Four new faculty members join the School of Architecture and Planning (SA+P) this fall, offering the MIT community creativity, knowledge, and scholarship in multidisciplinary roles.

“These individuals add considerable strength and depth to our faculty,” says Hashim Sarkis, dean of the School of Architecture and Planning. “We are excited for the academic vigor they bring to research and teaching.”

Karrie G. Karahalios ’94, MEng ’95, SM ’97, PhD ’04 joins the MIT Media Lab as a full professor of media arts and sciences. Karahalios is a pioneer in the exploration of social media and of how people communicate in environments that are increasingly mediated by algorithms that, as she has written, “shape the world around us.” Her work combines computing, systems, artificial intelligence, anthropology, sociology, psychology, game theory, design, and infrastructure studies. Karahalios’ work has received numerous honors including the National Science Foundation CAREER Award, Alfred P. Sloan Research Fellowship, SIGMOD Best Paper Award, and recognition as an ACM Distinguished Member.

Pat Pataranutaporn SM ’18, PhD ’20 joins the MIT Media Lab as an assistant professor of media arts and sciences. A visionary technologist, scientist, and designer, Pataranutaporn explores the frontier of human-AI interaction, inventing and investigating AI systems that support human thriving. His research focuses on how personalized AI systems can amplify human cognition, from learning and decision-making to self-development, reflection, and well-being. Pataranutaporn will co-direct the Advancing Humans with AI Program.

Mariana Popescu joins the Department of Architecture as an assistant professor. Popescu is a computational architect and structural designer with a strong interest and experience in innovative ways of approaching the fabrication process and use of materials in construction. Her area of expertise is computational and parametric design, with a focus on digital fabrication and sustainable design. Her extensive involvement in projects related to promoting sustainability has led to a multilateral development of skills, which combine the fields of architecture, engineering, computational design, and digital fabrication. Popescu earned her doctorate at ETH Zurich. She was named a “Pioneer” on the MIT Technology Review global list of “35 innovators under 35” in 2019.

Holly Samuelson joins the Department of Architecture as an associate professor in the Building Technology Program at MIT, teaching architectural technology courses. Her teaching and research focus on issues of building design that impact human and environmental health. Her current projects harness advanced building simulation to investigate issues of greenhouse gas emissions, heat vulnerability, and indoor environmental quality while considering the future of buildings in a changing electricity grid. Samuelson has co-authored over 40 peer-reviewed papers, winning a best paper award from the journal Energy and Building. As a recognized expert in architectural technology, she has been featured in news outlets including The Washington Post, The Boston Globe, the BBC, and The Wall Street Journal. Samuelson earned her doctor of design from Harvard University Graduate School of Design.

Peter Temin PhD ’64, the MIT Elisha Gray II Professor of Economics, emeritus, passed away on Aug. 4. He was 87. 

Temin was a preeminent economic historian whose work spanned a remarkable range of topics, from the British Industrial Revolution and Roman economic history to the causes of the Great Depression and, later in his career, the decline of the American middle class. He also made important contributions to modernizing the field of economic history through his systematic use of economic theory and data analysis.

“Peter was a dedicated teacher and a wonderful colleague, who could bring economic history to life like few before or since,” says Jonathan Gruber, Ford Professor and chair of the Department of Economics. “As an undergraduate at MIT, I knew Peter as an engaging teacher and UROP [Undergraduate Research Opportunities Program] supervisor. Later, as a faculty member, I knew him as a steady and supportive colleague. A great person to talk to about everything, from research to politics to life at the Cape. Peter was the full package: a great scholar, a great teacher, and a dedicated public goods provider.”

When Temin began his career, the field of economic history was undergoing a reorientation within the profession. Led by giants like Paul Samuelson and Robert Solow, economics had become a more quantitative, mathematically rigorous discipline, and economic historians responded by embracing the new tools of economic theory and data collection. This “new economic history” (today also known as “cliometrics”) revolutionized the field by introducing statistical analysis and mathematical modeling to the study of the past. Temin was a pioneer of this new approach, using econometrics to reexamine key historical events and demonstrate how data analysis could lead to the overturning of long-held assumptions.

A prolific scholar who authored 17 books and edited six, Temin made important contributions to an incredibly diverse set of topics. “As kindly as he was brilliant, Peter was a unique type of academic,” says Harvard University Professor Claudia Goldin, a fellow economic historian and winner of the 2023 Nobel Prize in economic sciences. “He was a macroeconomist and an economic historian who later worked on today’s social problems. In between, he studied antitrust, health care, and the Roman economy.”

Temin’s earliest work focused on American industrial development during the 19th century and honed the signature approach that quickly made him a leading economic historian — combining rigorous economic theory with a deep understanding of historical context to reexamine the past. Temin was known for his extensive analysis of the Great Depression, which often challenged prevailing wisdom. By arguing that factors beyond monetary policy — including the gold standard and a decline in consumer spending — were critical drivers of the crisis, Temin helped recast how economists think about the catastrophe and the role of monetary policy in economic downturns.

As his career progressed, Temin’s work increasingly expanded to include the economic history of other regions and periods. His later work on the Great Depression placed a greater emphasis on the international context of the crisis, and he made significant contributions to our understanding of the drivers of the British Industrial Revolution and the nature of the Roman economy.

“Peter Temin was a giant in the field of economic history, with work touching every aspect of the field and original ideas backed by careful research,” says Daron Acemoglu, Institute Professor and recipient of the 2024 Nobel Prize in economics. “He challenged the modern view of the Industrial Revolution that emphasized technological changes in a few industries, pointing instead to a broader transformation of the British economy. He took on the famous historian of the ancient world, Moses Finley, arguing that slavery notwithstanding, markets in the Roman economy — especially land markets — worked. Peter’s influence and contributions have been long-lasting and will continue to be so.”

Temin was born in Philadelphia in 1937. His parents were activists who emphasized social responsibility, and his older brother, Howard, became a geneticist and virologist who shared the 1975 Nobel Prize in medicine. Temin received his BA from Swarthmore College in 1959 and went on to earn his PhD in Economics from MIT in 1964. He was a junior fellow of Harvard University’s Society of Fellows from 1962 to 1965.

Temin started his career as an assistant professor of industrial history at the MIT Sloan School of Management before being hired by the Department of Economics in 1967. He served as department chair from 1990t o 1993 and held the Elisha Gray II professorship from 1993 to 2009. Temin won a Guggenheim Fellowship in 2001, and served as president of the Economic History Association (1995-96) and the Eastern Economic Association (2001-02).

At MIT, Temin’s scholarly achievements were matched by a deep commitment to engaging students as a teacher and advisor. “As a researcher, Peter was able to zero in on the key questions around a topic and find answers where others had been flailing,” says Christina Romer, chair of the Council of Economic Advisers under President Obama and a former student and advisee. “As a teacher, he managed to draw sleepy students into a rousing discussion that made us think we had figured out the material on our own, when, in fact, he had been masterfully guiding us. And as a mentor, he was unfailingly supportive and generous with both his time and his vast knowledge of economic history. I feel blessed to have been one of his students.”

When he became the economics department head in 1990, Temin prioritized hiring newly-minted PhDs and other junior faculty. This foresight continues to pay dividends — his junior hires included Daron Acemoglu and Abhijit Banerjee, and he launched the recruiting of Bengt Holmström for a senior faculty position. All three went on to win Nobel Prizes and have been pillars of economics research and education at MIT.

Temin remained an active researcher and author after his retirement in 2009. Much of his later work turned toward the contemporary American economy and its deep-seated divisions. In his influential 2017 book, “The Vanishing Middle Class: Prejudice and Power in a Dual Economy,” he argued that the United States had become a “dual economy,” with a prosperous finance, technology, and electronics sector on one hand and, on the other, a low-wage sector characterized by stagnant opportunity.

“There are echoes of Temin’s later writings in current department initiatives, such as the Stone Center on Inequality and Shaping the Future of Work” notes Gruber. “Temin was in many ways ahead of the curve in treating inequality as an issue of central importance for our discipline.”

In “The Vanishing Middle Class,” Temin also explored the role that historical events, particularly the legacy of slavery and its aftermath, played in creating and perpetuating economic divides. He further explored these themes in his last book, “Never Together: The Economic History of a Segregated America,” published in 2022. While Temin was perhaps best known for his work applying modern economic tools to the past, this later work showed that he was no less adept at the inverse: using historical analysis to shed light on modern economic problems.

Temin was active with MIT Hillel throughout his career, and outside the Institute, he enjoyed staying active. He could often be seen walking or biking to MIT, and taking a walk around Jamaica Pond was a favorite activity in his last few months of life. Peter and his late wife Charlotte were also avid travelers and art collectors. He was a wonderful husband, father, and grandfather, who was deeply devoted to his family.

Temin is lovingly remembered by his daughter Elizabeth “Liz” Temin and three grandsons, Colin and Zachary Gibbons and Elijah Mendez. He was preceded in death by his wife, Charlotte Temin, a psychologist and educator, and his daughter, Melanie Temin Mendez.

Artificial intelligence is changing the way businesses store and access their data. That’s because traditional data storage systems were designed to handle simple commands from a handful of users at once, whereas today, AI systems with millions of agents need to continuously access and process large amounts of data in parallel. Traditional data storage systems now have layers of complexity, which slows AI systems down because data must pass through multiple tiers before reaching the graphical processing units (GPUs) that are the brain cells of AI.

Cloudian, co-founded by Michael Tso ’93, SM ’93 and Hiroshi Ohta, is helping storage keep up with the AI revolution. The company has developed a scalable storage system for businesses that helps data flow seamlessly between storage and AI models. The system reduces complexity by applying parallel computing to data storage, consolidating AI functions and data onto a single parallel-processing platform that stores, retrieves, and processes scalable datasets, with direct, high-speed transfers between storage and GPUs and CPUs.

Cloudian’s integrated storage-computing platform simplifies the process of building commercial-scale AI tools and gives businesses a storage foundation that can keep up with the rise of AI.

“One of the things people miss about AI is that it’s all about the data,” Tso says. “You can’t get a 10 percent improvement in AI performance with 10 percent more data or even 10 times more data — you need 1,000 times more data. Being able to store that data in a way that’s easy to manage, and in such a way that you can embed computations into it so you can run operations while the data is coming in without moving the data — that’s where this industry is going.”

From MIT to industry

As an undergraduate at MIT in the 1990s, Tso was introduced by Professor William Dally to parallel computing — a type of computation in which many calculations occur simultaneously. Tso also worked on parallel computing with Associate Professor Greg Papadopoulos.

“It was an incredible time because most schools had one super-computing project going on — MIT had four,” Tso recalls.

As a graduate student, Tso worked with MIT senior research scientist David Clark, a computing pioneer who contributed to the internet’s early architecture, particularly the transmission control protocol (TCP) that delivers data between systems.

“As a graduate student at MIT, I worked on disconnected and intermittent networking operations for large scale distributed systems,” Tso says. “It’s funny — 30 years on, that’s what I’m still doing today.”

Following his graduation, Tso worked at Intel’s Architecture Lab, where he invented data synchronization algorithms used by Blackberry. He also created specifications for Nokia that ignited the ringtone download industry. He then joined Inktomi, a startup co-founded by Eric Brewer SM ’92, PhD ’94 that pioneered search and web content distribution technologies.

In 2001, Tso started Gemini Mobile Technologies with Joseph Norton ’93, SM ’93 and others. The company went on to build the world’s largest mobile messaging systems to handle the massive data growth from camera phones. Then, in the late 2000s, cloud computing became a powerful way for businesses to rent virtual servers as they grew their operations. Tso noticed the amount of data being collected was growing far faster than the speed of networking, so he decided to pivot the company.

“Data is being created in a lot of different places, and that data has its own gravity: It’s going to cost you money and time to move it,” Tso explains. “That means the end state is a distributed cloud that reaches out to edge devices and servers. You have to bring the cloud to the data, not the data to the cloud.”

Tso officially launched Cloudian out of Gemini Mobile Technologies in 2012, with a new emphasis on helping customers with scalable, distributed, cloud-compatible data storage.

“What we didn’t see when we first started the company was that AI was going to be the ultimate use case for data on the edge,” Tso says.

Although Tso’s research at MIT began more than two decades ago, he sees strong connections between what he worked on and the industry today.

“It’s like my whole life is playing back because David Clark and I were dealing with disconnected and intermittently connected networks, which are part of every edge use case today, and Professor Dally was working on very fast, scalable interconnects,” Tso says, noting that Dally is now the senior vice president and chief scientist at the leading AI company NVIDIA. “Now, when you look at the modern NVIDIA chip architecture and the way they do interchip communication, it’s got Dally’s work all over it. With Professor Papadopoulos, I worked on accelerate application software with parallel computing hardware without having to rewrite the applications, and that’s exactly the problem we are trying to solve with NVIDIA. Coincidentally, all the stuff I was doing at MIT is playing out.”

Today Cloudian’s platform uses an object storage architecture in which all kinds of data —documents, videos, sensor data — are stored as a unique object with metadata. Object storage can manage massive datasets in a flat file stucture, making it ideal for unstructured data and AI systems, but it traditionally hasn’t been able to send data directly to AI models without the data first being copied into a computer’s memory system, creating latency and energy bottlenecks for businesses.

In July, Cloudian announced that it has extended its object storage system with a vector database that stores data in a form which is immediately usable by AI models. As the data are ingested, Cloudian is computing in real-time the vector form of that data to power AI tools like recommender engines, search, and AI assistants. Cloudian also announced a partnership with NVIDIA that allows its storage system to work directly with the AI company’s GPUs. Cloudian says the new system enables even faster AI operations and reduces computing costs.

“NVIDIA contacted us about a year and a half ago because GPUs are useful only with data that keeps them busy,” Tso says. “Now that people are realizing it’s easier to move the AI to the data than it is to move huge datasets. Our storage systems embed a lot of AI functions, so we’re able to pre- and post-process data for AI near where we collect and store the data.”

AI-first storage

Cloudian is helping about 1,000 companies around the world get more value out of their data, including large manufacturers, financial service providers, health care organizations, and government agencies.

Cloudian’s storage platform is helping one large automaker, for instance, use AI to determine when each of its manufacturing robots need to be serviced. Cloudian is also working with the National Library of Medicine to store research articles and patents, and the National Cancer Database to store DNA sequences of tumors — rich datasets that AI models could process to help research develop new treatments or gain new insights.

“GPUs have been an incredible enabler,” Tso says. “Moore’s Law doubles the amount of compute every two years, but GPUs are able to parallelize operations on chips, so you can network GPUs together and shatter Moore’s Law. That scale is pushing AI to new levels of intelligence, but the only way to make GPUs work hard is to feed them data at the same speed that they compute — and the only way to do that is to get rid of all the layers between them and your data.”

If you’ve urgently ordered a package from Amazon — and exhaled when it arrived on your doorstep hours later — you likely have three graduates of the MIT Leaders for Global Operations (LGO) program to thank: John Tagawa SM ’99; Diego Méndez de la Luz MNG ’04, MBA ’11, SM ’11; or Chuck Cummings MBA ’11, SM ’11.

Each holds critical roles within the company. Tagawa oversees Amazon’s North American operations. Méndez de la Luz heads up operations in Mexico. Cummings leads customer fulfillment throughout Canada. They also mentor LGO students and recent graduates throughout the organization and credit LGO’s singular blend of operational and leadership strength for their success as Amazon grows.

John Tagawa

Tagawa came to Amazon — now the world’s largest online retailer — through an LGO alumni connection in 2008, joining the organization during rapid expansion. He led fulfillment centers on the West Coast and went on to oversee operations in India, South America, and in Europe, with a focus on safety, speed, and efficiency.

Today, he’s a resource for other LGO graduates at Amazon, applauding the program’s uniquely multidimensional focus on tech, engineering, and leadership, all of which are key pillars as the organization continues to grow.

“Today, we have hundreds of fulfillment centers worldwide, and Amazon has grown its transportation and last-mile delivery network in an effort to ensure greater resilience and speed in getting products to customers,” he explains.

Tagawa says that LGO’s unique dual-degree program provided a singular blueprint for success as an operations leader and an engineer.

“The technology and engineering education that I received at MIT plays directly into my day-to-day role. We’re constantly thinking about how to infuse technology and innovate at scale to improve outcomes for our employees and customers. That ranges from introducing robotics to our fulfillment centers to using AI to determine how much inventory we should buy and where we should place it to introducing technology on the shop floor to help our frontline leaders. Those components of my LGO education were critical,” he says. 

After receiving his undergraduate degree at the University of Washington, Tagawa pursued engineering and operations roles. But it wasn’t until LGO that he realized how important the fusion of business, operations, and leadership competencies was.

“What drew me to LGO was being able to study business and finance, coupled with an engineering and leadership education. I hadn’t realized how powerful bringing all three of those disciplines together could be,” he reflects. “Amazon’s efficacy relies on how great our leaders are, and a big part of my role is to develop, coach, and build a great leadership team. The foundation of my ability to do that is based on what I learned at MIT about becoming a lifelong learner.”

Tagawa recalls his own classes with Donald Davis, the late chair and CEO of The Stanley Works. Davis was one of LGO’s first lecturers, sharing case studies from his time on the front lines. Davis imparted the concepts of servant-leadership and diversity, which shaped Tagawa’s outlook at Amazon.

“I get energized by the leadership principles at Amazon. We strive to be Earth's best employer​​ and being customer-obsessed. It’s energizing to lead large-scale organizations whose sole mission is to improve the lives of our employees and customers, with a strong focus on developing great leaders. Who could ask for something better than that?” he asks.

Diego Méndez de la Luz

This blend of leadership acumen and engineering dynamism also jump-started the career of Méndez de la Luz, now Amazon’s country director of Mexico operations. LGO’s leadership focus was crucial in preparing him for his Amazon role, where he oversees the vast majority of Amazon’s 10,000 employees in Mexico — those who work in operations — across 40 facilities throughout his home country.

At MIT, he took classes with notable professors, whom he credits with broadening his intellectual and professional horizons. 

“I was a good student throughout my education, but only after joining LGO did I learn what I consider to be foundational concepts and skills,” says Méndez de la Luz, who also started his career in engineering. “I learned about inventory management, business law, accounting, and about how to have important conversations in the workplace — things I never learned as an engineer. LGO was tremendously useful.”

Méndez de la Luz joined Amazon shortly after LGO, working his way up from frontline management roles at fulfillment centers throughout the United States. Today, he oversees the end-to-end network of imports, fulfillment, transportation, and customer delivery.

At Amazon, he believes he’s making a real difference in his native country. With Amazon’s scale comes the responsibility to improve both the planet and local communities, he says. Amazon engages with communities through volunteer programs, literacy efforts, and partnerships with shelters.

Today, Méndez de la Luz says that he’s working in his “dream job — exactly what I went to MIT for,” in a community he loves.

“My role at Amazon is a great source of pride. When I was growing up, I wanted to be the president of Mexico. I still want to make a difference for people in our society. Here, I have the ability to come back to my home country to create good jobs. Having the ability to do that has been a surprise to me — but a very positive development that I just value so much,” he says. “I want people to feel excited that they’re going to come to work and see their friends and colleagues do well.”

Chuck Cummings

This collaborative atmosphere propelled Cummings to pursue a post-MIT career at Amazon after years as a mechanical engineer. He discovered a hospitable workplace that valued growth: He began as an operations management intern, and today he leads the customer fulfillment business in Canada, which includes the country’s fulfillment centers. It’s a big job made better by his LGO expertise, where he always strives for co-worker and customer satisfaction.

“I sought out LGO because I’ve always loved the shop floor,” he says. “I continue to get excited about: How do we offer faster speeds to Canadian customers? How do we keep lowering our cost structure so that we can continue to invest and offer new benefits for our customers? At the same time, how do I build the absolute best working environment for all of my employees?”

Last year, Cummings’ team launched an Amazon robotics fulfillment center in Calgary, Alberta. This was a significant enhancement for Canadian customers; now, Calgary shoppers have more inventory much closer to home, with delivery speeds to match. Cummings also helped to bring Amazon’s storage and distribution network to a new facility in Vancouver, British Columbia, which will enable nearby fulfillment centers to respond to a wider selection of customer orders at the fastest-possible delivery speeds.

These were substantial endeavors, which he felt comfortable undertaking thanks to his classes at MIT. His experience was so meaningful that Cummings now serves as Amazon’s co-school captain for LGO, where he recruits the next generation of LGO graduates for internships and full-time roles. Cummings has now worked with more than 25 LGO graduates, and he says they’re easy to pick out of a crowd.

“You can give them very ambiguous, complex problems, and they can dive into the data and come out with an amazing solution. But what makes LGO students even more special is, at the same time, they have strong communication skills. They have a lot of emotional intelligence. It’s a combination of business leadership with extreme technical understanding,” he says.

Both Tagawa and Méndez de la Luz interact frequently with LGO students, too. They agree that, while Amazon’s technology is always unfolding, its leadership qualities remain constant — and match perfectly with LGO’s reputation for creating dynamic, empathetic professionals who also prize technical skill.

“Whereas technology has grown and changed by leaps and bounds, leadership principles carry on for decades,” Tagawa says. “The infusion of the engineering, business, and leadership components at LGO are second to none.”

A new strategy for strengthening polymer materials could lead to more durable plastics and cut down on plastic waste, according to researchers at MIT and Duke University.

Using machine learning, the researchers identified crosslinker molecules that can be added to polymer materials, allowing them to withstand more force before tearing. These crosslinkers belong to a class of molecules known as mechanophores, which change their shape or other properties in response to mechanical force.

“These molecules can be useful for making polymers that would be stronger in response to force. You apply some stress to them, and rather than cracking or breaking, you instead see something that has higher resilience,” says Heather Kulik, the Lammot du Pont Professor of Chemical Engineering at MIT, who is also a professor of chemistry and the senior author of the study.

The crosslinkers that the researchers identified in this study are iron-containing compounds known as ferrocenes, which until now had not been broadly explored for their potential as mechanophores. Experimentally evaluating a single mechanophore can take weeks, but the researchers showed that they could use a machine-learning model to dramatically speed up this process.

MIT postdoc Ilia Kevlishvili is the lead author of the open-access paper, which appeared Friday in ACS Central Science. Other authors include Jafer Vakil, a Duke graduate student; David Kastner and Xiao Huang, both MIT graduate students; and Stephen Craig, a professor of chemistry at Duke.

The weakest link

Mechanophores are molecules that respond to force in unique ways, typically by changing their color, structure, or other properties. In the new study, the MIT and Duke team wanted to investigate whether they could be used to help make polymers more resilient to damage.

The new work builds on a 2023 study from Craig and Jeremiah Johnson, the A. Thomas Guertin Professor of Chemistry at MIT, and their colleagues. In that work, the researchers found that, surprisingly, incorporating weak crosslinkers into a polymer network can make the overall material stronger. When materials with these weak crosslinkers are stretched to the breaking point, any cracks propagating through the material try to avoid the stronger bonds and go through the weaker bonds instead. This means the crack has to break more bonds than it would if all of the bonds were the same strength.

To find new ways to exploit that phenomenon, Craig and Kulik joined forces to try to identify mechanophores that could be used as weak crosslinkers.

“We had this new mechanistic insight and opportunity, but it came with a big challenge: Of all possible compositions of matter, how do we zero in on the ones with the greatest potential?” Craig says. “Full credit to Heather and Ilia for both identifying this challenge and devising an approach to meet it.”

Discovering and characterizing mechanophores is a difficult task that requires either time-consuming experiments or computationally intense simulations of molecular interactions. Most of the known mechanophores are organic compounds, such as cyclobutane, which was used as a crosslinker in the 2023 study.

In the new study, the researchers wanted to focus on molecules known as ferrocenes, which are believed to hold potential as mechanophores. Ferrocenes are organometallic compounds that have an iron atom sandwiched between two carbon-containing rings. Those rings can have different chemical groups added to them, which alter their chemical and mechanical properties.

Many ferrocenes are used as pharmaceuticals or catalysts, and a handful are known to be good mechanophores, but most have not been evaluated for that use. Experimental tests on a single potential mechanophore can take several weeks, and computational simulations, while faster, still take a couple of days. Evaluating thousands of candidates using these strategies is a daunting task.

Realizing that a machine-learning approach could dramatically speed up the characterization of these molecules, the MIT and Duke team decided to use a neural network to identify ferrocenes that could be promising mechanophores.

They began with information from a database known as the Cambridge Structural Database, which contains the structures of 5,000 different ferrocenes that have already been synthesized.

“We knew that we didn’t have to worry about the question of synthesizability, at least from the perspective of the mechanophore itself. This allowed us to pick a really large space to explore with a lot of chemical diversity, that also would be synthetically realizable,” Kevlishvili says.

First, the researchers performed computational simulations for about 400 of these compounds, allowing them to calculate how much force is necessary to pull atoms apart within each molecule. For this application, they were looking for molecules that would break apart quickly, as these weak links could make polymer materials more resistant to tearing.

Then they used this data, along with information on the structure of each compound, to train a machine-learning model. This model was able to predict the force needed to activate the mechanophore, which in turn influences resistance to tearing, for the remaining 4,500 compounds in the database, plus an additional 7,000 compounds that are similar to those in the database but have some atoms rearranged.

The researchers discovered two main features that seemed likely to increase tear resistance. One was interactions between the chemical groups that are attached to the ferrocene rings. Additionally, the presence of large, bulky molecules attached to both rings of the ferrocene made the molecule more likely to break apart in response to applied forces.

While the first of these features was not surprising, the second trait was not something a chemist would have predicted beforehand, and could not have been detected without AI, the researchers say. “This was something truly surprising,” Kulik says.

Tougher plastics

Once the researchers identified about 100 promising candidates, Craig’s lab at Duke synthesized a polymer material incorporating one of them, known as m-TMS-Fc. Within the material, m-TMS-Fc acts as a crosslinker, connecting the polymer strands that make up polyacrylate, a type of plastic.

By applying force to each polymer until it tore, the researchers found that the weak m-TMS-Fc linker produced a strong, tear-resistant polymer. This polymer turned out to be about four times tougher than polymers made with standard ferrocene as the crosslinker.

“That really has big implications because if we think of all the plastics that we use and all the plastic waste accumulation, if you make materials tougher, that means their lifetime will be longer. They will be usable for a longer period of time, which could reduce plastic production in the long term,” Kevlishvili says.

The researchers now hope to use their machine-learning approach to identify mechanophores with other desirable properties, such as the ability to change color or become catalytically active in response to force. Such materials could be used as stress sensors or switchable catalysts, and they could also be useful for biomedical applications such as drug delivery.

In those studies, the researchers plan to focus on ferrocenes and other metal-containing mechanophores that have already been synthesized but whose properties are not fully understood.

“Transition metal mechanophores are relatively underexplored, and they’re probably a little bit more challenging to make,” Kulik says. “This computational workflow can be broadly used to enlarge the space of mechanophores that people have studied.”

The research was funded by the National Science Foundation Center for the Chemistry of Molecularly Optimized Networks (MONET).

M.C. Escher’s artwork is a gateway into a world of depth-defying optical illusions, featuring “impossible objects” that break the laws of physics with convoluted geometries. What you perceive his illustrations to be depends on your point of view — for example, a person seemingly walking upstairs may be heading down the steps if you tilt your head sideways. 

Computer graphics scientists and designers can recreate these illusions in 3D, but only by bending or cutting a real shape and positioning it at a particular angle. This workaround has downsides, though: Changing the smoothness or lighting of the structure will expose that it isn’t actually an optical illusion, which also means you can’t accurately solve geometry problems on it.

Researchers at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) have developed a unique approach to represent “impossible” objects in a more versatile way. Their “Meschers” tool converts images and 3D models into 2.5-dimensional structures, creating Escher-like depictions of things like windows, buildings, and even donuts. The approach helps users relight, smooth out, and study unique geometries while preserving their optical illusion.

This tool could assist geometry researchers with calculating the distance between two points on a curved impossible surface (“geodesics”) and simulating how heat dissipates over it (“heat diffusion”). It could also help artists and computer graphics scientists create physics-breaking designs in multiple dimensions.

Lead author and MIT PhD student Ana Dodik aims to design computer graphics tools that aren’t limited to replicating reality, enabling artists to express their intent independently of whether a shape can be realized in the physical world. “Using Meschers, we’ve unlocked a new class of shapes for artists to work with on the computer,” she says. “They could also help perception scientists understand the point at which an object truly becomes impossible.”

Dodik and her colleagues will present their paper at the SIGGRAPH conference in August.

Making impossible objects possible

Impossible objects can’t be fully replicated in 3D. Their constituent parts often look plausible, but these parts don’t glue together properly when assembled in 3D. But what can be computationally imitated, as the CSAIL researchers found out, is the process of how we perceive these shapes.

Take the Penrose Triangle, for instance. The object as a whole is physically impossible because the depths don’t “add up,” but we can recognize real-world 3D shapes (like its three L-shaped corners) within it. These smaller regions can be realized in 3D — a property called “local consistency” — but when we try to assemble them together, they don’t form a globally consistent shape.

The Meschers approach models’ locally consistent regions without forcing them to be globally consistent, piecing together an Escher-esque structure. Behind the scenes, Meschers represents impossible objects as if we know their x and y coordinates in the image, as well as differences in z coordinates (depth) between neighboring pixels; the tool uses these differences in depth to reason about impossible objects indirectly.

The many uses of Meschers

In addition to rendering impossible objects, Meschers can subdivide their structures into smaller shapes for more precise geometry calculations and smoothing operations. This process enabled the researchers to reduce visual imperfections of impossible shapes, such as a red heart outline they thinned out.

The researchers also tested their tool on an “impossibagel,” where a bagel is shaded in a physically impossible way. Meschers helped Dodik and her colleagues simulate heat diffusion and calculate geodesic distances between different points of the model.

“Imagine you’re an ant traversing this bagel, and you want to know how long it’ll take you to get across, for example,” says Dodik. “In the same way, our tool could help mathematicians analyze the underlying geometry of impossible shapes up close, much like how we study real-world ones.”

Much like a magician, the tool can create optical illusions out of otherwise practical objects, making it easier for computer graphics artists to create impossible objects. It can also use “inverse rendering” tools to convert drawings and images of impossible objects into high-dimensional designs. 

“Meschers demonstrates how computer graphics tools don’t have to be constrained by the rules of physical reality,” says senior author Justin Solomon, associate professor of electrical engineering and computer science and leader of the CSAIL Geometric Data Processing Group. “Incredibly, artists using Meschers can reason about shapes that we will never find in the real world.”

Meschers can also aid computer graphics artists with tweaking the shading of their creations, while still preserving an optical illusion. This versatility would allow creatives to change the lighting of their art to depict a wider variety of scenes (like a sunrise or sunset) — as Meschers demonstrated by relighting a model of a dog on a skateboard.

Despite its versatility, Meschers is just the start for Dodik and her colleagues. The team is considering designing an interface to make the tool easier to use while building more elaborate scenes. They’re also working with perception scientists to see how the computer graphics tool can be used more broadly.

Dodik and Solomon wrote the paper with CSAIL affiliates Isabella Yu ’24, SM ’25; PhD student Kartik Chandra SM ’23; MIT professors Jonathan Ragan-Kelley and Joshua Tenenbaum; and MIT Assistant Professor Vincent Sitzmann. 

Their work was supported, in part, by the MIT Presidential Fellowship, the Mathworks Fellowship, the Hertz Foundation, the U.S. National Science Foundation, the Schmidt Sciences AI2050 fellowship, MIT Quest for Intelligence, the U.S. Army Research Office, U.S. Air Force Office of Scientific Research, SystemsThatLearn@CSAIL initiative, Google, the MIT–IBM Watson AI Laboratory, from the Toyota–CSAIL Joint Research Center, Adobe Systems, the Singapore Defence Science and Technology Agency, and the U.S. Intelligence Advanced Research Projects Activity.

Youssef Marzouk ’97, SM ’99, PhD ’04, the Breene M. Kerr (1951) Professor in the Department of Aeronautics and Astronautics (AeroAstro) at MIT, has been appointed associate dean of the MIT Schwarzman College of Computing, effective July 1.

Marzouk, who has served as co-director of the Center for Computational Science and Engineering (CCSE) since 2018, will work in his new role to foster a stronger community among bilingual computing faculty across MIT. A key aspect of this work will be providing additional structure and support for faculty members who have been hired into shared positions in departments and the college.

Shared faculty at MIT represent a new generation of scholars whose research and teaching integrate the forefront of computing and another discipline (positions that were initially envisioned as “bridge faculty” in the 2019 Provost’s Task Force reports). Since 2021, the MIT Schwarzman College of Computing has been steadily growing this cohort. In collaboration with 24 departments across the Institute, 20 faculty have been hired in shared positions: three in the School of Architecture and Planning; four in the School of Engineering; seven in the School of Humanities, Arts, and Social Sciences; four in the School of Science; and two in the MIT Sloan School of Management.

“Youssef’s experience leading cross-cutting efforts in research and education in CCSE is of direct relevance to the broader goal of bringing MIT’s computing bilinguals together in meaningful ways. His insights and collaborative spirit position him to make a lasting impact in this role. We are delighted to welcome him to this new leadership position in the college,” says Dan Huttenlocher, dean of the MIT Schwarzman College of Computing and the Henry Ellis Warren Professor of Electrical Engineering and Computer Science.

“I’m excited that Youssef has agreed to take on this important role in the college. His thoughtful approach and nuanced understanding of MIT’s academic landscape make him ideally suited to support our shared faculty community. I look forward to working closely with him,” says Asu Ozdaglar, deputy dean of the MIT Schwarzman College of Computing, head of the Department of Electrical Engineering and Computer Science (EECS), and the MathWorks Professor of EECS.

Marzouk’s research interests lie at the intersection of computational mathematics, statistical inference, and physical modeling. He and his students develop and analyze new methodologies for uncertainty quantification, Bayesian computation, and machine learning in complex physical systems. His recent work has centered on algorithms for data assimilation and inverse problems; high-dimensional learning and surrogate modeling; optimal experimental design; and transportation of measure as a tool for statistical inference and generative modeling. He is strongly motivated by the interplay between theory, methods, and diverse applications, and has collaborated with other researchers at MIT on topics ranging from materials science to fusion energy to the geosciences.

In 2018, he was appointed co-director of CCSE with Nicolas Hadjiconstantinou, the Quentin Berg Professor of Mechanical Engineering. An interdisciplinary research and education center dedicated to advancing innovative computational methods and applications, CCSE became one of the academic units of the MIT Schwarzman College of Computing when it formally launched in 2020.

CCSE has grown significantly under Marzouk and Hadjiconstantinou’s leadership. Most recently, they spearheaded the design and launch of the center’s new standalone PhD program in computational science and engineering, which will welcome its second cohort in September. Collectively, CCSE’s standalone and interdisciplinary PhD programs currently enroll more than 70 graduate students.

Marzouk is also a principal investigator in the MIT Laboratory for Information and Decision Systems, and a core member of MIT’s Statistics and Data Science Center.

Among his many honors and awards, he was named a fellow of the Society for Industrial and Applied Mathematics (SIAM) in 2025. He was elected associate fellow of the American Institute of Aeronautics and Astronautics (AIAA) in 2018 and received the National Academy of Engineering Frontiers of Engineering Award in 2012, the MIT Junior Bose Award for Teaching Excellence in 2012, and the DOE Early Career Research Award in 2010. His recent external engagement includes service on multiple journal editorial boards; co-chairing major SIAM conferences and elected service on various SIAM committees; leadership of scientific advisory boards, including that of the Institute for Computational and Experimental Research in Mathematics (ICERM); and organizing many other international programs and workshops.

At MIT, in addition to co-directing CCSE, Marzouk has served as both graduate and undergraduate officer of the Department of AeroAstro. He also leads the MIT Center for the Exascale Simulation of Materials in Extreme Environments, an interdisciplinary computing effort sponsored by the U.S. Department of Energy’s Predictive Science Academic Alliance program.

Marzouk received his bachelor’s, master’s, and doctoral degrees from MIT. He spent four years at Sandia National Laboratories, as a Truman Fellow and a member of the technical staff, before joining the MIT faculty in 2009.

In the push to shrink and enhance technologies that control light, MIT researchers have unveiled a new platform that pushes the limits of modern optics through nanophotonics, the manipulation of light on the nanoscale, or billionths of a meter.

The result is a class of ultracompact optical devices that are not only smaller and more efficient than existing technologies, but also dynamically tunable, or switchable, from one optical mode to another. Until now, this has been an elusive combination in nanophotonics.

The work is reported in the July 8 issue of Nature Photonics.

“This work marks a significant step toward a future in which nanophotonic devices are not only compact and efficient, but also reprogrammable and adaptive, capable of dynamically responding to external inputs. The  marriage of emerging quantum materials and established nanophotonics architectures will surely bring advances to both fields,” says Riccardo Comin, MIT’s Class of 1947 Career Development Associate Professor of Physics and leader of the work. Comin is also affiliated with MIT’s Materials Research Laboratory and Research Laboratory of Electronics (RLE).

Comin’s colleagues on the work are Ahmet Kemal Demir, an MIT graduate student in physics; Luca Nessi, a former MIT postdoc who is now a postdoc at Politecnico di Milano; Sachin Vaidya, a postdoc in RLE; Connor A. Occhialini PhD ’24, who is now a postdoc at Columbia University; and Marin Soljačić, the Cecil and Ida Green Professor of Physics at MIT.

Demir and Nessi are co-first authors of the Nature Photonics paper.

Toward new nanophotonic materials

Nanophotonics has traditionally relied on materials like silicon, silicon nitride, or titanium dioxide. These are the building blocks of devices that guide and confine light using structures such as waveguides, resonators, and photonic crystals. The latter are periodic arrangements of materials that control how light propagates, much like how a semiconductor crystal affects electron motion.

While highly effective, these materials are constrained by two major limitations. The first involves their refractive indices. These are a measure of how strongly a material interacts with light; the higher the refractive index, the more the material “grabs” or interacts with the light, bending it more sharply and slowing it down more. The refractive indices of silicon and other traditional nanophotonic materials are often modest, which limits how tightly light can be confined and how small optical devices can be made.

A second major limitation of traditional nanophotonic materials: once a structure is fabricated, its optical behavior is essentially fixed. There is usually no way to significantly reconfigure how it responds to light without physically altering it. “Tunability is essential for many next-gen photonics applications, enabling adaptive imaging, precision sensing, reconfigurable light sources, and trainable optical neural networks,” says Vaidya.

Introducing chromium sulfide bromide

These are the longstanding challenges that chromium sulfide bromide (CrSBr) is poised to solve. CrSBr is a layered quantum material with a rare combination of magnetic order and strong optical response. Central to its unique optical properties are excitons: quasiparticles formed when a material absorbs light and an electron is excited, leaving behind a positively charged “hole.” The electron and hole remain bound together by electrostatic attraction, forming a sort of neutral particle that can strongly interact with light.

In CrSBr, excitons dominate the optical response and are highly sensitive to magnetic fields, which means they can be manipulated using external controls.

Because of these excitons, CrSBr exhibits an exceptionally large refractive index that allows researchers to sculpt the material to fabricate optical structures like photonic crystals that are up to an order of magnitude thinner than those made from traditional materials. “We can make optical structures as thin as 6 nanometers, or just seven layers of atoms stacked on top of each other,” says Demir.

And crucially, by applying a modest magnetic field, the MIT researchers were able to continuously and reversibly switch the optical mode. In other words, they demonstrated the ability to dynamically change how light flows through the nanostructure, all without any moving parts or changes in temperature. “This degree of control is enabled by a giant, magnetically induced shift in the refractive index, far beyond what is typically achievable in established photonic materials,” says Demir.

In fact, the interaction between light and excitons in CrSBr is so strong that it leads to the formation of polaritons, hybrid light-matter particles that inherit properties from both components. These polaritons enable new forms of photonic behavior, such as enhanced nonlinearities and new regimes of quantum light transport. And unlike conventional systems that require external optical cavities to reach this regime, CrSBr supports polaritons intrinsically.

While this demonstration uses standalone CrSBr flakes, the material can also be integrated into existing photonic platforms, such as integrated photonic circuits. This makes CrSBr immediately relevant to real-world applications, where it can serve as a tunable layer or component in otherwise passive devices.

The MIT results were achieved at very cold temperatures of up to 132 kelvins (-222 degrees Fahrenheit). Although this is below room temperature, there are compelling use cases, such as quantum simulation, nonlinear optics, and reconfigurable polaritonic platforms, where the unparalleled tunability of CrSBr could justify operation in cryogenic environments.

In other words, says Demir, “CrSBr is so unique with respect to other common materials that even going down to cryogenic temperatures will be worth the trouble, hopefully.”

That said, the team is also exploring related materials with higher magnetic ordering temperatures to enable similar functionality at more accessible conditions.

This work was supported by the U.S. Department of Energy, the U.S. Army Research Office, and a MathWorks Science Fellowship. The work was performed in part at MIT.nano.

When surgeons repair tissues, they’re currently limited to mechanical solutions like sutures and staples, which can cause their own damage, or meshes and glues that may not adequately bond with tissues and can be rejected by the body.

Now, Tissium is offering surgeons a new solution based on a biopolymer technology first developed at MIT. The company’s flexible, biocompatible polymers conform to surrounding tissues, attaching to them in order to repair torn tissue after being activated using blue light.

“Our goal is to make this technology the new standard in fixation,” says Tissium co-founder Maria Pereira, who began working with polymers as a PhD student through the MIT Portugal Program. “Surgeons have been using sutures, staples, or tacks for decades or centuries, and they’re quite penetrating. We’re trying to help surgeons repair tissues in a less traumatic way.”

In June, Tissium reached a major milestone when it received marketing authorization from the Food and Drug Administration for its non-traumatic, sutureless solution to repair peripheral nerves. The FDA’s De Novo marketing authorization acknowledges the novelty of the company’s platform and enables commercialization of the MIT spinout’s first product. It came after studies showing the platform helped patients regain full flexion and extension of their injured fingers or toes without pain.

Tissium’s polymers can work with a range of tissue types, from nerves to cardiovascular and the abdominal walls, and the company is eager to apply its programmable platform to other areas.

“We really think this approval is just the beginning,” Tissium CEO Christophe Bancel says. “It was a critical step, and it wasn’t easy, but we knew if we could get the first one, it would begin a new phase for the company. Now it’s our responsibility to show this works with other applications and can benefit more patients.”

From lab to patients

Years before he co-founded Tissium, Jeff Karp was a postdoc in the lab of MIT Institute Professor Robert Langer, where he worked to develop elastic materials that were biodegradable and photocurable for a range of clinical applications. After graduation, Karp became an affiliate faculty member in the Harvard-MIT Program in Health Sciences and Technology. He is also a faculty member at Harvard Medical School and Brigham and Women’s Hospital. In 2008, Pereira joined Karp’s lab as a visiting PhD student through funding from the MIT Portugal Program, tuning the polymers’ thickness and ability to repel water to optimize the material’s ability to attach to wet tissue.

“Maria took this polymer platform and turned it into a fixation platform that could be used in many areas in medicine,” Karp recalls. “[The cardiac surgeon] Pedro del Nido at Boston Children’s Hospital had alerted us to this major problem of a birth defect that causes holes in the heart of newborns. There were no suitable solutions, so that was one of the applications we began working on that Maria led.”

Pereira and her collaborators went on to demonstrate they could use the biopolymers to seal holes in the hearts of rats and pigs without bleeding or complications. Bancel, a pharmaceutical industry veteran, was introduced to the technology when he met with Karp, Pereira, and Langer during a visit to Cambridge in 2012, and he spent the next few months speaking with surgeons.

“I spoke with about 15 surgeons from a range of fields about their challenges,” Bancel says. “I realized if the technology could work in these settings, it would address a big set of challenges. All of the surgeons were excited about how the material could impact their practice.”

Bancel worked with MIT’s Technology Licensing Office to take the biopolymer technology out of the lab, including patents from Karp’s original work in Langer’s lab. Pereira moved to Paris upon completing her PhD, and Tissium was officially founded in 2013 by Pereira, Bancel, Karp, Langer, and others.

“The MIT and Harvard ecosystems are at the core of our success,” Pereira says. “From the get-go, we tried to solve problems that would be meaningful for patients. We weren’t just doing research for the sake of doing research. We started in the cardiovascular space, but we quickly realized we wanted to create new standards for tissue repair and tissue fixation.”

After licensing the technology, Tissium had a lot of work to do to make it scalable commercially. The founders partnered with companies that specialize in synthesizing polymers and created a method to 3D print a casing for polymer-wrapped nerves.

“We quickly realized the product is a combination of the polymer and the accessories,” Bancel says. “It was about how surgeons used the product. We had to design the right accessories for the right procedures.”

The new system is sorely needed. A recent meta-analysis of nerve repairs using sutures found that only 54 percent of patients achieved highly meaningful recovery following surgery. By not using sutures, Tissium’s flexible polymer technology offers an atraumatic way to reconnect nerves. In a recent trial of 12 patients, all patients that completed follow up regained full flexion and extension of their injured digits and reported no pain 12 months after surgery.

“The current standard of care is suboptimal,” Pereira says. “There are variabilities in the outcome, sutures can create trauma, tension, misalignment, and all that can impact patient outcomes, from sensation to motor function and overall quality of life.”

Trauma-free tissue repair

Today Tissium has six products in development, including one ongoing clinical trial in the hernia space and another set to begin soon for a cardiovascular application.

“Early on, we had the intuition that if this were to work in one application, it would be surprising if it didn’t work in many other applications,” Bancel says.

The company also believes its 3D-printed production process will make it easier to expand.

“Not only can this be used for tissue fixation broadly across medicine, but we can leverage the 3D printing method to make all kinds of implantable medical devices from the same polymeric platform,” Karp explains. “Our polymers are programmable, so we can program the degradation, the mechanical properties, and this could open up the door to other exciting breakthroughs in medical devices with new capabilities.”

Now Tissium’s team is encouraging people in the medical field to reach out if they think their platform could improve on the standard of care — and they’re mindful that the first approval is a milestone worth celebrating unto itself.

“It’s the best possible outcome for your research to generate not just a paper, but a treatment with potential to improve the standard of care along with patients’ lives,” Karp says. “It’s the dream, and it’s an incredible feeling to be able to celebrate this with all the collaborators that have been involved along the way.”

Langer adds, “I agree with Jeff. It’s wonderful to see the research we started at MIT reach the point of FDA approval and change peoples’ lives.”

A fundamental problem for governments is getting citizens to comply with their laws and policies. They can’t monitor everyone and catch all the rule-breakers. “It’s a logistical impossibility,” says Lily L. Tsai, MIT’s Ford Professor of Political Science and the director and founder of the MIT Governance Lab.

Instead, governments need citizens to choose to follow the rules of their own accord. “As a government, you have to rely on them to voluntarily comply with the laws, policies, and regulations that are put into place,” Tsai says.

One particularly important thing governments need citizens to do is pay their taxes. In a paper in the October issue of the journal World Development, Tsai and her co-authors, including Minh Trinh ’22, a graduate of the Department of Political Science, look at different factors that might affect compliance with property tax laws in China. They found that study participants in an in-person tax-paying experiment were more likely to pay their taxes if government officials were monitoring and punishing corruption.

“When people think that government authorities are motivated by the public good, have moral character, and have integrity, then the requests that those authorities make of citizens are more likely to seem legitimate, and so they’re more likely to pay their taxes,” Tsai says.

In China, only two cities, Chongqing and Shanghai, collect property taxes. Officials have been concerned that citizens might resist property taxes because homeownership is the main source of urban household wealth in China. Private homeownership accounts for 64 percent of household wealth in China, compared to only 29 percent in the United States.

Tsai and her co-authors wanted to test how governments might make people more willing to pay their property taxes. Researchers have theorized that citizens are more likely to comply with tax laws when they feel like they’re getting something in return from the government. The government can be responsive to citizens’ demands for public services, for example. Or the government can punish officials who are corrupt or perform poorly.

In the first part of the study, a survey of Chinese citizens, respondents expressed preferences for different hypothetical property tax policies. The results suggested that participants wanted the government to be responsive to their needs and to hold officials accountable. People preferred a policy that allowed for citizen input on the use of tax revenue over one that did not, and a policy that allowed for the sanctioning of corrupt officials garnered more support than a policy that did not.

Survey participants also preferred a lighter penalty for not paying their taxes over a harsher penalty, and they supported a tax exemption for first apartments. Interestingly to the researchers, policies that allowed for government responsiveness and accountability received roughly the same support as these policies with economic benefits. “This is evidence to show that we should really pay attention to non-economic factors, because they can have similar magnitudes of impact on tax-paying behavior,” Tsai says.

For the second stage of the study, researchers recruited people for a lab experiment in Shanghai (one of the two cities that collects property taxes). Participants played a game on an iPad in which they chose repeatedly whether or not to pay property taxes. At the end of the game, they received an amount of real money that varied depending on how they and other participants played the game.

Participants were then randomly split into different groups. In one group, participants were given an opportunity to voice their preference for how their property tax revenue was used. Some were told the government incorporated their feedback, while others were told their preferences were not considered — in other words, participants learned whether or not the government was responsive to their needs. In another group, participants learned that a corrupt official had stolen money from property tax revenue. Some were told that the official had been caught and punished, while others were told the official got away with stealing.

The researchers measured whether game players’ willingness to pay property taxes changed after receiving this new information. They found that while the willingness of players who learned the government was responsive to their needs did not change significantly, players who learned the government punished corrupt officials paid their property taxes more frequently.

“It was kind of amazing to see that people care a lot about whether or not higher-level authorities are making sure that tax dollars are not being wasted through corruption,” Tsai says. She argues in her 2021 book, “When People Want Punishment: Retributive Justice and the Puzzle of Authoritarian Popularity,” that when authorities are willing to punish their own officials, it may signal to people that leaders have moral integrity and share the values of ordinary people, making them appear more legitimate.

While the researchers expected to see government responsiveness affect tax payment as well, Tsai says it’s not totally surprising that for people living in places without direct channels for citizen input, the opportunity to participate in the decision-making process in a lab setting might not resonate as strongly.

The findings don’t mean that government responsiveness isn’t important. But they suggest that even when there aren’t opportunities for citizens to make their voices heard, there are other ways for governments to appear legitimate and get people to comply with rules voluntarily.

As the strength of democratic institutions declines globally, scholars wonder whether perceptions of governments’ legitimacy will decline at the same time. “These findings suggest that maybe that’s not necessarily the case,” Tsai says.

Dean Agustín Rayo and the MIT School of Humanities, Arts, and Social Sciences (SHASS) recently welcomed 14 new professors to the MIT community. They arrive with diverse backgrounds and vast knowledge in their areas of research.

Naoki Egami joins MIT as an associate professor in the Department of Political Science. He is also a faculty affiliate of the Institute for Data, Systems, and Society. Egami specializes in political methodology and develops statistical methods for questions in political science and the social sciences. His current research programs focus on three areas: external validity and generalizability; machine learning and artificial intelligence for the social sciences; and causal inference with network and spatial data. His work has appeared in various academic journals in political science, statistics, and computer science, such as American Political Science Review, American Journal of Political Science, Journal of the American Statistical Association, Journal of the Royal Statistical Society (Series B), NeurIPS, and Science Advances. Before joining MIT, Egami was an assistant professor at Columbia University. He received a PhD from Princeton University (2020) and a BA from the University of Tokyo (2015).

Valentin Figueroa joins the Department of Political Science as an assistant professor. His research examines historical state building, ideological change, and scientific innovation, with a regional focus on Western Europe and Latin America. His current book project investigates the disestablishment of patrimonial administrations and the rise of bureaucratic states in early modern Europe. Before joining MIT, he was an assistant professor at the Pontificia Universidad Católica de Chile. Originally from Argentina, Figueroa holds a BA and an MA in political science from Universidad de San Andrés and Universidad Torcuato Di Tella, respectively, and a PhD in political science from Stanford University.

Bailey Flanigan is an assistant professor in the Department of Political Science, with a shared appointment in the MIT Schwarzman College of Computing in the Department of Electrical Engineering and Computer Science. Her research combines tools from across these disciplines — including social choice theory, game theory, algorithms, statistics, and survey methods — to advance political methodology and strengthen public participation in democracy. She is specifically interested in sampling algorithms, opinion measurement/preference elicitation, and the design of democratic innovations like deliberative minipublics and participatory budgeting. Before joining MIT, Flanigan was a postdoc at Harvard University’s Data Science Initiative. She earned her PhD in computer science from Carnegie Mellon University and her BS in bioengineering from the University of Wisconsin at Madison.

Rachel Fraser is an associate professor in the Department of Linguistics and Philosophy. Before coming to MIT, Fraser taught at Oxford University, where she also completed her graduate work in philosophy. She has interests in epistemology, language, feminism, aesthetics, and political philosophy. At present, her main project is a book manuscript on the epistemology of narrative.

Brian Hedden PhD ’12 is a professor in the Department of Linguistics and Philosophy, with a shared appointment in the MIT Schwarzman College of Computing in the Department of Electrical Engineering and Computer Science. His research focuses on how we ought to form beliefs and make decisions. He works in epistemology, decision theory, and ethics, including ethics of AI. He is the author of “Reasons without Persons: Rationality, Identity, and Time” (Oxford University Press, 2015) and articles on topics including collective action problems, legal standards of proof, algorithmic fairness, and political polarization, among others. Prior to joining MIT, he was a faculty member at the Australian National University and the University of Sydney, and a junior research fellow at Oxford. He received his BA From Princeton University in 2006 and his PhD from MIT in 2012.

Rebekah Larsen is an assistant professor in the Comparative Media Studies/Writing program. A media sociologist with a PhD from Cambridge University, her work uncovers and analyzes understudied media ecosystems, with special attention to sociotechnical change and power relations within these systems. Recent scholarly sites of inquiry include conservative talk radio stations in rural Utah (and ethnographic work in conservative spaces); the new global network of fact checkers funded by social media platform content moderation contracts; and search engine manipulation of journalists and activists around a controversial 2010s privacy regulation. Prior to MIT, Larsen held a Marie Curie grant at the University of Copenhagen, and was a visiting fellow at the Information Society Project (Yale Law School). She maintains current affiliations as a faculty associate at the Berkman Klein Center (Harvard Law School) and a research associate at the Center for Governance and Human Rights (Cambridge University).

Pascal Le Boeuf joins the Music and Theater Arts Section as an assistant professor. Described as “sleek, new,” “hyper-fluent,” and “a composer that rocks” by The New York Times, he is a Grammy Award-winning composer, jazz pianist, and producer whose works range from improvised music to hybridizing notation-based chamber music with production-based technology. Recent projects include collaborations with Akropolis Reed Quintet, Christian Euman, Jamie Lidell, Alarm Will Sound, Ji Hye Jung, Tasha Warren, Dave Eggar, Barbora Kolarova and Arx Duo, JACK Quartet, Friction Quartet, Hub New Music, Todd Reynolds, Sara Caswell, Jessica Meyer, Nick Photinos, Ian Chang, Dayna Stephens, Linda May Han Oh, Justin Brown, and Le Boeuf Brothers. He received a 2025 Grammy Award for Best Instrumental Composition, a 2024 Barlow Commission, a 2023 Guggenheim Fellowship, and a 2020 Copland House Residency Award. Le Boeuf is a Harold W. Dodds Honorific Fellow and PhD candidate in music composition at Princeton University.

Becca Lewis is an assistant professor in the Comparative Media Studies/Writing program. An interdisciplinary scholar who examines the rise of right-wing politics in Silicon Valley and online, she holds a PhD in communication theory and research from Stanford University and an MS in social science from the University of Oxford. Her work has been published in academic journals including New Media and Society, Social Media and Society, and American Behavioral Scientist, and in news outlets such as The Guardian and Business Insider. She previously worked as a researcher at the Data and Society Research Institute, where she published the organization’s flagship reports on media manipulation, disinformation, and right-wing digital media. In 2022, she served as an expert witness in the defamation lawsuit brought against Alex Jones by the parents of a Sandy Hook shooting victim.

Ben Lindquist is an assistant professor in the History Section, with a shared appointment in the MIT Schwarzman College of Computing in the Department of Electrical Engineering and Computer Science. His work observes the historical ways that computing has circulated with ideas of religion, emotion, and divergent thinking. “The Feeling Machine,” his first book, under contract with the University of Chicago Press, follows the history of synthetic speech to ask how emotion became a subject of computer science. Before coming to MIT, he was a postdoc in the Science in Human Culture Program at Northwestern University and earned his PhD in history from Princeton University.

Bar Luzon joins the Department of Linguistics and Philosophy as an assistant professor. Luzon completed her BA in philosophy in 2017 at the Hebrew University of Jerusalem, and her PhD in philosophy in 2024 at New York University. Before coming to MIT, she was a Mellon Postdoctoral Fellow in the Philosophy Department at Rutgers University. She works in the philosophy of mind and language, metaphysics, and epistemology. Her research focuses on the nature of representation and the structure of reality. In the course of pursuing these issues, she writes about mental content, metaphysical determination, the vehicles of mental representation, and the connection between truth and different epistemic notions.

Mark Rau is an assistant professor in the Music and Theater Arts Section, with a shared appointment in the MIT Schwarzman College of Computing in the Department of Electrical Engineering and Computer Science. He is involved in developing graduate programming focused on music technology. He is interested in the fields of musical acoustics, vibration and acoustic measurement, audio signal processing, and physical modeling synthesis, among other areas. As a lifelong musician, his research focuses on musical instruments and creative audio effects. Before joining MIT, he was a postdoc at McGill University and a lecturer at Stanford University. He completed his PhD at Stanford’s Center for Computer Research in Music and Acoustics. He also holds an MA in music, science, and technology from Stanford, as well as a BS in physics and BMus in jazz from McGill University.

Viola Schmitt is an associate professor in the Department of Linguistics and Philosophy. She is a linguist with a special interest in semantics. Much of her work focuses on trying to understand general constraints on human language meaning; that is, the principles regulating which meanings can be expressed by human languages and how languages can package meaning. Variants of this question were also central to grants she received from the Austrian and German research foundations. She earned her PhD in linguistics from the University of Vienna and worked as a postdoc and/or lecturer at the Universities of Vienna, Graz, Göttingen, and at the University of California at Los Angeles. Her most recent position was as a junior professor at the Humboldt University Berlin.

Angela Saini joins the Comparative Media Studies/Writing program as an assistant professor. A science journalist and author, she presents television and radio documentaries for the BBC and her writing has appeared in National Geographic, Wired, Science, and Foreign Policy. She has published four books, which have together been translated into 18 languages. Her bestselling 2019 book, “Superior: The Return of Race Science,” was a finalist for the LA Times Book Prize, and her latest, “The Patriarchs: The Origins of Inequality,” was a finalist for the Orwell Prize for Political Writing. She has an MEng from the University of Oxford, and was made an honorary fellow of her alma mater, Keble College, in 2023.

Paris Smaragdis SM ’97, PhD ’01 joins the Music and Theater Arts Section as a professor with a shared appointment in the MIT Schwarzman College of Computing in the Department of Electrical Engineering and Computer Science. He holds a BMus (cum laude ’95) from Berklee College of Music. His research lies at the intersection of signal processing and machine learning, especially as it relates to sound and music. He has been a research scientist at Mitsubishi Electric Research Labs, a senior research scientist at Adobe Research, and an Amazon Scholar with Amazon’s AWS. He spent 15 years as a professor at the University of Illinois Urbana Champaign in the Computer Science Department, where he spearheaded the design of the CS+Music program, and served as an associate director of the School of Computer and Data Science.

Imagine a ball bouncing down a flight of stairs. Now think about a cascade of water flowing down those same stairs. The ball and the water behave very differently, and it turns out that your brain has different regions for processing visual information about each type of physical matter.

In a new study, MIT neuroscientists have identified parts of the brain’s visual cortex that respond preferentially when you look at “things” — that is, rigid or deformable objects like a bouncing ball. Other brain regions are more activated when looking at “stuff” — liquids or granular substances such as sand.

This distinction, which has never been seen in the brain before, may help the brain plan how to interact with different kinds of physical materials, the researchers say.

“When you’re looking at some fluid or gooey stuff, you engage with it in different way than you do with a rigid object. With a rigid object, you might pick it up or grasp it, whereas with fluid or gooey stuff, you probably are going to have to use a tool to deal with it,” says Nancy Kanwisher, the Walter A. Rosenblith Professor of Cognitive Neuroscience; a member of the McGovern Institute for Brain Research and MIT’s Center for Brains, Minds, and Machines; and the senior author of the study.

MIT postdoc Vivian Paulun, who is joining the faculty of the University of Wisconsin at Madison this fall, is the lead author of the paper, which appears today in the journal Current Biology. RT Pramod, an MIT postdoc, and Josh Tenenbaum, an MIT professor of brain and cognitive sciences, are also authors of the study.

Stuff vs. things

Decades of brain imaging studies, including early work by Kanwisher, have revealed regions in the brain’s ventral visual pathway that are involved in recognizing the shapes of 3D objects, including an area called the lateral occipital complex (LOC). A region in the brain’s dorsal visual pathway, known as the frontoparietal physics network (FPN), analyzes the physical properties of materials, such as mass or stability.

Although scientists have learned a great deal about how these pathways respond to different features of objects, the vast majority of these studies have been done with solid objects, or “things.”

“Nobody has asked how we perceive what we call ‘stuff’ — that is, liquids or sand, honey, water, all sorts of gooey things. And so we decided to study that,” Paulun says.

These gooey materials behave very differently from solids. They flow rather than bounce, and interacting with them usually requires containers and tools such as spoons. The researchers wondered if these physical features might require the brain to devote specialized regions to interpreting them.

To explore how the brain processes these materials, Paulun used a software program designed for visual effects artists to create more than 100 video clips showing different types of things or stuff interacting with the physical environment. In these videos, the materials could be seen sloshing or tumbling inside a transparent box, being dropped onto another object, or bouncing or flowing down a set of stairs.

The researchers used functional magnetic resonance imaging (fMRI) to scan the visual cortex of people as they watched the videos. They found that both the LOC and the FPN respond to “things” and “stuff,” but that each pathway has distinctive subregions that respond more strongly to one or the other.

“Both the ventral and the dorsal visual pathway seem to have this subdivision, with one part responding more strongly to ‘things,’ and the other responding more strongly to ‘stuff,’” Paulun says. “We haven’t seen this before because nobody has asked that before.”

Roland Fleming, a professor of experimental psychology at Justus Liebig University of Geissen, described the findings as a “major breakthrough in the scientific understanding of how our brains represent the physical properties of our surrounding world.”

“We’ve known the distinction exists for a long time psychologically, but this is the first time that it’s been really mapped onto separate cortical structures in the brain. Now we can investigate the different computations that the distinct brain regions use to process and represent objects and materials,” says Fleming, who was not involved in the study.

Physical interactions

The findings suggest that the brain may have different ways of representing these two categories of material, similar to the artificial physics engines that are used to create video game graphics. These engines usually represent a 3D object as a mesh, while fluids are represented as sets of particles that can be rearranged.

“The interesting hypothesis that we can draw from this is that maybe the brain, similar to artificial game engines, has separate computations for representing and simulating ‘stuff’ and ‘things.’ And that would be something to test in the future,” Paulun says.

The researchers also hypothesize that these regions may have developed to help the brain understand important distinctions that allow it to plan how to interact with the physical world. To further explore this possibility, the researchers plan to study whether the areas involved in processing rigid objects are also active when a brain circuit involved in planning to grasp objects is active.

They also hope to look at whether any of the areas within the FPN correlate with the processing of more specific features of materials, such as the viscosity of liquids or the bounciness of objects. And in the LOC, they plan to study how the brain represents changes in the shape of fluids and deformable substances.

The research was funded by the German Research Foundation, the U.S. National Institutes of Health, and a U.S. National Science Foundation grant to the Center for Brains, Minds, and Machines.