Featured video: MIT teachings, free to the world

A new short film from MIT Open Learning explores the origin, influence, and global reach of MIT OpenCourseWare, reflecting on its role in establishing MIT, in 2001, as the first higher education institution to make educational resources freely available to learners across the world.

Part of MIT Open Learning, MIT OpenCourseWare helped spark a global movement that continues to shape how knowledge is shared across the world. The film, titled “The Courage to Be Open: MIT OpenCourseWare and the Democratization of Knowledge,” captures both the vision behind this work and the lasting impact it has had on expanding access to learning at scale.

Video by MIT Open Learning | 15 minutes, 22 seconds

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MIT students study plasma physics beneath Alaska’s aurora

For many graduate students, waking up at noon after a 4 a.m. bedtime is a sign of a night well spent. For a group of MIT students, it was simply the start of their workday — timed not to the sun, but to the aurora.

Their goal was simple: to study plasma phenomena using the aurora borealis as a natural laboratory. The process, less so; working largely in darkness in Fairbanks, Alaska, the students conducted experiments in temperatures that dipped as low as -25 degrees Fahrenheit, using red headlamps for visibility. The sun set before 3 p.m., and even at its warmest, temperatures barely reached 20 F.

The aurora provides a rare opportunity to observe plasma behavior directly, as charged particles that interact with Earth’s magnetic field produce visible, large-scale structures in the night sky. As Fairbanks is situated beneath a region of especially frequent auroral activity, it is one of the most reliable places in the world to observe these phenomena, though the conditions come with real constraints. 

For one thing, the extreme cold directly impacted the instrumentation. “Our laptops went from full battery to nearly empty in 10 minutes because of the cold,” says Leonardo Corsaro, a PhD student in physics at the Plasma Science and Fusion Center (PSFC) at MIT. “We were trying to transfer data as fast as possible before everything shut down; it was a race against time!”

The challenges extended beyond the cold itself. “The cold can be managed,” says Leon Nichols, a PhD student in physics at PSFC. “With good planning, you can stay comfy in -20 F. The real difficulty was movement when deploying cameras far away from the roads. Walking through thick snow can burn up to 900 calories in an hour. We used cross-country skis to access some of the more remote terrain that would have taken hours to reach otherwise.”

But the conditions were more than worth it: During their time in Alaska, the group witnessed the strongest solar storm in the past two decades, bringing the aurora to life in ways few will ever experience. “It felt like we were the only ones there,” Sydney Menne, a PhD student in nuclear science and engineering, recounts, “removed from the Earth and just entirely surrounded by the aurora, fully immersed in it.” 

The team was granted access to observation facilities at Poker Flat Research Range through the University of Alaska Fairbanks Geophysical Institute. Over the course of the trip, students deployed multiple all-sky camera systems across distances of up to 100 miles, enabling simultaneous observations of auroral structures from different locations. These cameras, which capture 360-degree images of the night sky, were paired with magnetometers to correlate visual auroral features with changes in Earth’s magnetic field. 

By combining spatially distributed imaging with magnetic field measurements, the team aimed to capture how auroral structures change across space, with the long-term goal of supporting three-dimensional reconstructions of the aurora. This year’s campaign also expanded the measurements beyond imaging, using muon detectors to explore possible correlations between visual auroral activity, magnetic field changes, and particle detections, offering a potential window into how high-energy particles in the upper atmosphere relate to visible auroral activity.

Despite decades of study, many aspects of the aurora remain poorly understood, and each observation offers an opportunity to better characterize the behavior of plasma in near-Earth space. The team also observed a pulsating aurora, a relatively rare phenomenon in which strips of light stretching across the sky blink on and off multiple times per second. By combining instruments not traditionally applied to these problems and deploying low-cost systems at scale, the team is exploring new approaches to studying these phenomena. Insights from these observations can help improve our understanding of space weather, including how solar activity affects satellites, communications systems, and power infrastructure on Earth.

For some participants, the experience reshaped how they think about plasma physics itself. Corsaro explains, “In my research, it is easy to associate these phenomena with colorful plots and simulations, losing touch with the physical process. Seeing structures in the aurora, electric currents and flows forming and shifting overhead, brought a sense of reality to those concepts, and served as a reminder that real plasmas are far less neat and intuitive than theory suggests.”

The experience is part of a broader effort. This group of students represented the third iteration of the Geophysical Plasma Observation Expedition (GPOE), a project involving MIT students from the Plasma Science and Fusion Center, along with collaborating departments, that sends a cohort to Fairbanks, Alaska, each year. Faculty members now provide support for the expedition, while continuity is maintained through its student-driven structure, with each cohort including a mix of returning and new participants. The expedition is organized and led entirely by students and operates on an intensive, compressed timeline. Students are responsible not only for data collection, but also for instrument design, site selection, logistics, and post-processing, completing a full research cycle within a matter of months.

This year’s cohort included graduate students Leonardo Corsaro and Leon Nichols of PSFC; Sydney Menne of the Department of Nuclear Science and Engineering; and Noah Wolfe and Oleksandra “Sasha” Lukina of the Laser Interferometer Gravitational-Wave Observatory (LIGO) Laboratory and the MIT Kavli Institute for Astrophysics and Space Research. The group was accompanied by Professor Matthew Evans, professor of physics at MIT, who is affiliated with the LIGO Laboratory and the Kavli Institute. 

“This is an opportunity to go from concept to data analysis in just a few months,” says John Ball, a PhD student in nuclear science and engineering at PSFC. “That kind of compressed scientific cycle is rare, especially in our field.”

The program itself has relatively recent and somewhat unusual origins. It began in 2023, when graduate student Shon Mackie, frustrated by the lack of hands-on plasma diagnostic opportunities, noticed the solar cycle was approaching its peak and saw an opportunity to study plasma phenomena more directly. He drafted a short proposal to PSFC leadership, and the response from then-Director Dennis Whyte was two lines: “Sounds cool, literally! PSFC will fund this.” 

Since its launch in 2023, GPOE has evolved from a single-camera effort into a multi-instrument, multi-site campaign with growing participation, with each cohort building on the work of previous years by refining instrumentation, expanding observational coverage, and improving data collection strategies. 

This hands-on, student-driven approach has also created opportunities to extend the experience beyond MIT. In 2024, the program expanded to include a new outreach collaboration with the MIT Museum and the MIT Nord Anglia Collaboration, bringing approximately 65 high school students from around 20 schools worldwide to MIT to help design and build components of the all-sky camera systems used in the field. Working within a set of technical constraints, students developed and tested designs, ultimately producing 13 cameras that were deployed during the Alaska expedition.

The program has also begun to produce results beyond the expedition itself. Students have presented their work at major conferences, including the American Geophysical Union, and published findings in peer-reviewed journals such as Earth and Space Science. The group’s low-cost all-sky camera and magnetometer design is now being adopted by other research teams and community science initiatives, extending its impact beyond MIT.

Beyond its scientific goals, participants emphasized the broader impact of the experience. 

“Standing outside at midnight in Alaska, staring up at sheets of glowing plasma stretching thousands of kilometers across the sky, really brings home just how small and delicate our own place in the universe is,” says Ball. 

As the program continues to grow, students hope to expand both its technical capabilities and its reach, including more permanent instrumentation and expanding outreach partnerships. For many involved, the expedition represents not just a research opportunity, but a reminder of the scale and immediacy of the phenomena they study.

“Science is an adventure,” Corsaro says. “This kind of work reminds you why you became a scientist in the first place.”

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MIT science writing students collaborate with The Associated Press

This spring, six reporters from The Associated Press’ climate desk traveled from cities across the United States to work with students from the MIT Graduate Program in Science Writing. Students developed and pitched local climate stories, then, over a four-day intensive weekend, worked with visual journalists from the AP to report and produce their pieces. Articles cover a broad spectrum of environmental topics, ranging from area kelp harvests that are used to produce biofuels to efforts to restore cranberry bogs in environmentally friendly ways, and include visual elements, like photography and videography.

The four collaborative pieces include:

• “How a retired cranberry bog helped change the game for wetland restoration,” by Jamie Jiang and Julia Vaz
• “Planes and ships could run on kelp someday, but there are serious hurdles,” by Zoe Beketova and Ana Georgescu
• “Massachusetts is dumping sewage into waterways. Grassroots organizations are fighting back,” by Ashley D’Souza and Lucie McCormick
• “One of America’s oldest weather observatories shows people the science behind our climate,” by Laura Martin Agudelo and Alex Megerle

“This workshop was an intense few days that offered a unique opportunity for MIT journalists to get feedback while in the field, reporting. The students brought enthusiasm and passion to the reporting, heading out before the sun came up and working long into the nights over the weekend for stories in the Boston area and beyond,” says AP’s Climate Photo Editor Alyssa Goodman, the workshop’s lead organizer. “For the AP team members who participated, it was also a rewarding opportunity, allowing us to share our passion for climate storytelling while getting to know these students, watching them build strong stories and gain experiences that will help them as they continue in journalism.”

The collaboration is unique, even among journalism programs. The Associated Press is one of the most prestigious, longest-running news wire services in existence. Nearly 4 billion people worldwide come in contact with AP journalism every day. The publication has won 59 Pulitzer Prizes, including 36 in photojournalism.

MIT student reporters say that the opportunity to directly work with journalists from the AP’s climate team and have their own stories published has been a highlight of their time in the Graduate Program in Science Writing.

“It was great to be in the field with a reporter and photographer from the AP News team, learning directly from her as the reporting unfolded,” says Zoe Beketova, whose story focused on kelp biofuels. “That kind of expertise is difficult to get in a static classroom setting, and I think my team learned a lot.”

Ana Georgescu says that the experience of working with the AP team was “like stepping into a real newsroom.” Georgescu adds that coordinating with AP editors and reporting teams in real time and under tight deadlines provided valuable on-the-ground experience.

“What made the biggest difference for me was being in the field alongside an experienced photojournalist and seeing how they read a scene in practice,” she says. “We were able to get immediate feedback on how we directed subjects, which scenes we chose, and how we integrated photography into the reporting process. That kind of hands-on, in-the-moment experience was incredibly helpful, and it’s made me really excited to keep exploring climate stories, as well as the visual side of journalism.”

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MIT affiliates elected to National Academy of Sciences for 2026

The National Academy of Sciences (NAS) has elected 120 members and 25 international members for 2026, including six MIT faculty members and 10 additional alumni. 

Among MIT professors, Bengt Holmström, Michale Fee, Gareth McKinley ’91, Keith Nelson, Fan Wang, and Catherine Wolfram ’96 were elected in recognition of their “distinguished and continuing achievements in original research.” 

Additional alumni who were elected include Christopher J. Chang PhD ’02 (Chemistry); Cynthia J. Ebinger SM ’86, PhD ’88 (Earth, Atmospheric and Planetary Sciences); Andrew Gelman ’85, ’86 (Mathematics and Physics); Richard L. Greene ’60 (Physics); Chuan He PhD ’00 (Chemistry); Pardis C. Sabeti ’97 (Biology/Life Sciences); Robert J. Shiller SM ’68, PhD ’72 (Economics); Daniel M. Sigman PhD ’97 (EAPS); Eero Simoncelli SM ’88, PhD ’93 (Electrical Engineering and Computer Science); and Salil P. Vadhan PhD ’99 (Mathematics).

Membership in the National Academy of Sciences is one of the highest honors a scientist can receive in their career. The NAS is a private, nonprofit institution that was established under a congressional charter signed by President Abraham Lincoln in 1863. It recognizes achievement in science by election to membership, and — with the National Academy of Engineering and the National Academy of Medicine — provides science, engineering, and health policy advice to the federal government and other organizations.

Bengt Holmström is the Paul A. Samuelson Professor of Economics, emeritus. He received his doctoral degree from the Stanford Graduate School of Business in 1978 and held faculty positions at Northwestern University and Yale University before joining the MIT faculty in 1994 with a joint appointment in economics and management.

Holmström is best known for his foundational research on the theory of contracting and incentives, for which he received the 2016 Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred Nobel (together with Oliver Hart of Harvard University). His extensive contributions to contract theory as applied to the theory of the firm, corporate governance, and liquidity problems in financial crises have had wide-ranging impacts, while bringing contract theory into mainstream economic thought.

In addition to the Nobel, Holmström’s research has been recognized with the Stephen A. Ross Prize in Financial Economics and the Grand Cross of the Order of the Lion of Finland. He is a member of the American Academy of Arts and Sciences, the Econometric Society, and the American Finance Association. Holmström is also an elected foreign member of the Royal Swedish Academy of Sciences and a member of the Finnish Academy of Sciences and Letters.

Michale S. Fee is the Glen V. and Phyllis F. Dorflinger Professor of Neuroscience, head of the MIT Department of Brain and Cognitive Sciences (BCS), and investigator at the McGovern Institute for Brain Research. His research explores how the brain learns and generates complex sequential behaviors. Using the zebra finch as a model system, Fee investigates the neural mechanisms underlying birdsong — a behavior that young birds learn from their fathers through trial and error, much as human infants learn to speak through babbling. His research extends far beyond birdsong — the neural circuits controlling birdsong learning are closely related to human brain circuits disrupted in Parkinson’s and Huntington’s diseases. Insights from Fee’s research could reveal new clues to the causes and potential treatments of these complex brain disorders.

After receiving his BE with honors in engineering physics at the University of Michigan in 1985, Fee studied applied physics at Stanford University, where he carried out his PhD thesis work in the laboratory of Steven Chu. In 1992, he began working as a postdoc in David Kleinfeld’s lab in the Biological Computation Research Department at Bell Laboratories. Four years later, he became a permanent member of the technical staff at Bell Labs and began working on the mechanisms of vocal sequence generation in the songbird. In 2003, he became an investigator at the McGovern Institute and a faculty member in BCS. In 2021, he was appointed BCS department head, continuing the department’s tradition of being led by scientists whose exemplary work makes MIT a world leader in brain science. Fee is a member of the American Academy of Arts and Sciences and a recipient of multiple undergraduate and graduate teaching awards at MIT.  

Gareth H. McKinley ’91 is the School of Engineering Professor of Teaching Innovation in the Department of Mechanical Engineering at MIT, former associate head and interim head of the department, and co-founder of Cambridge Polymer Group. McKinley’s research interests include non-Newtonian fluid dynamics, microfluidics, extensional rheology, field-responsive materials, super-hydrophobicity, drag reduction, and the wetting of nanostructured surfaces. His work focuses on understanding the rheology of complex fluids such as surfactants, biomaterials, gels, and polymers, which are ubiquitous in foods and consumer products. 

McKinley has made outstanding contributions to viscoelastic fluid mechanics, understanding flow instabilities and stretching flows. His research group has developed novel instrumentation and customized rheological analysis techniques that have driven the field of rheology for complex and soft fluids. His instrumentation and testing algorithms, along with freely-distributed code for analyzing large amplitude oscillatory shear flow, and broad-band “chirp” rheometry, are used worldwide in industry and academia . 

McKinley is the author of over 390 technical publications. He has won the Publication Award of the Society of Rheology twice (2007 and 2022), as well as the 2021 Walters Award from J. Non-Newtonian Fluid Mechanics. He was awarded the Bingham Medal of The Society of Rheology in 2013, the Gold Medal from the British Society of Rheology in 2014, and the G.I. Taylor Medal from the Society for Engineering Science in 2022. In 2019, he was elected to the National Academy of Engineering and was also inducted as a fellow of the Royal Society of London. In 2023, he was awarded an honorary doctorate from the Katholieke University of Leuven, and in 2024 became a corresponding member of the Australian Academy of Sciences. In 2025, he was elected to the American Academy of Arts and Sciences and also became a foreign fellow of the Indian National Academy of Engineering.  

Keith A. Nelson, the Haslam and Dewey Professor of Chemistry, earned his BS in chemistry from Stanford University. After completing his doctoral studies in physical chemistry, also at Stanford, he conducted postdoctoral research with John P. McTague at the University of California at Los Angeles. In 1982, Nelson joined the MIT Department of Chemistry as an assistant professor.

His distinguished career has been recognized with numerous honors, including the William F. Meggers Award, the Bomem-Michelson Award, and the Frank Isakson Prize for Optical Effects in Solids. Research in the Nelson Group focuses on the time-resolved optical study and control of  collective transformations in condensed matter, using pulses of light in the THz, optical, and X-ray spectral ranges and laser-generated strain waves to drive the modes of motion through which these changes occur.

Fan Wang is a professor of Brain and Cognitive Sciences, investigator at the McGovern Institute, and co-director of the K. Lisa Yang and Hock E. Tan Center for Molecular Therapeutics at MIT. She investigates the neural circuits that govern the dynamic interactions between brain and body, exploring how the brain generates sensory perceptions and controls movement. Wang uses cutting-edge techniques including optogenetics, in vivo electrophysiology, and in vivo imaging to make discoveries with profound clinical implications.

By developing innovative tools to study how brain circuits work, Wang discovered distinct populations of neurons activated by anesthesia that can suppress pain without blocking sensation, and can calm anxiety by regulating automatic body functions like heart rate. She also identified the brain circuits controlling rhythmic movements essential for exploration and communication. Together, these findings reveal how emotion, physiology, movement, and consciousness are deeply interconnected.

Before coming to MIT, Wang obtained her PhD from Columbia University working with Richard Axel, and received her postdoctoral training at the University of California at San Francisco and Stanford University with Marc Tessier-Lavigne. She became a faculty member at Duke University in 2003, where she was later appointed Morris N. Broad Professor of Neurobiology. Wang became an investigator at the McGovern Institute and a faculty member in the Department of Brain and Cognitive Sciences at MIT in 2021. She is a member of the American Academy of Arts and Sciences and a recipient of multiple undergraduate teaching and graduate mentorship awards at MIT.  

Catherine D. Wolfram ’96 is the William Barton Rogers Professor in Energy and professor of applied economics in the MIT Sloan School of Management. Before coming to MIT Sloan, Wolfram previously served as the Cora Jane Flood Professor of Business Administration at the Haas School of Business at the University of California at Berkeley. From March 2021 to October 2022, she served as the deputy assistant secretary for climate and energy economics at the U.S. Treasury, while on leave from UC Berkeley. Before leaving for government service, she was the program director of the National Bureau of Economic Research’s Environment and Energy Economics Program and a research affiliate at the Energy Institute at Haas. Before joining the faculty at UC Berkeley, she was an assistant professor of economics at Harvard University. She received a PhD in economics from MIT in 1996 and an BA from Harvard in 1989.

Wolfram has published extensively on the economics of energy markets. Her work has analyzed rural electrification programs in the developing world, energy efficiency programs in the United States, the effects of environmental regulation on energy markets, and the impact of privatization and market restructuring in the United States and United Kingdom. She is currently working on projects at the intersection of climate, energy, and trade, including work on carbon border adjustment mechanisms and oil market sanctions. Since March 2025, Wolfram has served on the COP30 President’s Council on Economics, Finance, and Climate, and has chaired a working group on climate coalitions.

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Some democracies are struggling to ensure safe drinking water

About 2 billion people — just under a quarter of the world’s population — lack regular access to clean drinking water. And roughly 800,000 people annually die from illnesses associated with unsanitary water.

Drinking water access is a fundamental problem for human and economic development. The U.N., for instance, highlighted the issue in its Sustainable Development Goals of 2015, an ambitious 17-point agenda that specified safe drinking water as a basic global aim.

Past research shows that democracies, in comparison to other forms of government, tend to be more successful at delivering this kind of public good, which benefits a large portion of the population. This is likely due to accountability measures that include elections, greater transparency, and more freedom in civil society.

But now a study led by an MIT professor shows that across nearly 100 countries with developing economies, that dynamic has become more complex in the 21st century. While democracies are slightly ahead of non-democracies when it comes to providing at least some water, they have been falling behind when it comes to ensuring that there is safe water on tap. 

“Among low- and middle-income countries, which have not done as well economically, we found there wasn’t really a big difference between democracies and non-democracies in the provision of what is called basic drinking water,” says MIT political scientist Evan Lieberman, co-author of a new paper detailing the results. “But for safe drinking water, we found, surprisingly, that democratic countries were becoming less good at extending access.” 

While the study does not pinpoint the precise reasons for this, it suggests a lens for viewing the problem. Democracies tend to be better at delivering visible public goods, the kinds of things citizens can literally see — like infrastructure that delivers water. But the difference between safe and unsafe water is not necessarily visible and obvious, so public officials may not be as responsive.

“This is likely a big part of the equation, that the invisibility of safe water makes it a less compelling public good for politicians,” says Lieberman, the Total Professor of Political Science and Contemporary Africa, and director of MIT’s Center for International Studies.

The paper, “Beyond the tap: The limited value of democracy for delivering universal safe water access in low- and middle-income countries,” is published in the journal World Development. The authors are Lieberman, and Naomi Tilles, a doctoral student in political science at Stanford University.

Seeing is believing

To conduct the study, the scholars analyzed drinking water data recorded by the World Health Organization/UNICEF Joint Monitoring Programme. That provides information for basic availability to water, defined as access to an improved water source with no more than 30 minutes of collection time; and access to safe drinking water, defined as an improved water source that is available on premises, available when needed, and free from potentially disease-producing contaminants, which range from fecal matter to harmful chemicals.

Examining 96 low- and middle-income countries, the researchers looked at a variety of measures pertaining to its democratic or non-democratic features, and ran 39,000 regressions to see how the form of government related to its provision of water. Overall, Lieberman and Tilles found that democratic governance is modestly associated with an increase in the basic availability of water, compared to non-democracies. However, the effect is not particularly robust.

The good news is that between 2000 and 2024, 81 of the 90 countries with data available in both years made gains in safe drinking water access. However, democratic countries have been less successful than their non-democratic counterparts in advancing the goal of achieving universal access. 

“Moreover, the gap between democracies and non-democracies seems to be getting a little bit larger over time,” Lieberman observes. 

Because the study is focused on establishing the overall empirical situation, the scholars do not claim to have determined why this trend has been emerging. Many newer democracies have struggled to establish high-functioning governance in some regions, which may influence their overall results. 

More broadly, Lieberman suggests, visibility matters. Past scholarship has shown that democracies perform relatively well in delivering visible public goods, especially in countries with little information in the public sphere. Delivering water generates attention for politicians in a way that keeping water safe does not. 

“Politicians may figure out they should do things citizens like, to stay in office, such as bringing water to an area,” Lieberman says. “You can have a ribbon-cutting ceremony, and people feel it really happened. But water quality is often invisible.

It’s a more difficult challenge to ensure safe water: You have to do testing, prevent people from polluting, and you may need to treat the water.”

In any case, Lieberman notes, “Given what we find, what is clear is that the incentives are not aligned under the current systems for advancing safe-water access within all democracies. That provides opportunities for human agency to create incentives for citizens, nongovernment agencies, and governments to do what is needed.” 

Development for all

Lieberman comes to the topic of water access as an expert on African politics. His most recent book, “Until We Have Won Our Liberty” (Princeton University Press, 2022), examines the vicissitudes of South African democracy. In the book and in general, he suggests that democracy is the most viable path toward development with “dignity,” meaning economic growth accompanied by liberties and equal treatment under the law. 

“I think democracy provides dignified development, by granting people recognition and participation, and that’s an extremely valuable thing,” Lieberman says.

Still, when it comes to the performance of many countries with regard to safe water, he says, “I think we just need to be clear-eyed about real problems.”

In some countries, he suggests, the time horizon of elected officials may also be relatively short-term, and they may be more oriented toward simpler problems than water safety. At the same time, other members of society need to find ways to make water safety a bigger issue in the eyes of the public. 

“There are important lessons for democracies to learn, and citizens in civil society who are aware of this challenge need to figure out ways to get people to care about it, to recognize the connection between illness and unsafe water, and to use political campaigns to advance their longer-term interests,” Lieberman says.

Overall, he adds, “There is something intrinsically important about democratic government. Then the question becomes how to make it work better to deliver really important outcomes like safe water.”

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Technology usually creates jobs for young, skilled workers. Will AI do the same?

At any given time, technology does two things to employment: It replaces traditional jobs, and it creates new lines of work. Machines replace farmers, but enable, say, aeronautical engineers to exist. So, if tech creates new jobs, who gets them? How well do they pay? How long do new jobs remain new, before they become just another common task any worker can do?

A new study of U.S. employment led by MIT labor economist David Autor sheds light on all these matters. In the postwar U.S., as Autor and his colleagues show in granular detail, new forms of work have tended to benefit college graduates under 30 more than anyone else. 

“We had never before seen exactly who is doing new work,” Autor says. “It’s done more by young and educated people, in urban settings.” 

The study also contains a powerful large-scale insight: A lot of innovation-based new work is driven by demand. Government-backed expansion of research and manufacturing in the 1940s, in response to World War II, accounted for a huge amount of new work, and new forms of expertise. 

“This says that wherever we make new investments, we end up getting new specializations,” Autor says. “If you create a large-scale activity, there’s always going to be an opportunity for new specialized knowledge that’s relevant for it. We thought that was exciting to see.” 

The paper, “What Makes New Work Different from More Work?” is forthcoming in the Annual Review of Economics. The authors are Autor; Caroline Chin, a doctoral student in MIT’s Department of Economics; Anna M. Salomons, a professor at Tilburg University’s Department of Economics and Utrecht University’s School of Economics; and Bryan Seegmiller PhD ’22, an assistant professor at Northwestern University’s Kellogg School of Management.

And yes, learning about new work, and the kinds of workers who obtain it, might be relevant to the spread of artificial intelligence — although, in Autor’s estimation, it is too soon to tell just how AI will affect the workplace.

“People are really worried that AI-based automation is going to erode specific tasks more rapidly,” Autor observes. “Eroding tasks is not the same thing as eroding jobs, since many jobs involve a lot of tasks. But we’re all saying: Where is the new work going to come from? It’s so important, and we know little about it. We don’t know what it will be, what it will look like, and who will be able to do it.”

“If everyone is an expert, then no one is an expert”

The four co-authors also collaborated on a previous major study of new work, published in 2024, which found that about six out of 10 jobs in the U.S. from 1940 to 2018 were in new specialties that had only developed broadly since 1940. The new study extends that line of research by looking more precisely at who fills the new lines of work. 

To do that, the researchers used U.S. Census Bureau data from 1940 through 1950, as well as the Census Bureau’s American Community Survey (ACS) data from 2011 to 2023. In the first case, because Census Bureau records become wholly public after about 70 years, the scholars could examine individual-level data about occupations, salaries, and more, and could track the same workers as they changed jobs between the 1940 and 1950 Census enumerations. 

Through a collaborative research arrangement with the U.S. Census Bureau, the authors also gained secure access to person-level ACS records. These data allowed them to analyze the earnings, education, and other demographic characteristics of workers in new occupational specialties — and to compare them with workers in longstanding ones.

New work, Autor observes, is always tied to new forms of expertise. At first, this expertise is scarce; over time, it may become more common. In any case, expertise is often linked to new forms of technology.

“It requires mastering some capability,” Autor says. “What makes labor valuable is not simply the ability to do stuff, but specialized knowledge. And that often differentiates high-paid work from low-paid work.” Moreover, he adds, “It has to be scarce. If everyone is an expert, then no one is an expert.”

By examining the census data, the scholars found that back in 1950, about 7 percent of employees had jobs in types of work that had emerged since 1930. More recently, about 18 percent of workers in the 2011-2023 period were in lines of work introduced since 1970. (That happens to be roughly the same portion of new jobs per decade, although Autor does not think this is a hard-and-fast trend.) 

In these time periods, new work has emerged more often in urban areas, with people under 30 benefitting more than any other age category. Getting a job in a line of new work seems to have a lasting effect: People employed in new work in 1940 were 2.5 times as likely to be in new work in 1950, compared to the general population. College graduates were 2.9 percentage points more likely than high school graduates to be engaged in new work. 

New work also has a wage premium, that is, better salaries on aggregate than in already-existing forms of work. Yet as the study shows, that wage premium also fades over time, as the particular expertise in many forms of new work becomes much more widely grasped. 

“The scarcity value erodes,” Autor says. “It becomes common knowledge. It itself gets automated. New work gets old.”

After all, Autor points out, driving a car was once a scarce form of expertise. For that matter, so was being able to use word-processing programs such as WordPerfect or Microsoft Word, well into the 1990s. After a while, though, being able to handle word-processing tools became the most elementary part of using a computer.

Back to AI for a minute

Studying who gets new jobs led the scholars to striking conclusions about how new work is created. Examining county-level data from the World War II era, when the federal government was backing new manufacturing in public-private partnerships throughout the U.S., the study shows that counties with new factories had more new work, and that 85 to 90 percent of new work from 1940 to 1950 was technology-driven. 

In this sense there was a great deal of demand-driven innovation at the time. Today, public discourse about innovation often focuses on the supply side, namely, the innovators and entrepreneurs trying to create new products. But the study shows that the demand side can significantly influence innovative activity. 

“Technology is not like, ‘Eureka!’ where it just happens,” Autor says. “Innovation is a purposive activity. And innovation is cumulative. If you get far enough, it will have its own momentum. But if you don’t, it’ll never get there.”

Which brings us back to AI, the topic so many people are focused on in 2026. Will AI create good new jobs, or will it take work away? Well, it likely depends how we implement it, Autor thinks. Consider the massive health care sector, where there could be a lot of types of tech-driven new work, if people are interested in creating jobs.

“There are different ways we could use AI in health care,” Autor says. “One is just to automate people’s jobs away. The other is to allow people with different levels of expertise to do different tasks. I would say the latter is more socially beneficial. But it’s not clear that is where the market will go.” 

On the other hand, maybe with government-driven demand in various forms, AI could get applied in ways that end up boosting health care-sector productivity, creating new jobs as a result. 

“More than half the dollars in health care in the U.S. are public dollars,” Autor observes. “We have a lot of leverage there, we can push things in that direction. There are different ways to use this.” 

This research was supported, in part, by the Hewlett Foundation, the Google Technology and Society Visiting Fellows Program, the NOMIS Foundation, the Schmidt Sciences AI2050 Fellowship, the Smith Richardson Foundation, the James M. and Cathleen D. Stone Foundation, and Instituut Gak.

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Q&A: The path to a PhD in computational science and engineering at MIT

In 2023, the Center for Computational Science and Engineering (CCSE), an academic unit in the MIT Schwarzman College of Computing, introduced a new standalone PhD degree program. This interdisciplinary PhD program blends both coursework and a thesis, enabling students to pursue research in cross-cutting methodological aspects of computational science and engineering.

PhD candidate Emily Williams is poised to be the first graduate of the program. With a technical background in aerospace engineering and applied mathematics, her research interests include stochastic and generative modeling for multiscale chaotic systems. She earned a BS in aerospace engineering from the University of Illinois Urbana-Champaign and an MS in aeronautics and astronautics from MIT. She was awarded the Department of Energy Computational Science Graduate Fellowship, which funded her doctoral research. Here, she discusses her experience with the program and its impact on her career trajectory.

Q: What has been a highlight of the CCSE degree program?

A: I found the program curriculum to be extremely thoughtful and intentional. In particular, the program of study was constructed to cover many important areas of computational science and engineering research and education, from engineering and mathematical modeling to scientific and parallel computing. I found a lot of overlap with the DoE CSGF program of study, so I was given a lot of freedom to pursue very interesting technical electives that fit within CSE that I might not have been able to explore if I had been in a discipline-centric program.

Q: Why is this program so impactful, especially in the context of having a stand-alone PhD program?

A: I think a stand-alone PhD program helps to further establish the MIT CCSE as a leader in CSE research and education. The joint programs give graduate researchers more opportunity to learn and apply leading CSE methodologies to their disciplinary areas and primarily stay within their home department. For me, I’ve found that I’ve had more opportunities for collaboration, in potentially applying my methods to a wide range of different exciting applications. I think this theme of collaboration will continue to foster through those advancing through the standalone program in particular.

Q: What advice would you give to students considering this program?

A: I think my advice would be to keep an open mind. My interest in CSE was shaped by common threads in my education and research interests over the years that I didn’t think were connected at all. Through my fellowship and the standalone program, I felt like I was able to create my own path to my degree and take courses that excited me and fit within the CSE themes of our program of study.

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Steel developed at MIT is key to Formula One, Baja 1000, and MIT Motorsports

A high-performance steel with MIT origins has come full circle. 

After proving its worth in Formula One and Baja 1000 race cars, the computationally designed material has now been incorporated into the 2026 electric race car built by the student-run MIT Motorsports team.

The MIT car is scheduled to race against cars from other universities in the Formula SAE Electric competition in June.

Designing materials

Gregory B. Olson, professor of the practice in the MIT Department of Materials Science and Engineering, founded the MIT Steel Research Group (SRG) in 1985 with the goal of using computers to accelerate the hunt for new materials by plumbing databases of those materials’ fundamental properties. It was the beginning of a new field — computational materials design — that would eventually lead to the Materials Genome Initiative, a national program announced by President Barack Obama in 2011.

In 1985, however, “nobody knew whether we could really do this,” says Olson. Olson and colleagues eventually showed that the approach worked, and around 1990 the Army Research Office funded an SRG project aimed at developing high-performance steels for the gears in helicopters. That work came to the attention of producers at “Infinite Voyage,” a science documentary that ran on the Public Broadcasting System.

“When “Infinite Voyage” came to see me about the helicopter gear steels,” Olson remembers, “we got into a discussion about my interest in race cars” and whether the steels might have an application there.

The answer was yes, and Olson found himself connecting with the Newman/Haas racing team that Michael and Mario Andretti were driving for. Newman/Haas was also featured in the “Infinite Voyage” program, so “my first discussion with their chief engineer was on live television,” says Olson, who is also affiliated with the MIT Materials Research Laboratory.

He and colleagues went on to design a novel gear steel that could withstand the extreme conditions associated with a race car. They did the work over a weekend. “The surface hardness was the same as for a conventional gear steel, but we gave it the core properties of an armor steel,” Olson says.

Introducing Ferrium C61

That steel, which became known as Ferrium C61, was commercialized through QuesTek Innovations, the materials-design company Olson co-founded. It became the company’s first product.

Although it was never used in Newman/Haas cars, QuesTek pitched it to Baja 1000 off-road racers.

“We particularly focused on the 1600 class of those racing dune buggies. They would go flying over a sand dune with the wheels spinning in the air. And when they land, there would be a tremendous jolt to the drive gears,” Olson says. The result: The racers’ gears made with conventional steel regularly failed.

“The average life for conventional drive gears was point-six race,” says Olson (meaning on average they lasted for only 60 percent of a race). “With Ferrium C61, we changed it from point-six to six races.” The gears could now complete an average six races before failing.

QuesTek brought that data to meetings with different Formula One teams “to try to get C61 into other racing classes,” Olson says. 

Enter Red Bull, the British-licensed Formula One team. “The leading mechanical failure in Formula One racing is gearbox failures,” Olsen says. The gearbox houses the gearset, or collection of gears, in a car’s engine. “Once Red Bull adopted our steel for the gearset, they never had any gearbox failures, and they were world champions four times in the last decade.”

MIT Motorsports heard of this history and within the past year approached Olson about getting a sample of C61. “QuesTek had some stock available, and sold it at a high discount to the MIT team with, of course, instructions on how to heat-treat it,” Olson says. 

Because, of course, the students, who are mostly undergraduates, made the gears — and the car — themselves.

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Building AI models that understand chemical principles

Among all of the possible chemical compounds, it’s estimated that between 10²⁰ and 10⁶⁰ may hold potential as small-molecule drugs.

Evaluating each of those compounds experimentally would be far too time-consuming for chemists. So, in recent years, researchers have begun using artificial intelligence to help identify compounds that could make good drug candidates. 

One of those researchers is MIT Associate Professor Connor Coley PhD ’19, the Class of 1957 Career Development Associate Professor with shared appointments in the departments of Chemical Engineering and Electrical Engineering and Computer Science and the MIT Schwarzman College of Computing. His research straddles the line between chemical engineering and computer science, as he develops and deploys computational models to analyze vast numbers of possible chemical compounds, design new compounds, and predict reaction pathways that could generate those compounds. 

“It’s a very general approach that could be applied to any application of organic molecules, but the primary application that we think about is small-molecule drug discovery,” he says.

The intersection of AI and science

Coley’s interest in science runs in the family. In fact, he says, his family includes more scientists than non-scientists, including his father, a radiologist; his mother, who earned a degree in molecular biophysics and biochemistry before going to the MIT Sloan School of Management; and his grandmother, a math professor.

As a high school student in Dublin, Ohio, Coley participated in Science Olympiad competitions and graduated from high school at the age of 16. He then headed to Caltech, where he chose chemical engineering as a major because it offered a way to combine his interests in science and math.

During his undergraduate years, he also pursued an interest in computer science, working in a structural biology lab using the Fortran programming language to help solve the crystal structure of proteins. After graduating from Caltech, he decided to keep going in chemical engineering and came to MIT in 2014 to start a PhD.

Advised by professors Klavs Jensen and William Green, Coley worked on ways to optimize automated chemical reactions. His work focused on combining machine learning and cheminformatics — the application of computation methods to analyze chemical data — to plan reaction pathways that could make new drug molecules. He also worked on designing hardware that could be used to perform those reactions automatically. 

Part of that work was done through a DARPA-funded program called Make-It, which was focused on using machine learning and data science to improve the synthesis of medicines and other useful compounds from simple building blocks.

“That was my real entry point into thinking about cheminformatics, thinking about machine learning, and thinking about how we can use models to understand how different chemicals can be made and what reactions are possible,” Coley says.

Coley began applying for faculty jobs while still a graduate student, and accepted an offer from MIT at age 25. He received a mix of advice for and against taking a job at the same school where he went to graduate school, and eventually decided that a position at MIT was too enticing to turn down.

“MIT is a very special place in terms of the resources and the fluidity across departments. MIT seemed to be doing a really good job supporting the intersection of AI and science, and it was a vibrant ecosystem to stay in,” he says. “The caliber of students, the enthusiasm of the students, and just the incredible strength of collaborations definitely outweighed any potential concerns of staying in the same place.”

Chemistry intuition

Coley deferred the faculty position for one year to do a postdoc at the Broad Institute, where he sought more experience in chemical biology and drug discovery. There, he worked on ways to identify small molecules, from billions of candidates in DNA-encoded libraries, that might have binding interactions with mutated proteins associated with diseases.

After returning to MIT in 2020, he built his lab group with the mission of deploying AI not only to synthesize existing compounds with therapeutic potential, but also to design new molecules with desirable properties and new ways to make them. Over the past few years, his lab has developed a variety of computational approaches to tackle those goals. 

“We try to think about how to best pair a challenge in chemistry with a potential computational solution. And often that pairing motivates the development of new methods,” Coley says. One model his lab has developed, known as ShEPhERD, was trained to evaluate potential new drug molecules based on how they will interact with target proteins, based on the drug molecules’ three-dimensional shapes. This model is now being used by pharmaceutical companies to help them discover new drugs.

“We’re trying to give more of a medicinal chemistry intuition to the generative model, so the model is aware of the right criteria and considerations,” Coley says.

In another project, Coley’s lab developed a generative AI model called FlowER, which can be used to predict the reaction products that will result from combining different chemical inputs. 

In designing that model, the researchers built in an understanding of fundamental physical principles, such as the law of conservation of mass. They also compelled the model to consider the feasibility of the intermediate steps that need to take place on the pathway from reactants to products. These constraints, the researchers found, improved the accuracy of the model’s predictions.

“Thinking about those intermediate steps, the mechanisms involved, and how the reaction evolves is something that chemists do very naturally. It’s how chemistry is taught, but it’s not something that models inherently think about,” Coley says. “We’ve spent a lot of time thinking about how to make sure that our machine-learning models are grounded in an understanding of reaction mechanisms, in the same way an expert chemist would be.”

Students in his lab also work on many different areas related to the optimization of chemical reactions, including computer-aided structure elucidation, laboratory automation, and optimal experimental design.

“Through these many different research threads, we hope to advance the frontier of AI in chemistry,” Coley says.

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The Haystack 37m Telescope: A new era of astrophysical research

The Haystack 37m Telescope has been a landmark in radio astronomy and radar studies of the solar system since its first light in 1964. Over the following four decades, it supported NASA's Apollo landings on the moon, made planetary radar maps of the surface of Venus, contributed to experimental tests of Einstein's general relativity, supported the development of VLBI, and conducted foundational studies of quasars and star-forming regions. 

Recently, the Haystack 37m Telescope — a 37-meter radio and millimeter-wavelength antenna at MIT Haystack Observatory in Westford, Massachusetts — made its return to front-line astronomical research following an extended period of system upgrades. These observations reconnect this instrument with its long tradition of scientific discovery and open a new chapter.

On Dec. 8, 2025, Haystack scientists observed the supermassive black hole system at the center of the galaxy Messier 87 (M87) using a technique called very long baseline interferometry (VLBI) that links telescopes across continents to achieve extraordinary resolution. These observations mark the return of one of America's most storied radio telescopes to its historical scientific and educational mission.

The observations targeted the powerful jet of energy and matter launched from M87’s central black hole, M87*. This jet, driven by a black hole six-and-a-half billion times the mass of our sun, extends thousands of light years into intergalactic space and is one of the most energetic phenomena in the known universe. 

Previous international campaigns, namely those led by the Event Horizon Telescope, have imaged the black hole's immediate “shadow.” The Haystack 37m Telescope observations, performed in collaboration with the telescopes of the Very Long Baseline Array (VLBA) and the Greenland Telescope (GLT), help to probe the larger-scale structure of the jet, investigating how energy is transported far beyond the black hole's vicinity. Understanding this process is central to explaining how supermassive black holes shape the galaxies that surround them.

“The Haystack 37m Telescope’s exceptional sensitivity enables the intercontinental telescope array to detect faint emission from around the distant M87* black hole,” says Paul Tiede, principal investigator of the M87 study. “In tandem with the GLT and the VLBA, Haystack is helping create the first multifrequency movies of M87*’s faint jet, greatly improving our understanding of black hole physics.”

The upgraded Haystack 37m Telescope opens multiple new lines of research. At MIT, Saverio Cambioni and Richard Teague of the Department of Earth, Atmospheric and Planetary Sciences (EAPS) plan to use the instrument within MIT’s Planetary Defense Project to measure asteroid sizes and shapes, characterizing objects that could pose a hazard to Earth and deepening our understanding of the solar system’s formation. Associate Professor Brett McGuire of the Department of Chemistry plans to search for complex organic molecules in space, work that speaks to the question of how the chemical precursors to life arise.

“We are thrilled to provide the research community with a powerful telescope at a time where few such instruments are available,” says Jens Kauffmann, principal investigator of the Haystack 37m Telescope Astronomy Program, who uses the telescope to study the formation of stars and their planets. “Even more exciting are the prospects this generates for the next generation of astronomers. Hands-on training opportunities on world-class research telescopes have become exceptionally rare worldwide, and now we can offer this singular advanced workforce development program right here in Massachusetts.”

Student involvement with the Haystack 37m Telescope has already resumed: Undergraduate interns at Haystack Observatory played an active role in developing the telescope’s control systems and data analysis algorithms. This work exemplifies Haystack’s role as a hands-on research and training environment where students contribute directly and gain practical experience with a frontline research instrument.

The return to research-focused observations is the result of more than 10 years of careful, sustained work. From 2010 to 2014, the Haystack 37m Telescope underwent a major upgrade and refurbishment that enhanced its ability to observe at millimeter wavelengths. This work was primarily done to improve the antenna’s capability as a space radar. The dish now primarily serves U.S. government agencies in that capability, and astronomy was temporarily a secondary activity. 

But work to restore the telescope's science capability never stopped. Initial support from the National Science Foundation (NSF) in 2015 modernized systems for data analysis and radio signal processing. The first successful engineering-oriented VLBI experiments with the new dish were conducted at the same time. Additional NSF funding in 2019, provided in the context of the Next Generation Event Horizon Telescope (ngEHT) program, enabled a more general and sustained effort to upgrade receiver equipment and computing systems. Support from private donors to Haystack also aided in this longer-term effort.

Several recent developments, particularly in 2025, proved significant. With support from MIT's Jarve Seed Fund for Science Innovation, scientists and engineers removed lingering technical limitations with astronomy systems and expanded the telescope's scientific reach. Other funding for projects led by the Smithsonian Astrophysical Observatory enabled the M87 campaign and commissioning of the next-generation digital back end, a highly advanced signal-processing system developed for the ngEHT. Together, these advances made the December 2025 observations possible. MIT Haystack Observatory is now pursuing support from both private and federal sources for further improvements under the Haystack 37m Telescope Astronomy Program.

“The upgraded Haystack 37m Telescope empowers MIT students and researchers to pursue fundamental questions relating to our origins and our solar system,” says Richard Teague, professor at MIT EAPS. “With privileged access to such a powerful facility, we can undertake ambitious observational programs previously impossible to schedule. This is the beginning of what we expect will be an exciting era of new discoveries with the Haystack 37m Telescope.”

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Single-molecule tracker illuminates workings of cancer-related proteins

Using a powerful single-molecule imaging method they developed, a research team from the Broad Institute of MIT and Harvard has unveiled a dynamic view of how some cancer-related proteins interact in living cells. 

The technique relies on highly stable nanoparticle probes that brightly illuminate individual molecules for long periods of time. The researchers used their method to observe, for the first time, individual receptors as they move around the cell membrane, attaching to and then letting go of other receptors to alter signaling within the cell.

Described in the journal Cell, the work demonstrates the method’s potential for investigating other receptors and molecules, and for improved drug screening to better understand the effects of therapeutics on living cells.

“With our photostable probes, we can map out the entire lifespan of these molecules in their native environment and see things that have never been observable before,” says study leader Sam Peng, a Broad Institute core institute member and assistant professor of chemistry at MIT.

Molecular movies

Peng’s method solves a problem with existing contrast agents used in single-molecule tracking, such as dyes. Under the laser light that’s used to excite these dyes, they burn out after a few seconds in a phenomenon known as photobleaching, which means that scientists could only use them to take a few snapshots of cell receptors, and not follow them over the entirety of the signaling process.

For a longer and richer view, Peng’s lab developed long-lasting probes, known as upconverting nanoparticles, which emit signals that remain stable under laser excitation. The nanoparticles contain rare-earth ions that continue to luminescence for minutes, hours, and potentially years. In addition, by altering the type and doses of the ions, scientists can engineer probes emitting in many different colors, enabling tracking of many targets in a single experiment.

In the current study, the researchers aimed to uncover new biology by focusing on the EGFR family of cell receptors, which have been linked to several kinds of cancer. They collaborated with EGFR experts Matthew Meyerson and Heidi Greulich of the Broad’s Cancer Program. They knew that EGFR receptors need to pair up, or “dimerize,” in order to initiate signaling within the cell, but they wanted to learn more about the dynamics of these pairings — what the receptors partner with, how long they stay together, and how they find new partners.

For a better and more sustained look at the receptors, the research team customized their upconverting nanoparticles to tag EGFR and related receptors HER2 and HER3, which are linked to cancer, and used them to track the molecules in living human cells.

A new view of protein pairings

In this study, Peng and his team observed that, when activated with a stimulating molecule, EGFR receptors can pair up and stay dimerized for several minutes, something not observable using traditional dyes. Excessive and prolonged dimerization can lead to too much cell growth and cancer.

A microscopy video shows upconverting nanoparticles tagged to EGFR receptors (labeled pink and green), which track individual receptors as they dimerize. Image courtesy of the researchers.

When the EGFR molecules carried cancer-related mutations, the dimers became more stable, with the more stabilizing mutations linked to more potent cancers in people. In addition, the mutated receptors could form stable dimers even without an external stimulus prompting them to dimerize. The finding helps explain how EGFR mutations can lead to uncontrolled cell growth and cancer, and could inform efforts to target this process therapeutically.

The team discovered several other new and surprising details about how HER2 and HER3 form stable pairings with themselves, which helps illuminate the role of these molecules in related cancers.

When the research team tagged all three receptor types in one experiment, they observed a vibrant scene with receptors navigating the cell surface, finding partners, unpairing, and then finding new partners, over and over again.

Beyond shedding light on EGFR biology, the scientists hope that collaborators in other fields will apply their method to ask new scientific questions about other proteins of interest. “We think this technique could be transformative for studying molecular biology, because it enables dynamic biological processes to be observed with high spatiotemporal resolution over unprecedented timescales,” says Peng.

They are also planning to explore the method’s use in studying the mechanism of drug action, to reveal how potential therapeutics alter individual molecules over time. In addition, they will continue to improve their methods, such as making the probes smaller, brighter, and able to emit more colors.

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New research enables a robot to chart a better course

In the aftermath of a devastating earthquake, unpiloted aerial vehicles (UAVs) could fly through a collapsed building to map the scene, giving rescuers information they need to quickly reach survivors. 

But this remains an extremely challenging problem for an autonomous robot, which would need to swiftly adjust its trajectory to avoid sudden obstacles while staying on course.

Researchers from MIT and the University of Pennsylvania developed a new trajectory-planning system that tackles both challenges at once. Their technique enables a UAV to react to obstacles in milliseconds while staying on a smooth flight path that minimizes travel time. 

Their system uses a new mathematical formulation that ensures the robot travels safely to its destination along a feasible path, and that is less computationally intensive than other techniques. In this way, it generates smoother trajectories faster than state-of-the-art methods.

The trajectory planner is also efficient enough for real-time flight using only the robot’s onboard computer and sensors. 

Named MIGHTY, the open-source system does not require proprietary software packages that can cost hundreds of thousands of dollars. It could be more readily deployed in a wider variety of real-world settings.

In addition to search-and-rescue, MIGHTY could be utilized in applications like last-mile delivery in urban spaces, where UAVs need to avoid buildings, wires, and people, or in industrial inspection of complex structures, such as wind turbines.

“MIGHTY achieves comparable or better performance using only open-source tools, which means any researcher, student, or company — anywhere in the world — can use it freely. By removing this cost barrier, MIGHTY helps democratize high-performance trajectory planning and opens the door for a much broader community to build on this work,” says Kota Kondo, an aeronautics and astronautics graduate student and lead author of a paper on this trajectory planner.

Kondo is joined on the paper by Yuwei Wu, a graduate student at the University of Pennsylvania; Vijay Kumar, a professor at UPenn; and senior author Jonathan P. How, a Ford professor of aeronautics and astronautics and a principal investigator in the Laboratory for Information and Decision Systems (LIDS) and the Aerospace Controls Laboratory (ACL) at MIT. The research appears in IEEE Robotics and Automation Letters.

Overcoming trade-offs           

When Kondo was a child, the Fukushima Daiichi nuclear accident occurred following the Great East Japan Earthquake. With school cancelled, Kondo was stuck at home and watched the news every day as workers explored and secured the reactor site. Some workers still had to enter hazardous areas to contain the damage and assess the situation, exposing them to high doses of radioactive material.

“I became passionate about creating autonomous robots that can go into these dynamic and dangerous situations, then come back and report to humans who stay out of harm’s way,” Kondo says.

This task requires a strong trajectory planner, which is software that decides the path a robot should follow to safely get from point A to point B. 

But many existing systems force tradeoffs that limit performance. 

While some commercial systems can rapidly generate smooth trajectories, they can cost hundreds of thousands of dollars. Open-source alternatives often underperform compared to commercial solvers or are difficult to use.      

With MIGHTY, Kondo and his colleagues developed an open-source system that produces high-quality, smooth trajectories while reacting to obstacles in real-time, and which runs fast enough for flight using only onboard components.

To do this, they overcame a key challenge that limits many open-source systems. 

These methods usually estimate how long it will take the robot to get from point A to point B as a first step. From that fixed estimation of travel time, the planner finds the best path to reach the destination.

While using a fixed travel time allows the planner to rapidly generate a trajectory, it has drawbacks. For one, if the UAV must go far out of its way to avoid obstacles, it could be forced to crank up the speed to meet the fixed travel-time budget. This makes it harder to avoid sudden hazards.

A MIGHTY method

Instead, MIGHTY uses a mathematical technique, called a Hermite spline, that optimizes the travel time and flight path together, in a single step, to form a smooth trajectory that can be precisely controlled.

“Optimizing the spatial and temporal components together gets us better results, but now the optimization becomes so much bigger that it is harder to solve in a feasible amount of time,” Kondo says.

The researchers used a clever technique to reduce this computational overhead. 

Instead of generating a trajectory from scratch each time, MIGHTY makes an initial guess of a trajectory. Then it refines the trajectory through an iterative optimization, using a map of the scene generated by the UAV’s lidar sensors.

“We can make a decent guess of what the trajectory should be, which is a lot faster than generating the entire thing from nothing,” Kondo says.

This enables MIGHTY to react in real-time to unknown obstacles while keeping the trajectory smooth and minimizing travel time. The system utilizes the UAV’s onboard components, which is important for applications where a robot might travel far from a base station.

In simulated experiments, MIGHTY needed only about 90 percent of the computation time required by state-of-the-art methods, while safely reaching its destination about 15 percent faster than these approaches. 

When they tested the system on real robots, it reached a speed of 6.7 meters per second while avoiding every obstacle that appeared in its path.

“With MIGHTY, everything is integrated in one piece. It doesn’t need to talk to any other piece of software to get a solution. This helps us be even faster than some of the commercial solvers,” Kondo says.

In the future, the researchers want to enhance MIGHTY so it can be used to control multiple robots at once and conduct more flight experiments in challenging environments. They hope to continue improving the open-source system based on user feedback.

“MIGHTY makes an important contribution to agile robot navigation by revisiting the trajectory representation itself. Hermite splines have already been successfully used in visual simultaneous localization and mapping, and it is nice to see their advantages now being exploited for trajectory planning in mobile robots. By enabling joint optimization of path geometry, timing, velocity, and acceleration while retaining local control of the trajectory, MIGHTY gives robots more freedom to compute fast, dynamically feasible motions in cluttered environments,” says Davide Scaramuzza, professor and director of the Robotics and Perception Group at the University of Zurich, who was not involved with this research.

This research was funded, in part, by the United States Army Research Laboratory and the Defense Science and Technology Agency in Singapore.

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A bet that has paid off 500 million times over

In 2001, at the dawn of the digital age, MIT made a bold decision: to open its curriculum to the world. Through MIT OpenCourseWare — now part of MIT Open Learning — the Institute began sharing materials from nearly all of its courses online for free.  

A quarter of a century later, that decision has impacted the lives of more than 500 million people across the world who have used OpenCourseWare’s resources to expand their knowledge and develop new skills. 

“When MIT opens its doors, the world walks in,” said Dimitris Bertsimas, vice provost for open learning, at OpenCourseWare’s recent 25th Anniversary Symposium. “Twenty-five years ago, MIT made a bet on openness, generosity, and on the belief that knowledge is a public good. That bet has paid off 500 million times over.”

The impact of that bet took center stage as nearly 200 people gathered on campus for the symposium on April 8. The daylong celebration brought together faculty and staff, OpenCourseWare learners and educators, new and early funders of the program, MIT President Sally Kornbluth, Bertsimas, and others to reflect on OpenCourseWare’s global impact and the future of free and open education. 

The occasion also marked the premiere of “The Courage to Be Open: MIT OpenCourseWare and the Democratization of Knowledge.” Produced by MIT Open Learning’s Emmy Award-winning video team, the short documentary explores the origin, influence, and global reach of OpenCourseWare.

Initially announced as a 10-year initiative, MIT OpenCourseWare now offers more than 2,500 courses that span the undergraduate and graduate curriculum. Learners can freely access lecture notes, syllabi, problem sets, exams, and video lectures through the MIT Learn platform, the OpenCourseWare website, and its YouTube channel, which has grown into the platform’s most popular higher education channel with more than 6 million subscribers. To extend that reach even further, the OpenCourseWare Mirror Site Program provides free copies of course content on hard drives to educational organizations with limited or costly internet access.

From an idea to a global movement

In launching OpenCourseWare, MIT sparked a global movement, inspiring other universities to create their own open course initiatives and solidifying grassroots open education efforts into worldwide communities like OE Global. “Today, [OpenCourseWare] is cited in national education strategies, by nonprofit initiatives, and by international development programs — proof that openness scales when you lead with vision and courage,” Kornbluth said.

That impact lives on in the learners who turn to the Institute’s free course materials every day — from a community college student in Boston to a teenager in Australia to medical students in Turkey. OpenCourseWare has expanded the reach of MIT’s life-changing knowledge to nearly every corner of the world and opened doors to learners of all ages and backgrounds.

For many, that access is transformative. High school senior Hinata Yamahara and Andrea Henshall, a veteran of the United States Air Force, shared how OpenCourseWare helped fuel their curiosity, support their studies, and advance their goals.

“OpenCourseWare [reduces] the barrier to entry to more specialized topics,” said Yamahara, who discovered the resources while exploring an interest in urban planning, and now credits an MIT workshop with helping him pass the Federal Aviation Administration’s Private Pilot Knowledge Test.

From access to agency

What emerges across stories is that MIT’s decision to give away its course materials exemplified its mission to advance knowledge in service of the nation and the world. Openness, noted speakers, is part of the Institute’s DNA. “It’s written into our values,” said Chris Bourg, director of libraries at MIT, where she is also the founding director of the Center for Research on Equitable and Open Scholarship (CREOS).

Those values have also drawn thousands of supporters — from alumni and individual learners to businesses and the world’s leading philanthropic foundations — to help underwrite the initiative, and Open Learning more generally.

By making course materials not only free, but open, the Institute enables anyone to download, copy, modify, reuse, remix, and redistribute its resources for educational, non-commercial uses. “Access is powerful and absolutely necessary,” said Curt Newton, director of OpenCourseWare. “But openness goes further. It invites participation.”

For educators like Elizabeth Siler, a professor at Worcester State University in the department of business administration and economics, and Victor Odumuyiwa, an associate professor in computer science at the University of Lagos, OpenCourseWare offers a window into how MIT designs learning experiences and a foundation to bring those approaches into their own classrooms.

“I applied the same approach back home and, sincerely, I’ve gotten a lot of positive feedback from people getting jobs in global companies after taking the course that I designed,” Odumuyiwa said. 

For faculty on MIT’s campus, OpenCourseWare has also been transformative, fostering interdisciplinary collaborations and innovative uses of digital educational tools. Referencing the United Nations Sustainable Development Goals, Christopher Capozzola, the Elting E. Morison Professor of History at MIT, pointed to quality education (goal 4), reduced inequalities (goal 10), and peace, justice, and strong institutions (goal 16) as a guiding equation for open education. “I believe that MIT, through OpenCourseWare and all of our open education initiatives, has committed to solving that problem,” he said. “I just wanted to roll up my sleeves and be part of that.”

A new era for open education

If the rise of the internet in the early 2000s catalyzed MIT’s decision to “open its doors to the world without requiring a key,” said Kornbluth, artificial intelligence now presents a new moment to lead.

Building on that legacy, MIT Open Learning is leading the way with the launch of MIT Learn, an AI-enabled hub for the Institute’s non-degree learning opportunities. The platform brings together innovations like AskTIM — an AI assistant that helps learners discover relevant offerings and, in select offerings, enhances understanding with guided support — and new self-paced, modular online learning experiences that prepare learners to take on complex global challenges, including AI and climate. Together, these advances move MIT closer to a future of truly personalized education at global scale, grounded in faculty expertise and research.

“Sometime in the next five years, I’m looking for a moment that rhymes with what happened in 2001,” Newton said.

With the launch of MIT Learn and Open Learning’s goal of reaching 1 billion learners in the next decade, that next chapter is already taking shape.

“The future of open learning is bright, and belongs to all of us,” Bertsimas said.

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Startup making reusable emergency housing wins MIT $100K competition

A startup making emergency housing cheaper and faster to deploy won this year’s MIT $100K Entrepreneurship Competition on May 12.

Uplift Microhome is building reusable, modular housing units to provide housing on demand to people affected by natural disasters and other emergencies. Each of the company’s homes has its own batteries and water reservoir, allowing them to quickly be transported and placed off-grid.

“Every year, millions of Americans are displaced by natural disasters,” said co-founder Charlie Nitschelm, who is in MIT’s Leaders for Global Operations program, earning a master’s in engineering and an MBA. “If they're lucky, they can stay with friends or family. If they’re not so lucky, they could end up in a homeless shelter. But disasters aren’t just two-week problems. It takes months, sometimes years, to get back to what life was like before. Bottom line: We lack dignified and affordable housing after disasters.”

Uplift Microhome was one of seven teams chosen to pitch at the final event, which took place inside a packed Kresge Auditorium. Each team got five minutes to pitch their startups before a few minutes of questioning from judges.

This year’s competition started in April with more than 80 applications. The program’s judges selected 16 teams to compete in the semifinal before whittling that number down to the finalist teams for Tuesday’s event.

“This competition isn’t just about one big night,” $100K managing director and MIT Sloan School of Management student Celine Christory said. “It’s a year-long journey for our organizers and students. It kicks off with the ‘Pitch’ event in December, moves to ‘Accelerate’ in March, and culminates in the ‘Launch’ event.”

In the pitch that won the $100,000 Danny Lewin Grand Prize, Nitschelm said it takes an average of four months for the U.S. Federal Emergency Management Agency (FEMA) to deploy single-use housing after a disaster. That’s because these homes require power and utilities in addition to extensive foundation preparation.

“As a result, less than 1 percent of survivors actually receive a physical home,” Nitschelm said. “The rest get a check and are told to go figure it out. This isn’t just our opinion. The Department of Homeland Security audited FEMA and recommended providing a cost-effective housing alternative that allows disaster survivors to stay close to their home.”

Uplift’s homes can be transported on the back of a tractor trailer and deployed using a standard forklift. In addition to its battery and water reservoir, the homes feature self-leveling bases that allow them to be deployed on uneven terrain.

“That dramatically simplifies delivery, installation, and deactivation to the point where you can economically recover, refurbish, and redeploy the unit,” says co-founder Trevor O’Leary, a student at Harvard Business School.

The company has already built a home and believes it can manufacture each unit at a cost similar to the cheapest tractor trailer while delivering housing in hours. The company expects the marginal cost of reusing each unit to be an order of magnitude less expensive than current solutions. Down the line, it plans to deploy homes to combat housing insecurity, for seasonal workers and during construction projects. It plans to manufacture its homes in the United States.

The second-place $50,000 David T. Morgenthaler Founder’s Prize was awarded to the startup Mohan, which is using generative artificial intelligence to map the Earth’s subsurface in three dimensions. The company is deploying its technology to help mining companies decide where to drill, starting by targeting copper deposits.

“Everyone is talking about AI and chips, but no one is talking about what they sit on: copper,” said co-founder Hongze Bo, a PhD student in MIT’s Department of Earth, Atmospheric and Planetary Sciences. “Every cable, GPU, and data center depends on copper. By 2030, we’re going to be 4 million tons of copper short. But we don't know where the next deposit is. Today we just drill and hope.”

The core of Mohan’s technology is a diffusion AI model that iteratively removes noise from subsurface data to create underground scans. The company also develops its own subsurface data.

“We built a full, 3D subsurface model using generative AI,” explained Bo. “It’s the same technology behind [image generation tools] Sora and Midjourney.”

The third place $5,000 prize went to Iceberg Systems, which is using autonomous AI agents to predict how risk cascades across the economy. The company invented a new class of AI systems at MIT that coordinates millions of AIs to simulate how risks emerge through interaction. It has been working with the Department of Energy.

“Iceberg simulates behaviors across millions of market participants, from brokers to consumers to institutions, to simulate and predict how shocks cascade through their interactions and create systemic risk in the economy,” says co-founder and MIT PhD student Ayush Chopra.

The $5,000 Audience Choice Prize went to Pixology, an agentic AI platform that creates on-brand, sponsor-ready sports content to help monetize live moments.

The other finalists that presented at this year’s event were:

• NeuralPhysics, which is building foundation physics models and agents for hardware design simulation and manufacturing;
• DesignFlownAI, a design intelligence app embedded in computer-aided design software to give engineers insights in real time; and
• Auto Lab, an autonomous AI platform that helps teams build better models faster. 

The $100K Entrepreneurship Competition is one of MIT’s annual flagship entrepreneurial events. It began more than 30 years ago when a group of students, along with the late Ed Roberts, who was the founder and chair of the Martin Trust Center for MIT Entrepreneurship, decided to start a startup pitch competition.

The prize started at $10,000 then grew to $50,000 before reaching today’s $100,000 grand prize. Past participants include HubSpot, Akamai, and Lightmatter.

In addition to the prizes, teams received mentorship from venture capitalists, serial entrepreneurs, corporate executives, and attorneys; funding for prototypes; business plan feedback; and more.

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Big strides in cancer detection and treatment from the tiniest technologies

That there is tremendous potential for nanotechnology to transform cancer detection and treatment is a vision that has guided faculty at the Marble Center for Cancer Nanomedicine through its first 10 years. 

On April 9, the center gathered researchers, entrepreneurs, clinicians, industry collaborators, and members of the public at the Broad Institute of MIT and Harvard and the Koch Institute for Integrative Cancer Research galleries to celebrate a milestone anniversary and reflect on its journey.

“Our purpose has always been clear: to empower discovery and community in nanomedicine at MIT,” said Sangeeta Bhatia, faculty director at the Marble Center for Cancer Nanomedicine and the John J. and Dorothy Wilson Professor of Health Sciences and Technology and Electrical Engineering and Computer Science at MIT.

“A decade in, we are seeing that vision materialize not just in publications, but in our community, our startups, and ultimately, in patients whose lives are being changed,” Bhatia told an audience of about 150 gathered in person for the celebration.

The event featured an overview of the Marble Center by Bhatia and a perspective on nanomedicine by Robert S. Langer, the David H. Koch (1962) Institute Professor and faculty member at the Marble Center. 

A panel on translational nanomedicine followed the talks. It was moderated by Susan Hockfield, president emerita and professor of neuroscience at MIT, and included Noor Jailkhani, former MIT postdoc in the laboratory of the late MIT professor of biology Richard Hynes and CEO, co-founder and president of Matrisome Bio; Peter DeMuth ’13, chief scientific officer at Elicio Therapeutics; Vadim Dudkin, founding chief technology officer at Soufflé Therapeutics; and Viktor Adalsteinsson ’15, co-founder of Amplifyer Bio and director of the Gerstner Center for Cancer Diagnostics at the Broad Institute.

A decade of impact in nanomedicine

Established in 2016 through a generous gift from Kathy and Curt Marble ’63, the Marble Center brings together leading Koch Institute faculty members and their teams to focus on grand challenges in cancer detection, treatment, and monitoring through miniaturization and convergence — the blending of the life and physical sciences with engineering, a core concept fueling multidisciplinary research at the Koch Institute. 

At the center’s founding, Bhatia and Langer were joined by five additional faculty members: Daniel G. Anderson, professor of chemical engineering and member of the Institute for Medical Engineering and Science; Angela M. Belcher, the James Mason Crafts Professor in the departments of Biological Engineering and Materials Science and Engineering; Michael Birnbaum, professor of biological engineering; Paula T. Hammond, Institute professor and dean of the School of Engineering; and Darrell J. Irvine, who is now professor and vice-chair at the Department of Immunology and Microbiology at the Scripps Research Institute in La Jolla, California.

“Over the past decade, the center and its member laboratories have trained close to 500 researchers. Among them, 109 have become faculty in 79 clinical and research universities. We also have worked in close collaboration with clinical and industry partners to produce the results you are seeing today,” said Tarek Fadel, associate director of the Marble Center and director of strategic alliance at the Koch Institute. 

“Twenty-three startup companies have emerged from Marble Center laboratories during that time with companies such as Cision Vision, Soufflé Therapeutics, Orna Therapeutics, Matrisome Bio, Amplifyer Bio, Gensaic, among several others that hold so much promise for the early detection of disease and drug delivery,” Fadel added.

The Marble Center has launched several topical programs aimed at trainee development and industry engagement. At monthly seminars, trainees at the Marble Center lead an open forum on emerging issues in their fields. The Convergence Scholars Program, which was originally launched in 2017 to further the development of postdocs beyond the laboratory bench, is now a competitive award program offered to postdocs at the Koch Institute. Through an industry affiliate program, the center worked closely with several key players in the field of nanoscience. Industry collaborators mentor trainees and participate as judges in an annual poster symposium. 

More recently, MIT-wide grants have catalyzed new collaborations: In 2023, the Global Oncology in Nanomedicine grant supported a project on leveraging AI-based approaches to speed the development of RNA vaccines and other RNA therapies. The project was led by Giovanni Traverso, the Karl Van Tassel (1925) Career Development Professor and a professor of mechanical engineering.

From lab to clinic: Lessons in nanomedicine translation

Panelists at the anniversary event shared candid reflections on the often messy, but exhilarating process of turning their ideas into commercial technologies. 

DeMuth described how Elicio Therapeutics, whose core technologies originated from his graduate research in Irvine’s group, harnesses the natural power of the lymph nodes to generate enhanced immune responses against tumors. The amphiphile platform uses the body’s natural albumin transport system to “shuttle” medicines into the lymph nodes, boosting immune cell activation. Elicio is now advancing their platform through a Phase 2 trial in pancreatic ductal adenocarcinoma and colorectal cancer.  

Jailkhani co-founded Matrisome Bio with Bhatia and Hynes. Matrisome Bio is pioneering a new class of therapies, small protein binders called nanobodies that deliver potent payloads directly to the extracellular matrix of tumors and metastases while sparing normal tissues. Matrisome Bio is currently testing radioligand modalities with their targeting platform for the treatment of cancer. 

Adalsteinsson co-founded Amplifyer Bio with Bhatia and J. Christopher Love, the Raymond A. (1921) and Helen E. St. Laurent Professor of Chemical Engineering and associate director of the Koch Institute, with the goal of developing priming agents for liquid biopsy. Priming agents injected before a blood draw transiently slow the clearance of cell-free DNA from the bloodstream, thus allowing up to 100-fold more tumor DNA to be recovered for liquid biopsy applications. While injection for medical diagnostics has been done for decades in the context of imaging scans, Amplifyer Bio’s approach would be the first of its kind in the field of liquid biopsy.

Dudkin described Soufflé Therapeutics’ vision to enable targeted delivery with receptor-mediated uptake to any type of cell in the human body. Soufflé Therapeutics is working to engineer cell-specific ligands to deliver siRNA-based medicines that are precise and transferred across the cell membrane to their target, by combining proprietary technologies for identification of cell-specific receptors, ligand optimization, and potent siRNA engineering. 

Panelists stressed that successful translation requires complex choices. While platform technologies can theoretically address many cancer problems, startups must focus on specific indications and clinical modalities to succeed in resource-limited, commercial settings. While the academic lab offers freedom to explore multiple applications, commercialization demands strategic narrowing of scope. 

Reproducibility during scale-up emerged as another critical consideration: Founders building platform companies must demonstrate not only that their technology works, but that their underlying discovery is reproducible and robust enough to support a business. All panelists agreed that thinking about manufacturability early in research, rather than as an afterthought, significantly improves a startup’s path to the clinic. Highlighting tension between selecting cutting-edge approaches and managing their inherent regulatory risks, they recommended minimizing risk by leveraging established processes and chemistries that have already been validated in approved drugs.

Finally, panelists highlighted the importance of institutional collaborations, particularly with centers like the Marble Center for Cancer Nanomedicine. These partnerships offer access to collaborative, mission-driven researchers who can push technological boundaries, while startups maintain focus on narrow clinical applications. Panelists emphasized that faculty collaborators, such as at the Marble Center, often provide “big sky thinking” that explores new directions and applications that complement the company’s core mission.

The next chapter in nanomedicine at MIT

As the Marble Center enters its second decade, the community is focused on expanding collaborations, leveraging advances in computation and other intersecting disciplines, and exploring new disease indications. 

“The next 10 years will be defined by our ability to leverage insights gained at the nanoscale to push the boundaries of precision medicine. The Marble Center is in a unique position to do just that, as we evolve this incredible community at MIT to be a global hub for nanomedicine research,” said Bhatia. 

Bhatia also announced that in June, the Marble Center will launch a new grant, Integrated Nanoscale Sensing, Imaging, and Health Technologies (INSIHT), aimed at advancing new imaging and sensing technologies for precision medicine. 

Similarly, panelists expressed optimism about nanomedicine’s transformative potential, centered on precision medicine. The field, they argued, will focus on minimizing side effects while opening previously unavailable therapeutic windows — enabling treatments that are fundamentally more targeted and effective. This precision could render many currently untreatable diseases manageable, or even curable, while also enabling in some cases the repurposing of drugs that failed in earlier clinical contexts. 

“Ten years ago, Sangeeta, Tyler Jacks, and the Marble Center community had a vision” said Matthew Vander Heiden, director of the Koch Institute and Lester Wolfe (1919) Professor of Molecular Biology. 

“Today, that vision is creating a place where bold ideas turn into transformative advances that can help cancer patients and non-cancer patients as well. It is exciting to see this momentum in nanomedicine at MIT and what will happen in the coming decade.” 

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