents’] tendencies that were being explained to us. So, when I think of what players have access to now and how far we’ve come, it’s really impressive.” And yet, she added, the amount of data in men’s basketball remains well ahead of the women’s game: “It gives you an awareness of how far we have to go.”

Some women’s sports still lack the cash needed for basic analytics infrastructure. One Friday panelist, LPGA golfer Stacy Lewis, a 13-time winner on tour, noted that the popular ball-tracking analytics system used in men’s golf costs $1 million per week, beyond budget for the women’s game.

And at a Saturday panel, Gelman said that full data parity between men’s and women’s sports was not imminent. “Sadly, I think we’re years away because we just need more investment into it,” she said.

But there is movement. At one Saturday talk, data developer Charlotte Eisenberg detailed how the website Sports Reference — a key resource of free public data —has been adding play-by-play data for WNBA games. That can help for evaluating individual players, particularly over long time periods, and has long been available for NBA games.

In short, as women’s sports grow, their analytics opportunities will, too.

4. Don’t be daunted by someone’s blurry “eye test.”

A subtle trip-wire in sports analytics, even at SSAC, is the idea that analytics should match the so-called “eye test,” or seemingly intuitive sports observations.

Here’s the problem: There is no one “eye test” in any sport, because people’s intuitions differ. For some basketball coaches, an unselfish role player stands out. To others, a flashy off-the-dribble shooter passes the eye test, even without a high shooting percentage. That tension would exist even if statistics did not.

Enter analytics, which confirms the high value of efficient shooting (as well as old-school virtues like defense, rebounding, and avoiding turnovers). But in a twist, the definition of a good shot in basketball has famously changed. In 1979-80, the NBA introduced the three-point line; in 1985, teams were taking 3.1 three-pointers per game; now in 2024-25, teams are averaging 37.5 three-pointers per game, with great efficiency. What happened?

“People didn’t use [the three-point shot] well at the beginning,” Morey said on a Saturday panel, quipping that “they were too dumb to know that three is greater than two.”

Granted, players weren’t used to shooting threes in 1980. But it also took a long time to change intuitions in the sport. Today, analytics shows that a contested three-pointer is a higher-value shot that an open 18-foot two-pointer. That might still run counter to someone’s “eye test.”

Incidentally, always following analytically informed coaching might also lead to a more standardized, less interesting game, as Morey and basketball legend Sue Bird suggested at the same panel.

“There’s a little bit of instinct that is now removed from the game,” Bird said. Shooting threes makes sense, she concurred, but “You’re only focused on the three-point line, and it takes away all the other things.”

5. Think about absolute truths, but solve for current tactics. 

Bill James set the bar high for sports analytics: His breakthrough equation, “runs created,” described how baseball works with almost Newtonian simplicity. Team runs are the product of on-base percentage and slugging percentage, divided by plate appearances. This applies to individual players, too.

But it’s almost impossible to replicate that kind of fundamental formula in other sports.

“I think in soccer there’s still a ton to learn about how the game works,” O’Hanlon told MIT News. Should a team patiently build possession, play long balls, or press up high? And how do we value players with wildly varying roles?

That sometimes leads to situations where, O’Hanlon notes, “No one really knows the right questions that the data should be asking, because no one really knows the right way to play soccer.”

Happily, the search for underlying truths can also produce some tactical insights. Consider one of the three finalists in the conference’s research paper competition, “A Machine Learning Approach to Player Value and Decision Making in Professional Ultimate Frisbee,” by Braden Eberhard, Jacob Miller, and Nathan Sandholtz.

In it, the authors examine playing patterns in ultimate, seeing if teams score more by using a longer string of higher-percentage short-range passes, or by trying longer, high-risk throws. They found that players tend to try higher-percentage passes, although there is some variation, including among star players. That suggests tactical flexibility matters. If the defense is trying to take away short passes, throw long sometimes.

It is a classic sports issue: The right way to play often depends on how your opponent is playing. In the search for ultimate truths, analysts can reveal the usefulness of short-term tactics. That helps team win, which helps analytics types stay employed. But none of this would come to light if analysts weren’t digging into the sports they love, searching for answers and trying to let the world know what they find.

“There is nothing happening here that will change your life if you don’t follow through on it,” James said. “But there are many things happening here that will change your life if you do.” 

In 2022, Randall Pietersen, a civil engineer in the U.S. Air Force, set out on a training mission to assess damage at an airfield runway, practicing “base recovery” protocol after a simulated attack. For hours, his team walked over the area in chemical protection gear, radioing in geocoordinates as they documented damage and looked for threats like unexploded munitions.

The work is standard for all Air Force engineers before they deploy, but it held special significance for Pietersen, who has spent the last five years developing faster, safer approaches for assessing airfields as a master’s student and now a PhD candidate and MathWorks Fellow at MIT. For Pietersen, the time-intensive, painstaking, and potentially dangerous work underscored the potential for his research to enable remote airfield assessments.

“That experience was really eye-opening,” Pietersen says. “We’ve been told for almost a decade that a new, drone-based system is in the works, but it is still limited by an inability to identify unexploded ordnances; from the air, they look too much like rocks or debris. Even ultra-high-resolution cameras just don’t perform well enough. Rapid and remote airfield assessment is not the standard practice yet. We’re still only prepared to do this on foot, and that’s where my research comes in.”

Pietersen’s goal is to create drone-based automated systems for assessing airfield damage and detecting unexploded munitions. This has taken him down a number of research paths, from deep learning to small uncrewed aerial systems to “hyperspectral” imaging, which captures passive electromagnetic radiation across a broad spectrum of wavelengths. Hyperspectral imaging is getting cheaper, faster, and more durable, which could make Pietersen’s research increasingly useful in a range of applications including agriculture, emergency response, mining, and building assessments.

Finding computer science and community

Growing up in a suburb of Sacramento, California, Pietersen gravitated toward math and physics in school. But he was also a cross country athlete and an Eagle Scout, and he wanted a way to put his interests together.

“I liked the multifaceted challenge the Air Force Academy presented,” Pietersen says. “My family doesn’t have a history of serving, but the recruiters talked about the holistic education, where academics were one part, but so was athletic fitness and leadership. That well-rounded approach to the college experience appealed to me.”

Pietersen majored in civil engineering as an undergrad at the Air Force Academy, where he first began learning how to conduct academic research. This required him to learn a little bit of computer programming.

“In my senior year, the Air Force research labs had some pavement-related projects that fell into my scope as a civil engineer,” Pietersen recalls. “While my domain knowledge helped define the initial problems, it was very clear that developing the right solutions would require a deeper understanding of computer vision and remote sensing.”

The projects, which dealt with airfield pavement assessments and threat detection, also led Pietersen to start using hyperspectral imaging and machine learning, which he built on when he came to MIT to pursue his master’s and PhD in 2020.

“MIT was a clear choice for my research because the school has such a strong history of research partnerships and multidisciplinary thinking that helps you solve these unconventional problems,” Pietersen says. “There’s no better place in the world than MIT for cutting-edge work like this.”

By the time Pietersen got to MIT, he’d also embraced extreme sports like ultra-marathons, skydiving, and rock climbing. Some of that stemmed from his participation in infantry skills competitions as an undergrad. The multiday competitions are military-focused races in which teams from around the world traverse mountains and perform graded activities like tactical combat casualty care, orienteering, and marksmanship.

“The crowd I ran with in college was really into that stuff, so it was sort of a natural consequence of relationship-building,” Pietersen says. “These events would run you around for 48 or 72 hours, sometimes with some sleep mixed in, and you get to compete with your buddies and have a good time.”

Since coming to MIT with his wife and two children, Pietersen has embraced the local running community and even worked as an indoor skydiving instructor in New Hampshire, though he admits the East Coast winters have been tough for him and his family to adjust to.

Pietersen went remote between 2022 to 2024, but he wasn’t doing his research from the comfort of a home office. The training that showed him the reality of airfield assessments took place in Florida, and then he was deployed to Saudi Arabia. He happened to write one of his PhD journal publications from a tent in the desert.

Now back at MIT and nearing the completion of his doctorate this spring, Pietersen is thankful for all the people who have supported him in throughout his journey.

“It has been fun exploring all sorts of different engineering disciplines, trying to figure things out with the help of all the mentors at MIT and the resources available to work on these really niche problems,” Pietersen says.

Research with a purpose

In the summer of 2020, Pietersen did an internship with the HALO Trust, a humanitarian organization working to clear landmines and other explosives from areas impacted by war. The experience demonstrated another powerful application for his work at MIT.

“We have post-conflict regions around the world where kids are trying to play and there are landmines and unexploded ordnances in their backyards,” Pietersen says. “Ukraine is a good example of this in the news today. There are always remnants of war left behind. Right now, people have to go into these potentially dangerous areas and clear them, but new remote-sensing techniques could speed that process up and make it far safer.”

Although Pietersen’s master’s work primarily revolved around assessing normal wear and tear of pavement structures, his PhD has focused on ways to detect unexploded ordnances and more severe damage.

“If the runway is attacked, there would be bombs and craters all over it,” Pietersen says. “This makes for a challenging environment to assess. Different types of sensors extract different kinds of information and each has its pros and cons. There is still a lot of work to be done on both the hardware and software side of things, but so far, hyperspectral data appears to be a promising discriminator for deep learning object detectors.”

After graduation, Pietersen will be stationed in Guam, where Air Force engineers regularly perform the same airfield assessment simulations he participated in in Florida. He hopes someday soon, those assessments will be done not by humans in protective gear, but by drones.

“Right now, we rely on visible lines of site,” Pietersen says. “If we can move to spectral imaging and deep-learning solutions, we can finally conduct remote assessments that make everyone safer.”

Three outstanding educators have been named MacVicar Faculty Fellows: associate professor in comparative media studies/writing Paloma Duong, associate professor of economics Frank Schilbach, and associate professor of urban studies and planning Justin Steil.

For more than 30 years, the MacVicar Faculty Fellows Program has recognized exemplary and sustained contributions to undergraduate education at MIT. The program is named in honor of Margaret MacVicar, MIT’s first dean for undergraduate education and founder of the Undergraduate Research Opportunities Program. Fellows are chosen through a highly competitive, annual nomination process. The MIT Registrar’s Office coordinates and administers the award on behalf of the Office of the Vice Chancellor; nominations are reviewed by an advisory committee, and final selections are made by the provost.

Paloma Duong: Equipping students with a holistic, global worldview

Paloma Duong is the Ford International Career Development Associate Professor of Latin American and Media Studies. Her work has helped to reinvigorate Latin American subject offerings, increase the number of Spanish minors, and build community at the Institute.

Duong brings an interdisciplinary perspective to teaching Latin American culture in dialogue with media theory and political philosophy in the Comparative Media Studies/Writing (CMS/W) program. Her approach is built on a foundation of respect for each student’s unique academic journey and underscores the importance of caring for the whole student, honoring where they can go as intellectuals, and connecting them to a world bigger than themselves.

Senior Alex Wardle says that Professor Duong “broadened my worldview and made me more receptive to new concepts and ideas … her class has deepened my critical thinking skills in a way that very few other classes at MIT have even attempted to.”

Duong’s Spanish language classes and seminars incorporate a wide range of practices — including cultural analyses, artifacts, guest speakers, and hands-on multimedia projects — to help students engage with the material, think critically, and challenge preconceived notions while learning about Latin American history. CMS/W head and professor of science writing Seth Mnookin notes, “students become conversant with region-specific vocabularies, worldviews, and challenges.” This approach makes students feel “deeply respected” and treats them as “learning partners — interlocutors in their own right,” observes Bruno Perreau, the Cynthia L. Reed Professor of French Studies and Language.

Outside the classroom, Duong takes the time to mentor and get to know students by supporting and attending programs connected to MIT Cubanos, Cena a las Seis, and Global Health Alliance. She also serves as an advisor for comparative media studies and Spanish majors, is the undergraduate officer for CMS/W, and is a member of the School of Humanities, Arts, and Social Sciences Education Advisory Committee and the Committee on Curricula.

“Subject areas like Spanish and Latin American Studies play an important role at MIT,” writes T.L. Taylor, professor in comparative media studies/writing and MacVicar Faculty Fellow. “Students find a sense of community and support in these spaces, something that should be at the heart of our attention more than ever these days. We are lucky to have such a dynamic and engaged educator like Professor Duong.”

On receiving this award, Duong says, “I’m positively elated! I’m very grateful to my students and colleagues for the nomination and am honored to become part of such a remarkable group of fellow teachers and mentors. Teaching undergraduates at MIT is always a beautiful challenge and an endless source of learning; I feel super lucky to be in this position.”

Frank Schilbach: Bringing energy and excitement to the curriculum

Frank Schilbach is the Gary Loveman Career Development Associate Professor of Economics. His connection and dedication to undergraduates, combined with his efforts in communicating the importance of economics as a field of study, were key components in the revitalization of Course 14.

When Schilbach arrived at MIT in 2015, there were only three sophomore economics majors. “A less committed teacher would have probably just taken it as a given and got on with their research,” writes professor of economics Abhijit Banerjee. “Frank, instead, took it as a challenge … his patient efforts in convincing students that they need to make economics a part of their general education was a key reason why innovations [to broaden the major] succeeded. The department now has more than 40 sophomores.”

In addition to bolstering enrollment, Schilbach had a hand in curricular improvements. Among them, he created a “next step” for students completing class 14.01 (Principles of Microeconomics) with a revised class 14.13 (Psychology and Economics) that goes beyond classic topics in behavioral economics to explore links with poverty, mental health, happiness, and identity.

Even more significant is the thoughtful and inclusive approach to teaching that Schilbach brings. “He is considerate and careful, listening to everyone, explaining concepts while making students understand that we care about them … it is just a joy to see how the students revel in the activities and the learning,” writes Esther Duflo, the Abdul Latif Jameel Professor of Poverty Alleviation and Development Economics. Erin Grela ’20 notes, “Professor Schilbach goes above and beyond to solicit student feedback so that he can make real-time changes to ensure that his classes are serving his students as best they can.”

His impacts extend beyond MIT as well. Professor of economics David Atkin writes: “Many of these students are inspired by their work with Frank to continue their studies at the graduate level, with an incredible 29 of his students going on to PhD studies at many of the best programs in the country. For someone who has only recently been promoted to a tenured professor, this is a remarkable record of advising.”

“I am delighted to be selected as a MacVicar Fellow,” says Schilbach. “I am thrilled that students find my courses valuable, and it brings me great joy to think that my teaching may help some students improve their well-being and inspire them to use their incredible talents to better the lives of others.”

Justin Steil: Experiential learning meets public service

“I am honored to join the MacVicar Faculty Fellows,” writes associate professor of law and urban planning Justin Steil. “I am deeply grateful to have the chance to teach and learn with such hard-working and creative students who are enthusiastic about collaborating to discover new knowledge and solve hard problems, in the classroom and beyond.”

Professor Steil uses his background as a lawyer, a sociologist, and an urban planner to combine experiential learning with opportunities for public service. In class 11.469 (Urban Sociology in Theory and Practice), he connects students with incarcerated individuals to examine inequality at one of the state’s largest prisons, MCI Norfolk. In another undergraduate seminar, students meet with leaders of local groups like GreenRoots in Chelsea, Massachusetts; Alternatives for Community and Environment in Roxbury, Massachusetts; and the Dudley Street Neighborhood Initiative in Roxbury to work on urban environmental hazards. Ford Professor of Urban Design and Planning and MacVicar Faculty Fellow Lawrence Vale calls Steil’s classes “life-altering.”

In addition to teaching, Steil is also a paramedic and has volunteered as an EMT for MIT Emergency Medical Service (EMS), where he continues to transform routine activities into teachable moments. “There are numerous opportunities at MIT to receive mentorship and perform research. Justin went beyond that. My conversations with Justin have inspired me to go to graduate school to research medical devices in the EMS context,” says Abigail Schipper ’24.

“Justin is truly devoted to the complete education of our undergraduate students in ways that meaningfully serve the broader MIT community as well as the residents of Cambridge and Boston,” says Andrew (1956) and Erna Viterbi Professor of Biological Engineering Katharina Ribbeck. Miho Mazereeuw, associate professor of architecture and urbanism and director of the Urban Risk Lab, concurs: “through his teaching, advising, mentoring, and connections with community-based organizations and public agencies, Justin has knit together diverse threads into a coherent undergraduate experience.”

Student testimonials also highlight Steil’s ability to make each student feel special by delivering undivided attention and individualized mentorship. A former student writes: “I was so grateful to have met an instructor who believed in his students so earnestly … despite being one of the busiest people I’ve ever known, [he] … unerringly made the students he works with feel certain that he always has time for them.”

Since joining MIT in 2015, Steil has received a Committed to Caring award in 2018; the Harold E. Edgerton Award for exceptional contributions in research, teaching, and service in 2021; and a First Year Advising Award from the Office of the First Year in 2022.

Learn more about the MacVicar Faculty Fellows Program on the Registrar’s Office website. 

QS World University Rankings has placed MIT in the No. 1 spot in 11 subject areas for 2025, the organization announced today.

The Institute received a No. 1 ranking in the following QS subject areas: Chemical Engineering; Civil and Structural Engineering; Computer Science and Information Systems; Data Science and Artificial Intelligence; Electrical and Electronic Engineering; Linguistics; Materials Science; Mechanical, Aeronautical, and Manufacturing Engineering; Mathematics; Physics and Astronomy; and Statistics and Operational Research.

MIT also placed second in seven subject areas: Accounting and Finance; Architecture/Built Environment; Biological Sciences; Business and Management Studies; Chemistry; Earth and Marine Sciences; and Economics and Econometrics.

For 2024, universities were evaluated in 55 specific subjects and five broader subject areas. MIT was ranked No. 1 in the broader subject area of Engineering and Technology and No. 2 in Natural Sciences.

Quacquarelli Symonds Limited subject rankings, published annually, are designed to help prospective students find the leading schools in their field of interest. Rankings are based on research quality and accomplishments, academic reputation, and graduate employment.

MIT has been ranked as the No. 1 university in the world by QS World University Rankings for 13 straight years.

For those looking to climb the corporate ladder in the U.S., here’s an idea you might not have considered: debate training.

According to a new research paper, people who learn the basics of debate are more likely to advance to leadership roles in U.S. organizations, compared to those who do not receive this training. One key reason is that being equipped with debate skills makes people more assertive in the workplace.

“Debate training can promote leadership emergence and advancement by fostering individuals’ assertiveness, which is a key, valued leadership characteristic in U.S. organizations,” says MIT Associate Professor Jackson Lu, one of the scholars who conducted the study.

The research is based on two experiments and provides empirical insights into leadership development, a subject more often discussed anecdotally than studied systematically.

“Leadership development is a multi-billion-dollar industry, where people spend a lot of money trying to help individuals emerge as leaders,” Lu says. “But the public doesn’t actually know what would be effective, because there hasn’t been a lot of causal evidence. That’s exactly what we provide.”

The paper, “Breaking Ceilings: Debate Training Promotes Leadership Emergence by Increasing Assertiveness,” was published Monday in the Journal of Applied Psychology. The authors are Lu, an associate professor at the MIT Sloan School of Management; Michelle X. Zhao, an undergraduate student at the Olin Business School of Washington University in St. Louis; Hui Liao, a professor and assistant dean at the University of Maryland’s Robert H. Smith School of Business; and Lu Doris Zhang, a doctoral student at MIT Sloan.

Assertiveness in the attention economy

The researchers conducted two experiments. In the first, 471 employees in a Fortune 100 firm were randomly assigned to receive either nine weeks of debate training or no training. Examined 18 months later, those receiving debate training were more likely to have advanced to leadership roles, by about 12 percentage points. This effect was statistically explained by increased assertiveness among those with debate training.

The second experiment, conducted with 975 university participants, further tested the causal effects of debate training in a controlled setting. Participants were randomly assigned to receive debate training, an alternative non-debate training, or no training. Consistent with the first experiment, participants receiving the debate training were more likely to emerge as leaders in subsequent group activities, an effect statistically explained by their increased assertiveness.

“The inclusion of a non-debate training condition allowed us to causally claim that debate training, rather than just any training, improved assertiveness and increased leadership emergence,” Zhang says. 

To some people, increasing assertiveness might not seem like an ideal recipe for success in an organizational setting, as it might seem likely to increase tensions or decrease cooperation. But as the authors note, the American Psychological Association conceptualizes assertiveness as “an adaptive style of communication in which individuals express their feelings and needs directly, while maintaining respect for others.”

Lu adds: “Assertiveness is conceptually different from aggressiveness. To speak up in meetings or classrooms, people don’t need to be aggressive jerks. You can ask questions politely, yet still effectively express opinons. Of course, that’s different from not saying anything at all.”

Moreover, in the contemporary world where we all must compete for attention, refined communication skills may be more important than ever.

“Whether it is cutting filler or mastering pacing, knowing how to assert our opinions helps us sound more leader-like,” Zhang says.

How firms identify leaders

The research also finds that debate training benefits people across demographics: Its impact was not significantly different for men or women, for those born in the U.S. or outside it, or for different ethnic groups.

However, the findings raise still other questions about how firms identify leaders. As the results show, individuals might have incentive to seek debate training and other general workplace skills. But how much responsibility do firms have to understand and recognize the many kinds of skills, beyond assertiveness, that employees may have?

“We emphasize that the onus of breaking leadership barriers should not fall on individuals themelves,” Lu says. “Organizations should also recognize and appreciate different communication and leadership styles in the workplace.”

Lu also notes that ongoing work is needed to understand if those firms are properly valuing the attributes of their own leaders.

“There is an important distinction between leadership emergence and leadership effectiveness,” Lu says. “Our paper looks at leadership emergence. It’s possible that people who are better listeners, who are more cooperative, and humbler, should also be selected for leadership positions because they are more effective leaders.”

This research was partly funded by the Society for Personality and Social Psychology.

How do we foster trust in science in an increasingly polarized world? A group including scientists, journalists, policymakers and more gathered at MIT on March 10 to discuss how to bridge the gap between scientific expertise and understanding.

The conference, titled “Building Trust in Science for a More Informed Future,” was organized by the MIT Press and the nonprofit Aspen Institute’s Science and Society Program. It featured talks about the power of storytelling, the role of social media and generative artificial intelligence in our information landscape, and why discussions about certain science topics can become so emotionally heated.

A common theme was the importance of empathy between science communicators and the public.

“The idea that disagreement is often seen as disrespect is insightful,” said MIT’s Ford Professor of Political Science Lily Tsai. “One way to communicate respect is genuine curiosity along with the willingness to change one’s mind. We’re often focused on the facts and evidence and saying, ‘Don’t you understand the facts?’ But the ideal conversation is more like, ‘You value ‘x.’ Tell me why you value ‘x’ and let’s see if we can connect on how the science and research helps you to fulfill those values, even if I don’t agree with them.’”

Many participants discussed the threat of misinformation, a problem exacerbated by the emergence of social media and generative AI. But it’s not all bad news for the scientific community. MIT Provost Cindy Barnhart opened the event by citing surveys showing a high level of trust broadly in scientists across the globe. Still, she also pointed to a U.S. survey showing communication was seen as an area of relative weakness for scientists.

Barnhart noted MIT’s long commitment to science communication and commended communication efforts affiliated with MIT including MIT Press, MIT Technology Review, and MIT News.

“We’re working hard to communicate the value of science to society as we fight to build public support for the scientific research, discovery, and evidence that is needed in our society,” Barnhart said. “At MIT, an essential way we do that is by shining a bright light on the groundbreaking work of our faculty, research, scientists, staff, postdocs, and students.”

Another theme was the importance of storytelling in science communication, and participants including the two keynote speakers offered plenty of their own stories. Francis Collins, who directed the National Institutes of Health between 2009 and 2021, and Sudanese climate journalist Lina Yassin delivered a joint keynote address moderated by MIT Vice President for Communications Alfred Ironside.

Recalling his time leading the NIH through the Covid-19 pandemic, Collins said the Covid-19 vaccine development was a major success, but the scientific community failed to explain to the public the way science evolves based on new evidence.

“We missed a chance to use the pandemic as a teachable moment,” Collins said. “In March of 2020, we were just starting to learn about the virus and how it spread, but we had to make recommendations to the public, which would often change a month or two later. So people began to doubt the information they were getting was reliable because it kept changing. If you’re in a circumstance where you’re communicating scientific evidence, start by saying, ‘This is a work in progress.’”

Collins said the government should have had a better plan for communicating information to the public when the pandemic started.

“Our health system was badly broken at the time because it had been underinvested in for far too long, so community-based education wasn’t really possible,” Collins said, noting his agency should have done more to empower physicians who were trusted voices in rural communities. “Far too much of our communication was top down.”

In her keynote address, Yassin shared her experience trying to get people in her home country to evacuate ahead of natural disasters. She said many people initially ignored her advice, citing their faith in God’s plan for them. But when she reframed her messaging to incorporate the teachings of Islam, a religion most of the country practices, she said people were much more receptive.

That was another recurring lesson participants shared: Science discussions don’t occur in a vacuum. Any conversation that ignores a person’s existing values and experiences will be less effective.

“Personal experience, as well as personal faith and belief, are critically important filters that we encounter every time we talk to people about science,” Ironside said.

As the price of solar panels has plummeted in recent decades, installation costs have taken up a greater share of the technology’s overall price tag. The long installation process for solar farms is also emerging as a key bottleneck in the deployment of solar energy.

Now the startup Charge Robotics is developing solar installation factories to speed up the process of building large-scale solar farms. The company’s factories are shipped to the site of utility solar projects, where equipment including tracks, mounting brackets, and panels are fed into the system and automatically assembled. A robotic vehicle autonomously puts the finished product — which amounts to a completed section of solar farm — in its final place.

“We think of this as the Henry Ford moment for solar,” says CEO Banks Hunter ’15, who founded Charge Robotics with fellow MIT alumnus Max Justicz ’17. “We’re going from a very bespoke, hands on, manual installation process to something much more streamlined and set up for mass manufacturing. There are all kinds of benefits that come along with that, including consistency, quality, speed, cost, and safety.”

Last year, solar energy accounted for 81 percent of new electric capacity in the U.S., and Hunter and Justicz see their factories as necessary for continued acceleration in the industry.

The founders say they were met with skepticism when they first unveiled their plans. But in the beginning of last year, they deployed a prototype system that successfully built a solar farm with SOLV Energy, one of the largest solar installers in the U.S. Now, Charge has raised $22 million for its first commercial deployments later this year.

From surgical robots to solar robots

While majoring in mechanical engineering at MIT, Hunter found plenty of excuses to build things. One such excuse was Course 2.009 (Produce Engineering Processes), where he and his classmates built a smart watch for communication in remote areas.

After graduation, Hunter worked for the MIT alumni-founded startups Shaper Tools and Vicarious Surgical. Vicarious Surgical is a medical robotics company that has raised more than $450 million to date. Banks was the second employee and worked there for five years.

“A lot of really hands on, project-based classes at MIT translated directly into my first roles coming out of school and set me up to be very independent and run large engineering projects,” Banks says, “Course 2.009, in particular, was a big launch point for me. The founders of Vicarious Surgical got in touch with me through the 2.009 network.”

As early as 2017, Hunter and Justicz, who majored in mechanical engineering and computer science, had discussed starting a company together. But they had to decide where to apply their broad engineering and product skillsets.

“Both of us care a lot about climate change. We see climate change as the biggest problem impacting the greatest number of people on the planet,” Hunter says. “Our mentality was if we can build anything, we might as well build something that really matters.”

In the process of cold calling hundreds of people in the energy industry, the founders decided solar was the future of energy production because its price was decreasing so quickly.

“It’s becoming cheaper faster than any other form of energy production in human history,” Hunter says.

When the founders began visiting construction sites for the large, utility-scale solar farms that make up the bulk of energy generation, it wasn’t hard to find the bottlenecks. The first site they traveled to was in the Mojave Desert in California. Hunter describes it as a massive dust bowl where thousands of workers spent months repeating tasks like moving material and assembling the same parts, over and over again.

“The site had something like 2 million panels on it, and every single one was assembled and fastened the same way by hand,” Hunter says. “Max and I thought it was insane. There’s no way that can scale to transform the energy grid in a short window of time.”

Hunter says he heard from each of the largest solar companies in the U.S. that their biggest limitation for scaling was labor shortages. The problem was slowing growth and killing projects.

Hunter and Justicz founded Charge Robotics in 2021 to break through that bottleneck. Their first step was to order utility solar parts and assemble them by hand in their backyards.

“From there, we came up with this portable assembly line that we could ship out to construction sites and then feed in the entire solar system, including the steel tracks, mounting brackets, fasteners, and the solar panels,” Hunter explains. “The assembly line robotically assembles all those pieces to produce completed solar bays, which are chunks of a solar farm.”

Each bay represents a 40-foot piece of the solar farm and weighs about 800 pounds. A robotic vehicle brings it to its final location in the field. Banks says Charge’s system automates all mechanical installation except for the process of pile driving the first metal stakes into the ground.

Charge’s assembly lines also have machine-vision systems that scan each part to ensure quality, and the systems work with the most common solar parts and panel sizes.

From pilot to product

When the founders started pitching their plans to investors and construction companies, people didn’t believe it was possible.

“The initial feedback was basically, ‘This will never work,’” Hunter says. “But as soon as we took our first system out into the field and people saw it operating, they got much more excited and started believing it was real.”

Since that first deployment, Charge’s team has been making its system faster and easier to operate. The company plans to set up its factories at project sites and run them in partnership with solar construction companies. The factories could even run alongside human workers.

“With our system, people are operating robotic equipment remotely rather than putting in the screws themselves,” Hunter explains. “We can essentially deliver the assembled solar to customers. Their only responsibility is to deliver the materials and parts on big pallets that we feed into our system.”

Hunter says multiple factories could be deployed at the same site and could also operate 24/7 to dramatically speed up projects.

“We are hitting the limits of solar growth because these companies don’t have enough people,” Hunter says. “We can build much bigger sites much faster with the same number of people by just shipping out more of our factories. It’s a fundamentally new way of scaling solar energy.”

Professors Emery Brown and Hamsa Balakrishnan work in vastly different fields, but are united by their deep commitment to mentoring students. While each has contributed to major advancements in their respective areas — statistical neuroscience for Brown, and large-scale transportation systems for Balakrishnan — their students might argue that their greatest impact comes from the guidance, empathy, and personal support they provide. 

Emery Brown: Holistic mentorship

Brown is the Edward Hood Professor of Medical Engineering and Computational Neuroscience at MIT and a practicing anesthesiologist at Massachusetts General Hospital. Brown’s experimental research has made important contributions toward understanding the neuroscience of how anesthetics act in the brain to create the states of general anesthesia. 

One of the biggest challenges in academic environments is knowing how to chart a course. Brown takes the time to connect with students individually, helping them identify meaningful pathways that they may not have considered for themselves. In addition to mentoring his graduate students and postdocs, Brown also hosts clinicians and faculty from around the world. Their presence in the lab exposes students to a number of career opportunities and connections outside of MIT’s academic environment.

Brown also continues to support former students beyond their time in his lab, offering guidance on personal and professional development even after they have moved on to other roles. “Knowing that I have Emery at my back as someone I can always turn to … is such a source of confidence and strength as I go forward into my own career,” one nominator wrote. 

When Brown faced a major career decision recently, he turned to his students to ask how his choice might affect them. He met with students individually to understand the personal impact that each might experience. Brown was adamant in ensuring that his professional advancement would not jeopardize his students, and invested a great deal of thought and effort in ensuring a positive outcome for them. 

Brown is deeply committed to the health and well-being of his students, with many nominators sharing examples of his constant support through challenging personal circumstances. When one student reached out to Brown, overwhelmed by research, recent personal loss, and career uncertainty, Brown created a safe space for vulnerable conversations. 

“He listened, supported me, and encouraged me to reflect on my aspirations for the next five years, assuring me that I should pursue them regardless of any obstacles,” the nominator shared. “Following our conversation, I felt more grounded and regained momentum in my research project.”

In summation, his student felt that Brown’s advice was “simple, yet enlightening, and exactly what I needed to hear at that moment.”

Hamsa Balakrishnan: Unequivocal advocacy

Balakrishnan is the William E. Leonhard Professor of Aeronautics and Astronautics at MIT. She leads the Dynamics, Infrastructure Networks, and Mobility (DINaMo) Research Group. Her current research interests are in the design, analysis, and implementation of control and optimization algorithms for large-scale cyber-physical infrastructures, with an emphasis on air transportation systems. 

Her nominators commended Balakrishnan for her efforts to support and advocate for all of her students. In particular, she connects her students to academic mentors within the community, which contributes to their sense of acceptance within the field. 

Balakrishnan’s mindfulness in respecting personal expression and her proactive approach to making everyone feel welcome have made a lasting impact on her students. “Hamsa’s efforts have encouraged me to bring my full self to the workplace,” one student wrote; “I will be forever grateful for her mentorship and kindness as an advisor.”

One student shared their experience of moving from a difficult advising situation to working with Balakrishnan, describing how her mentorship was crucial in the nominator’s successful return to research: “Hamsa’s mentorship has been vital to building up my confidence as a researcher, as she [often] provides helpful guidance and positive affirmation.”

Balakrishnan frequently gives her students freedom to independently explore and develop their research interests. When students wanted to delve into new areas like space research — far removed from her expertise in air traffic management and uncrewed aerial vehicles — Balakrishnan embraced the challenge and learned about these topics in order to provide better guidance. 

One student described how Balakrishnan consistently encouraged the lab to work on topics that interested them. This led the student to develop a novel research topic and publish a first author paper within months of joining the lab. 

Balakrishnan is deeply committed to promoting a healthy work-life balance for her students. She ensures that mentees do not feel compelled to overwork by encouraging them to take time off. Even if students do not have significant updates, Balakrishnan encourages weekly meetings to foster an open line of communication. She helps them set attainable goals, especially when it comes to tasks like paper reading and writing, and never pressures them to work late hours in order to meet paper or conference deadlines. 

Look around, and you’ll see it everywhere: the way trees form branches, the way cities divide into neighborhoods, the way the brain organizes into regions. Nature loves modularity — a limited number of self-contained units that combine in different ways to perform many functions. But how does this organization arise? Does it follow a detailed genetic blueprint, or can these structures emerge on their own?

A new study from MIT Professor Ila Fiete suggests a surprising answer.

In findings published Feb. 18 in Nature, Fiete, an associate investigator in the McGovern Institute for Brain Research and director of the K. Lisa Yang Integrative Computational Neuroscience (ICoN) Center at MIT, reports that a mathematical model called peak selection can explain how modules emerge without strict genetic instructions. Her team’s findings, which apply to brain systems and ecosystems, help explain how modularity occurs across nature, no matter the scale.

Joining two big ideas

“Scientists have debated how modular structures form. One hypothesis suggests that various genes are turned on at different locations to begin or end a structure. This explains how insect embryos develop body segments, with genes turning on or off at specific concentrations of a smooth chemical gradient in the insect egg,” says Fiete, who is the senior author of the paper. Mikail Khona PhD '25, a former graduate student and K. Lisa Yang ICoN Center graduate fellow, and postdoc Sarthak Chandra also led the study.

Another idea, inspired by mathematician Alan Turing, suggests that a structure could emerge from competition — small-scale interactions can create repeating patterns, like the spots on a cheetah or the ripples in sand dunes.

Both ideas work well in some cases, but fail in others. The new research suggests that nature need not pick one approach over the other. The authors propose a simple mathematical principle called peak selection, showing that when a smooth gradient is paired with local interactions that are competitive, modular structures emerge naturally. “In this way, biological systems can organize themselves into sharp modules without detailed top-down instruction,” says Chandra.

Modular systems in the brain

The researchers tested their idea on grid cells, which play a critical role in spatial navigation as well as the storage of episodic memories. Grid cells fire in a repeating triangular pattern as animals move through space, but they don’t all work at the same scale — they are organized into distinct modules, each responsible for mapping space at slightly different resolutions.

No one knows how these modules form, but Fiete’s model shows that gradual variations in cellular properties along one dimension in the brain, combined with local neural interactions, could explain the entire structure. The grid cells naturally sort themselves into distinct groups with clear boundaries, without external maps or genetic programs telling them where to go. “Our work explains how grid cell modules could emerge. The explanation tips the balance toward the possibility of self-organization. It predicts that there might be no gene or intrinsic cell property that jumps when the grid cell scale jumps to another module,” notes Khona.

Modular systems in nature

The same principle applies beyond neuroscience. Imagine a landscape where temperatures and rainfall vary gradually over a space. You might expect species to be spread, and also to vary, smoothly over this region. But in reality, ecosystems often form species clusters with sharp boundaries — distinct ecological “neighborhoods” that don’t overlap.

Fiete’s study suggests why: local competition, cooperation, and predation between species interact with the global environmental gradients to create natural separations, even when the underlying conditions change gradually. This phenomenon can be explained using peak selection — and suggests that the same principle that shapes brain circuits could also be at play in forests and oceans.

A self-organizing world

One of the researchers’ most striking findings is that modularity in these systems is remarkably robust. Change the size of the system, and the number of modules stays the same — they just scale up or down. That means a mouse brain and a human brain could use the same fundamental rules to form their navigation circuits, just at different sizes.

The model also makes testable predictions. If it’s correct, grid cell modules should follow simple spacing ratios. In ecosystems, species distributions should form distinct clusters even without sharp environmental shifts.

Fiete notes that their work adds another conceptual framework to biology. “Peak selection can inform future experiments, not only in grid cell research but across developmental biology.”

MIT aerospace engineers have found that greenhouse gas emissions are changing the environment of near-Earth space in ways that, over time, will reduce the number of satellites that can sustainably operate there.

In a study appearing today in Nature Sustainability, the researchers report that carbon dioxide and other greenhouse gases can cause the upper atmosphere to shrink. An atmospheric layer of special interest is the thermosphere, where the International Space Station and most satellites orbit today. When the thermosphere contracts, the decreasing density reduces atmospheric drag — a force that pulls old satellites and other debris down to altitudes where they will encounter air molecules and burn up.

Less drag therefore means extended lifetimes for space junk, which will litter sought-after regions for decades and increase the potential for collisions in orbit.

The team carried out simulations of how carbon emissions affect the upper atmosphere and orbital dynamics, in order to estimate the “satellite carrying capacity” of low Earth orbit. These simulations predict that by the year 2100, the carrying capacity of the most popular regions could be reduced by 50-66 percent due to the effects of greenhouse gases.

“Our behavior with greenhouse gases here on Earth over the past 100 years is having an effect on how we operate satellites over the next 100 years,” says study author Richard Linares, associate professor in MIT’s Department of Aeronautics and Astronautics (AeroAstro).

“The upper atmosphere is in a fragile state as climate change disrupts the status quo,” adds lead author William Parker, a graduate student in AeroAstro. “At the same time, there’s been a massive increase in the number of satellites launched, especially for delivering broadband internet from space. If we don’t manage this activity carefully and work to reduce our emissions, space could become too crowded, leading to more collisions and debris.”

The study includes co-author Matthew Brown of the University of Birmingham.

Sky fall

The thermosphere naturally contracts and expands every 11 years in response to the sun’s regular activity cycle. When the sun’s activity is low, the Earth receives less radiation, and its outermost atmosphere temporarily cools and contracts before expanding again during solar maximum.

In the 1990s, scientists wondered what response the thermosphere might have to greenhouse gases. Their preliminary modeling showed that, while the gases trap heat in the lower atmosphere, where we experience global warming and weather, the same gases radiate heat at much higher altitudes, effectively cooling the thermosphere. With this cooling, the researchers predicted that the thermosphere should shrink, reducing atmospheric density at high altitudes.

In the last decade, scientists have been able to measure changes in drag on satellites, which has provided some evidence that the thermosphere is contracting in response to something more than the sun’s natural, 11-year cycle.

“The sky is quite literally falling — just at a rate that’s on the scale of decades,” Parker says. “And we can see this by how the drag on our satellites is changing.”

The MIT team wondered how that response will affect the number of satellites that can safely operate in Earth’s orbit. Today, there are over 10,000 satellites drifting through low Earth orbit, which describes the region of space up to 1,200 miles (2,000 kilometers), from Earth’s surface. These satellites deliver essential services, including internet, communications, navigation, weather forecasting, and banking. The satellite population has ballooned in recent years, requiring operators to perform regular collision-avoidance maneuvers to keep safe. Any collisions that do occur can generate debris that remains in orbit for decades or centuries, increasing the chance for follow-on collisions with satellites, both old and new.

“More satellites have been launched in the last five years than in the preceding 60 years combined,” Parker says. “One of key things we’re trying to understand is whether the path we’re on today is sustainable.”

Crowded shells

In their new study, the researchers simulated different greenhouse gas emissions scenarios over the next century to investigate impacts on atmospheric density and drag. For each “shell,” or altitude range of interest, they then modeled the orbital dynamics and the risk of satellite collisions based on the number of objects within the shell. They used this approach to identify each shell’s “carrying capacity” — a term that is typically used in studies of ecology to describe the number of individuals that an ecosystem can support.

“We’re taking that carrying capacity idea and translating it to this space sustainability problem, to understand how many satellites low Earth orbit can sustain,” Parker explains.

The team compared several scenarios: one in which greenhouse gas concentrations remain at their level from the year 2000 and others where emissions change according to the Intergovernmental Panel on Climate Change (IPCC) Shared Socioeconomic Pathways (SSPs). They found that scenarios with continuing increases in emissions would lead to a significantly reduced carrying capacity throughout low Earth orbit.

In particular, the team estimates that by the end of this century, the number of satellites safely accommodated within the altitudes of 200 and 1,000 kilometers could be reduced by 50 to 66 percent compared with a scenario in which emissions remain at year-2000 levels. If satellite capacity is exceeded, even in a local region, the researchers predict that the region will experience a “runaway instability,” or a cascade of collisions that would create so much debris that satellites could no longer safely operate there.

Their predictions forecast out to the year 2100, but the team says that certain shells in the atmosphere today are already crowding up with satellites, particularly from recent “megaconstellations” such as SpaceX’s Starlink, which comprises fleets of thousands of small internet satellites.

“The megaconstellation is a new trend, and we’re showing that because of climate change, we’re going to have a reduced capacity in orbit,” Linares says. “And in local regions, we’re close to approaching this capacity value today.”

“We rely on the atmosphere to clean up our debris. If the atmosphere is changing, then the debris environment will change too,” Parker adds. “We show the long-term outlook on orbital debris is critically dependent on curbing our greenhouse gas emissions.”

This research is supported, in part, by the U.S. National Science Foundation, the U.S. Air Force, and the U.K. Natural Environment Research Council.

Tuberculosis lives and thrives in the lungs. When the bacteria that cause the disease are coughed into the air, they are thrust into a comparatively hostile environment, with drastic changes to their surrounding pH and chemistry. How these bacteria survive their airborne journey is key to their persistence, but very little is known about how they protect themselves as they waft from one host to the next.

Now MIT researchers and their collaborators have discovered a family of genes that becomes essential for survival specifically when the pathogen is exposed to the air, likely protecting the bacterium during its flight.

Many of these genes were previously considered to be nonessential, as they didn’t seem to have any effect on the bacteria’s role in causing disease when injected into a host. The new work suggests that these genes are indeed essential, though for transmission rather than proliferation.

“There is a blind spot that we have toward airborne transmission, in terms of how a pathogen can survive these sudden changes as it circulates in the air,” says Lydia Bourouiba, who is the head of the Fluid Dynamics of Disease Transmission Laboratory, an associate professor of civil and environmental engineering and mechanical engineering, and a core faculty member in the Instiute for Medical Engineering and Science at MIT. “Now we have a sense, through these genes, of what tools tuberculosis uses to protect itself.”

The team’s results, appearing this week in the Proceedings of the National Academy of Sciences, could provide new targets for tuberculosis therapies that simultaneously treat infection and prevent transmission.

“If a drug were to target the product of these same genes, it could effectively treat an individual, and even before that person is cured, it could keep the infection from spreading to others,” says Carl Nathan, chair of the Department of Microbiology and Immunology and R.A. Rees Pritchett Professor of Microbiology at Weill Cornell Medicine.

Nathan and Bourouiba are co-senior authors of the study, which includes MIT co-authors and mentees of Bourouiba in the Fluids and Health Network: co-lead author postdoc Xiaoyi Hu, postdoc Eric Shen, and student mentees Robin Jahn and Luc Geurts. The study also includes collaborators from Weill Cornell Medicine, the University of California at San Diego, Rockefeller University, Hackensack Meridian Health, and the University of Washington.

Pathogen’s perspective

Tuberculosis is a respiratory disease caused by Mycobacterium tuberculosis, a bacterium that most commonly affects the lungs and is transmitted through droplets that an infected individual expels into the air, often through coughing or sneezing. Tuberculosis is the single leading cause of death from infection, except during the major global pandemics caused by viruses.

“In the last 100 years, we have had the 1918 influenza, the 1981 HIV AIDS epidemic, and the 2019 SARS Cov2 pandemic,” Nathan notes. “Each of those viruses has killed an enormous number of people. And as they have settled down, we are left with a ‘permanent pandemic’ of tuberculosis.”

Much of the research on tuberculosis centers on its pathophysiology — the mechanisms by which the bacteria take over and infect a host — as well as ways to diagnose and treat the disease. For their new study, Nathan and Bourouiba focused on transmission of tuberculosis, from the perspective of the bacterium itself, to investigate what defenses it might rely on to help it survive its airborne transmission.

“This is one of the first attempts to look at tuberculosis from the airborne perspective, in terms of what is happening to the organism, at the level of being protected from these sudden changes and very harsh biophysical conditions,” Bourouiba says.

Critical defense

At MIT, Bourouiba studies the physics of fluids and the ways in which droplet dynamics can spread particles and pathogens. She teamed up with Nathan, who studies tuberculosis, and the genes that the bacteria rely on throughout their life cycle.

To get a handle on how tuberculosis can survive in the air, the team aimed to mimic the conditions that the bacterium experiences during transmission. The researchers first looked to develop a fluid that is similar in viscosity and droplet sizes to what a patient would cough or sneeze out into the air. Bourouiba notes that much of the experimental work that has been done on tuberculosis in the past has been based on a liquid solution that scientists use to grow the bacteria. But the team found that this liquid has a chemical composition that is very different from the fluid that tuberculosis patients actually cough and sneeze into the air.

Additionally, Bourouiba notes that fluid commonly sampled from tuberculosis patients is based on sputum that a patient spits out, for instance for a diagnostic test. “The fluid is thick and gooey and it’s what most of the tuberculosis world considers to represent what is happening in the body,” she says. “But it’s extraordinarily inefficient in spreading to others because it’s too sticky to break into inhalable droplets.”

Through Bourouiba’s work with fluid and droplet physics, the team determined the more realistic viscosity and likely size distribution of tuberculosis-carrying microdroplets that would be transmitted through the air. The team also characterized the droplet compositions, based on analyses of patient samples of infected lung tissues. They then created a more realistic fluid, with a composition, viscosity, surface tension and droplet size that is similar to what would be released into the air from exhalations.

Then, the researchers deposited different fluid mixtures onto plates in tiny individual droplets and measured in detail how they evaporate and what internal structure they leave behind. They observed that the new fluid tended to shield the bacteria at the center of the droplet as the droplet evaporated, compared to conventional fluids where bacteria tended to be more exposed to the air. The more realistic fluid was also capable of retaining more water.

Additionally, the team infused each droplet with bacteria containing genes with various knockdowns, to see whether the absence of certain genes would affect the bacteria’s survival as the droplets evaporated.

In this way, the team assessed the activity of over 4,000 tuberculosis genes and discovered a family of several hundred genes that seemed to become important specifically as the bacteria adapted to airborne conditions. Many of these genes are involved in repairing damage to oxidized proteins, such as proteins that have been exposed to air. Other activated genes have to do with destroying damaged proteins that are beyond repair.

“What we turned up was a candidate list that’s very long,” Nathan says. “There are hundreds of genes, some more prominently implicated than others, that may be critically involved in helping tuberculosis survive its transmission phase.”

The team acknowledges the experiments are not a complete analog of the bacteria’s biophysical transmission. In reality, tuberculosis is carried in droplets that fly through the air, evaporating as they go. In order to carry out their genetic analyses, the team had to work with droplets sitting on a plate. Under these constraints, they mimicked the droplet transmission as best they could, by setting the plates in an extremely dry chamber to accelerate the droplets’ evaporation, analogous to what they would experience in flight.

Going forward, the researchers have started experimenting with platforms that allow them to study the droplets in flight, in a range of conditions. They plan to focus on the new family of genes in even more realistic experiments, to confirm whether the genes do indeed shield Mycobacterium tuberculosis as it is transmitted through the air, potentially opening the way to weakening its airborne defenses.

“The idea of waiting to find someone with tuberculosis, then treating and curing them, is a totally inefficient way to stop the pandemic,” Nathan says. “Most people who exhale tuberculosis do not yet have a diagnosis. So we have to interrupt its transmission. And how do you do that, if you don’t know anything about the process itself? We have some ideas now.”

This work was supported, in part, by the National Institutes of Health, the Abby and Howard P. Milstein Program in Chemical Biology and Translational Medicine, and the Potts Memorial Foundation, the National Science Foundation Center for Analysis and Prediction of Pandemic Expansion (APPEX), Inditex, NASA Translational Research Institute for Space Health , and Analog Devices, Inc.

Imagine that a robot is helping you clean the dishes. You ask it to grab a soapy bowl out of the sink, but its gripper slightly misses the mark.

Using a new framework developed by MIT and NVIDIA researchers, you could correct that robot’s behavior with simple interactions. The method would allow you to point to the bowl or trace a trajectory to it on a screen, or simply give the robot’s arm a nudge in the right direction.

Unlike other methods for correcting robot behavior, this technique does not require users to collect new data and retrain the machine-learning model that powers the robot’s brain. It enables a robot to use intuitive, real-time human feedback to choose a feasible action sequence that gets as close as possible to satisfying the user’s intent.

When the researchers tested their framework, its success rate was 21 percent higher than an alternative method that did not leverage human interventions.

In the long run, this framework could enable a user to more easily guide a factory-trained robot to perform a wide variety of household tasks even though the robot has never seen their home or the objects in it.

“We can’t expect laypeople to perform data collection and fine-tune a neural network model. The consumer will expect the robot to work right out of the box, and if it doesn’t, they would want an intuitive mechanism to customize it. That is the challenge we tackled in this work,” says Felix Yanwei Wang, an electrical engineering and computer science (EECS) graduate student and lead author of a paper on this method.

His co-authors include Lirui Wang PhD ’24 and Yilun Du PhD ’24; senior author Julie Shah, an MIT professor of aeronautics and astronautics and the director of the Interactive Robotics Group in the Computer Science and Artificial Intelligence Laboratory (CSAIL); as well as Balakumar Sundaralingam, Xuning Yang, Yu-Wei Chao, Claudia Perez-D’Arpino PhD ’19, and Dieter Fox of NVIDIA. The research will be presented at the International Conference on Robots and Automation.

Mitigating misalignment

Recently, researchers have begun using pre-trained generative AI models to learn a “policy,” or a set of rules, that a robot follows to complete an action. Generative models can solve multiple complex tasks.

During training, the model only sees feasible robot motions, so it learns to generate valid trajectories for the robot to follow.

While these trajectories are valid, that doesn’t mean they always align with a user’s intent in the real world. The robot might have been trained to grab boxes off a shelf without knocking them over, but it could fail to reach the box on top of someone’s bookshelf if the shelf is oriented differently than those it saw in training.

To overcome these failures, engineers typically collect data demonstrating the new task and re-train the generative model, a costly and time-consuming process that requires machine-learning expertise.

Instead, the MIT researchers wanted to allow users to steer the robot’s behavior during deployment when it makes a mistake.

But if a human interacts with the robot to correct its behavior, that could inadvertently cause the generative model to choose an invalid action. It might reach the box the user wants, but knock books off the shelf in the process.

“We want to allow the user to interact with the robot without introducing those kinds of mistakes, so we get a behavior that is much more aligned with user intent during deployment, but that is also valid and feasible,” Wang says.

Their framework accomplishes this by providing the user with three intuitive ways to correct the robot’s behavior, each of which offers certain advantages.

First, the user can point to the object they want the robot to manipulate in an interface that shows its camera view. Second, they can trace a trajectory in that interface, allowing them to specify how they want the robot to reach the object. Third, they can physically move the robot’s arm in the direction they want it to follow.

“When you are mapping a 2D image of the environment to actions in a 3D space, some information is lost. Physically nudging the robot is the most direct way to specifying user intent without losing any of the information,” says Wang.

Sampling for success

To ensure these interactions don’t cause the robot to choose an invalid action, such as colliding with other objects, the researchers use a specific sampling procedure. This technique lets the model choose an action from the set of valid actions that most closely aligns with the user’s goal.

“Rather than just imposing the user’s will, we give the robot an idea of what the user intends but let the sampling procedure oscillate around its own set of learned behaviors,” Wang explains.

This sampling method enabled the researchers’ framework to outperform the other methods they compared it to during simulations and experiments with a real robot arm in a toy kitchen.

While their method might not always complete the task right away, it offers users the advantage of being able to immediately correct the robot if they see it doing something wrong, rather than waiting for it to finish and then giving it new instructions.

Moreover, after a user nudges the robot a few times until it picks up the correct bowl, it could log that corrective action and incorporate it into its behavior through future training. Then, the next day, the robot could pick up the correct bowl without needing a nudge.

“But the key to that continuous improvement is having a way for the user to interact with the robot, which is what we have shown here,” Wang says.

In the future, the researchers want to boost the speed of the sampling procedure while maintaining or improving its performance. They also want to experiment with robot policy generation in novel environments.