How is the world watching the 2024 US election?

No matter the outcome, the results of the 2024 United States presidential election are certain to have global impact. How are citizens and leaders in other parts of the world viewing this election? What’s at stake for their countries and regions?

This was the focus of “The 2024 US Presidential Election: The World is Watching,” a Starr Forum held earlier this month on the MIT campus.

The Starr Forum is a public event series hosted by MIT’s Center for International Studies (CIS), and focused on leading issues of global interest. The event was moderated by Evan Lieberman, director of CIS and the Total Professor of Political Science and Contemporary Africa.

Experts in African, Asian, European, and Latin American politics assembled to share ideas with one another and the audience.

Each offered informed commentary on their respective regions, situating their observations within several contexts including the countries’ style of government, residents’ perceptions of American democratic norms, and America’s stature in the eyes of those countries’ populations.

Perceptions of U.S. politics from across the globe

Katrina Burgess, professor of political economy at Tufts University and the director of the Henry J. Leir Institute of Migration and Human Security, sought to distinguish the multiple political identities of members of the Latin American diaspora in America and their perceptions of America’s relationship with their countries.

“American democracy is no longer perceived as a standard bearer,” Burgess said. “While members of these communities see advantages in aligning themselves with one of the presidential candidates because of positions on economic relations, immigration, and border security, others have deeply-held views on fossil fuels and increased access to sustainable energy solutions.”

Prerna Singh, Brown University’s Mahatma Gandhi Professor of Political Science and International Studies, spoke about India’s status as the world’s largest democracy and described a country moving away from democratic norms.

“Indian leaders don’t confer with the press,” she said. “Indian leaders don’t debate like Americans.”

The ethnically and linguistically diverse India, Singh noted, has elected several women to its highest government posts, while the United States has yet to elect one. She described a brand of “exclusionary nationalism” that threatened to move India away from democracy and toward something like authoritarian rule. 

John Githongo, the Robert E. Wilhelm Fellow at CIS for 2024-25, shared his findings on African countries’ views of the 2024 election.

“America’s soft power infrastructure in Africa is crumbling,” said Githongo, a Kenyan native. “Chinese investment in Africa is up significantly and China is seen by many as an ideal political and economic partner.”

Youth-led protests in Kenya, Githongo noted, occurred in response to a failure of promised democratic reforms. He cautioned against a potential return to a pre-Cold War posture in Africa, noting that the Biden administration was the first in some time to attempt to reestablish economic and political ties with African countries.

Daniel Ziblatt, the Eaton Professor of Government at Harvard University and the director of the Minda de Gunzburg Center for European Studies, described shifting political winds in Europe that appear similar to increased right-wing extremism and a brand of populist agitation being observed in America.

“We see the rise of the radical, antidemocratic right in Europe and it looks like shifts we’ve observed in the U.S.,” he noted. “Trump supporters in Germany, Poland, and Hungary are increasingly vocal.”

Ziblatt acknowledged the divisions in the historical transatlantic relationship between Europe and America as symptoms of broader challenges. Russia’s invasion of Ukraine, energy supply issues, and national security apparatuses dependent on American support may continue to cause political ripples, he added.

Does America still have global influence?

Following each of their presentations, the guest speakers engaged in a conversation, taking questions from the audience. There was agreement among panelists that there’s less investment globally in the outcome of the U.S. election than may have been observed in past elections.

Singh noted that, from the perspective of the Indian media, India has bigger fish to fry.

Panelists diverged, however, when asked about the rise of political polarization and its connection with behaviors observed in American circles.

“This trend is global,” Burgess asserted. “There’s no causal relationship between American phenomena and other countries’ perceptions.”

“I think they’re learning from each other,” Ziblatt countered when asked about extremist elements in America and Europe. “There’s power in saying outrageous things.”

Githongo asserted a kind of “trickle-down” was at work in some African countries.

“Countries with right-leaning governments see those inclinations make their way to organizations like evangelical Christians,” he said. “Their influence mirrors the rise of right-wing ideology in other African countries and in America.”

Singh likened the continued splintering of American audiences to India’s caste system.

“I think where caste comes in is with the Indian diaspora,” she said. “Indian-American business and tech leaders tend to hail from high castes.” These leaders, she said, have outsized influence in their American communities and in India.

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Astronomers detect ancient lonely quasars with murky origins

A quasar is the extremely bright core of a galaxy that hosts an active supermassive black hole at its center. As the black hole draws in surrounding gas and dust, it blasts out an enormous amount of energy, making quasars some of the brightest objects in the universe. Quasars have been observed as early as a few hundred million years after the Big Bang, and it’s been a mystery as to how these objects could have grown so bright and massive in such a short amount of cosmic time.

Scientists have proposed that the earliest quasars sprang from overly dense regions of primordial matter, which would also have produced many smaller galaxies in the quasars’ environment. But in a new MIT-led study, astronomers observed some ancient quasars that appear to be surprisingly alone in the early universe.

The astronomers used NASA’s James Webb Space Telescope (JWST) to peer back in time, more than 13 billion years, to study the cosmic surroundings of five known ancient quasars. They found a surprising variety in their neighborhoods, or “quasar fields.” While some quasars reside in very crowded fields with more than 50 neighboring galaxies, as all models predict, the remaining quasars appear to drift in voids, with only a few stray galaxies in their vicinity.

These lonely quasars are challenging physicists’ understanding of how such luminous objects could have formed so early on in the universe, without a significant source of surrounding matter to fuel their black hole growth.

“Contrary to previous belief, we find on average, these quasars are not necessarily in those highest-density regions of the early universe. Some of them seem to be sitting in the middle of nowhere,” says Anna-Christina Eilers, assistant professor of physics at MIT. “It’s difficult to explain how these quasars could have grown so big if they appear to have nothing to feed from.”

There is a possibility that these quasars may not be as solitary as they appear, but are instead surrounded by galaxies that are heavily shrouded in dust and therefore hidden from view. Eilers and her colleagues hope to tune their observations to try and see through any such cosmic dust, in order to understand how quasars grew so big, so fast, in the early universe.

Eilers and her colleagues report their findings in a paper appearing today in the Astrophysical Journal. The MIT co-authors include postdocs Rohan Naidu and Minghao Yue; Robert Simcoe, the Francis Friedman Professor of Physics and director of MIT’s Kavli Institute for Astrophysics and Space Research; and collaborators from institutions including Leiden University, the University of California at Santa Barbara, ETH Zurich, and elsewhere.

Galactic neighbors

The five newly observed quasars are among the oldest quasars observed to date. More than 13 billion years old, the objects are thought to have formed between 600 to 700 million years after the Big Bang. The supermassive black holes powering the quasars are a billion times more massive than the sun, and more than a trillion times brighter. Due to their extreme luminosity, the light from each quasar is able to travel over the age of the universe, far enough to reach JWST’s highly sensitive detectors today.

“It’s just phenomenal that we now have a telescope that can capture light from 13 billion years ago in so much detail,” Eilers says. “For the first time, JWST enabled us to look at the environment of these quasars, where they grew up, and what their neighborhood was like.”

The team analyzed images of the five ancient quasars taken by JWST between August 2022 and June 2023. The observations of each quasar comprised multiple “mosaic” images, or partial views of the quasar’s field, which the team effectively stitched together to produce a complete picture of each quasar’s surrounding neighborhood.

The telescope also took measurements of light in multiple wavelengths across each quasar’s field, which the team then processed to determine whether a given object in the field was light from a neighboring galaxy, and how far a galaxy is from the much more luminous central quasar.

“We found that the only difference between these five quasars is that their environments look so different,” Eilers says. “For instance, one quasar has almost 50 galaxies around it, while another has just two. And both quasars are within the same size, volume, brightness, and time of the universe. That was really surprising to see.”

Growth spurts

The disparity in quasar fields introduces a kink in the standard picture of black hole growth and galaxy formation. According to physicists’ best understanding of how the first objects in the universe emerged, a cosmic web of dark matter should have set the course. Dark matter is an as-yet unknown form of matter that has no other interactions with its surroundings other than through gravity.

Shortly after the Big Bang, the early universe is thought to have formed filaments of dark matter that acted as a sort of gravitational road, attracting gas and dust along its tendrils. In overly dense regions of this web, matter would have accumulated to form more massive objects. And the brightest, most massive early objects, such as quasars, would have formed in the web’s highest-density regions, which would have also churned out many more, smaller galaxies.

“The cosmic web of dark matter is a solid prediction of our cosmological model of the Universe, and it can be described in detail using numerical simulations,” says co-author Elia Pizzati, a graduate student at Leiden University. “By comparing our observations to these simulations, we can determine where in the cosmic web quasars are located.”

Scientists estimate that quasars would have had to grow continuously with very high accretion rates in order to reach the extreme mass and luminosities at the times that astronomers have observed them, fewer than 1 billion years after the Big Bang.

“The main question we’re trying to answer is, how do these billion-solar-mass black holes form at a time when the universe is still really, really young? It’s still in its infancy,” Eilers says.

The team’s findings may raise more questions than answers. The “lonely” quasars appear to live in relatively empty regions of space. If physicists’ cosmological models are correct, these barren regions signify very little dark matter, or starting material for brewing up stars and galaxies. How, then, did extremely bright and massive quasars come to be?

“Our results show that there’s still a significant piece of the puzzle missing of how these supermassive black holes grow,” Eilers says. “If there’s not enough material around for some quasars to be able to grow continuously, that means there must be some other way that they can grow, that we have yet to figure out.”

This research was supported, in part, by the European Research Council. 

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Using spatial learning to transform math and science education

Legend has it that Isaac Newton was sitting under a tree when an apple fell on his head, sparking a bout of scientific thinking that led to the theory of gravity. It’s one of the most famous stories in science, perhaps because it shows the power of simple human experiences to revolutionize our understanding of the world around us.

About five years ago, Anurupa Ganguly ’07, MNG ’09 noticed kids don’t learn that way in schools.

“Students should learn how to use language, notation, and eventually shorthand representation of thoughts from deeply human experiences,” Ganguly says.

That’s the idea behind PrismsVR. The company offers virtual reality experiences for students, using physical learning to teach core concepts in math and science.

The platform can radically change the dynamics of the classroom, encouraging self-paced, student-led learning, where the teacher is focused on asking the right questions and sparking curiosity.

Instead of learning biology with a pen and paper, students become biomedical researchers designing a tissue regeneration therapy. Instead of learning trigonometry in a textbook, students become rural architects designing a new school building.

“We’re building a whole new learning platform, methodology, and tech infrastructure that allows students to experience problems in the first person, not through abstractions or 2D screens, and then go from that experience to ascribe meaning, language, and build up to equations, procedures, and other nomenclature,” Ganguly explains.

Today PrismsVR has been used by about 300,000 students across 35 states. The company’s approach was shown to boost algebra test scores by 11 percent in one study, with larger, multistate studies currently underway through funding from the Gates Foundation.

“Education has been in desperate need of real reform for many years,” Ganguly says. “But what’s happened is we’ve just been digitizing old, antiquated teaching methods instead. We would take a lecture and make it a video, or take a worksheet and make it a web app. I think districts see us taking a more aspirational approach, with multimodal interaction and concepts at the center of learning design, and are collaborating with us to scale that instead. We want to get this to every single public school student across the U.S., and then we’re going into community colleges, higher ed, and international.”

A new paradigm for learning

Ganguly was an undergraduate and master’s student in MIT’s Department of Electrical Engineering and Computer Science. When she began as an undergrad in 2003, she estimates that women made up about 30 percent of her class in the department, but as she advanced in her studies, that number seemed to dwindle.

“It was a disappearing act for some students, and I became inspired to understand what’s happening at the K-12 levels that set some students up for success and led to fragile foundations for others,” Ganguly recalls.

As she neared the end of her graduate program in 2009, Ganguly planned to move to California to take an engineering job. But as she was walking through MIT’s Infinite Corridor one day, a sign caught her eye. It was for Teach for America, which had collaborated with MIT to recruit students into the field of teaching, particularly for high need and high poverty students.

“I was inspired by that idea that I could use my education, engineering background, and disciplined systems thinking to think through systemic change in the public sector,” says Ganguly, who became a high school physics and algebra teacher in the Boston Public Schools.

Ganguly soon left the classroom and became director of math for the district, where she oversaw curriculum and teacher upskilling. From there, Ganguly went to New York City Public Schools, where she also supported curriculum development, trying to relate abstract math concepts to students’ experiences in the real world.

“As I began to travel from school to school, working with millions of kids, I became convinced that we don’t have the tools to solve the problem I thought about at MIT — of truly leveling the playing field and building enduring identities in the mathematical sciences,” Ganguly says.

The problem as Ganguly sees it is that students’ world is 3D, complex, and multimodal. Yet most lessons are confined to paper or tablets. For other things in life, students learn through their complex experiences: through their senses, movement, and emotions. Why should math and science be any different? In 2018, the Oculus Quest VR headset was released, and Ganguly thought she had found a more effective learning medium to scale how we learn.

But starting an education company based on virtual reality at the time was audacious. The 128-gigabyte Quest was priced at $500, and there were no standards-based VR curricula or standalone VR headsets in U.S. K-12 schools.

“Investors weren’t going to touch this,” Ganguly jokes.

Luckily, Ganguly received a small amount of funding from the National Science Foundation to build her first prototype. Ganguly started with Algebra 1; performance in this class is one of the top predictors of lifetime wages but has shown a stubbornly persistent achievement gap.

Her first module, which she built during the pandemic, places students in a food hall when a sudden announcement from the mayor rings out. There’s an alarming growth of an unknown virus in the area. The students get the power to travel back in time to see how the virus is spreading, from one person’s sneeze to many people’s behaviors in a demonstration of multiplicative growth.

The people turn to dots in a simulation as the journey moves to interactive, tactile data visualization, and the students are charged with figuring out how many weeks until the hospitals run out of capacity. Once the learning design for VR was established, Ganguly continued to build experiences across the curriculum in geometry, algebra II and III, biology, chemistry, and middle school subjects. Today Prisms covers all math and science subjects in grades seven to eleven, and the company is currently building out calculus, data science, and statistics for upper and postsecondary school. By the fall of 2025, Prisms will have evergreen content up to grade level 14.

Following the experiences, students gather in small groups to reflect on the lessons and write summaries. As students go through their virtual experiences, teachers have a web dashboard to monitor each child’s progress to support and intervene where needed.

“With our solution, the role of the teacher is to be Socrates and to ask high-quality questions, not deliver knowledge” Ganguly says.

As a solo founder, Ganguly says support from MIT’s Venture Mentoring Service, which offers members of the MIT community startup guidance in the form of “board meetings” led by successful entrepreneurs, was crucial.

“The MIT founder community is different,” Ganguly says. “We’re often technical founders, building for ourselves, and we build our company’s first product. Moving from product to your go-to-market strategy and hiring is a unique journey for product-minded founders.”

From textbooks to experiences

A few years ago, Ganguly’s team was leading a classroom coaching session in a Virginia school district when a teacher told her about a student named Silas.

“The teacher was saying, ‘Silas never does anything, he just sits in the back of class,’” Ganguly recalls. “I’ve seen this like clockwork, so we just said, ‘Let’s give Silas a fresh shot and see what we can do.’ Lo and behold, Silas was the first one to finish the module and write a full synthesis report. The teacher told me that was the first time Silas has turned in an assignment with everything filled in.”

Ganguly says it’s one of thousands of anecdotes she has.

“A lot of students feel shut out of the modern math classroom because of our stubborn approach of drill and kill,” Ganguly says. “Students want to learn through great stories. They want to help people. They want to be empathetic. They want their math education to matter.”

Ganguly sees PrismsVR as a fundamentally new way for students to learn no matter where they are.

“We intend to become the next textbook,” Ganguly says. “The next textbooks will be spatial and experiential.”

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MIT linguist Irene Heim shares Schock Prize in Logic and Philosophy

Linguist Irene Heim, professor emerita in MIT’s Department of Linguistics and Philosophy, has been named a co-recipient of the 2024 Rolf Schock Prize in Logic and Philosophy.

Heim shares the award with Hans Kamp, a professor of formal logics and philosophy of language at the University of Stuttgart in Germany. Heim and Kamp are being recognized for their independent work on the “conception and early development of dynamic semantics for natural language.”

The Schock Prize in Logic and Philosophy, sometimes referred to as the Nobel Prize of philosophy, is awarded every three years by the Schock Foundation to distinguished international recipients proposed by the Royal Swedish Academy of Sciences. A prize ceremony and symposium will be held at the Royal Academy of Fine Arts in Stockholm Nov. 11-12. MIT will host a separate event on campus celebrating Heim’s achievement on Dec. 7.

A press release from the Royal Swedish Academy of Sciences explains more about the research for which Heim and Kamp were recognized:

“Natural languages are highly context-dependent — how a sentence is interpreted often depends on the situation, but also on what has been uttered before. In one type of case, a pronoun depends on an earlier phrase in a separate clause. In the mid-1970s, some constructions of this type posed a hard problem for formal semantic theory.

“Around 1980, Hans Kamp and Irene Heim each separately developed similar solutions to this problem. Their theories brought far-reaching changes in the field. Both introduced a new level of representation between the linguistic expression and its worldly interpretation and, in both, this level has a new type of linguistic meaning. Instead of the traditional idea that a clause describes a worldly condition, meaning at this level consists in the way it contributes to updating information. Based on these fundamentally new ideas, the theories provide adequate interpretations of the problematic constructions.”

This is the first time the prize has been awarded for work done in linguistics. The work has had a transformative effect on three major subfields of linguistics: the study of linguistic mental representation (syntax), the study of their logical properties (semantics), and the study of the conditions on the use of linguistic expressions in conversation (pragmatics). Heim has published dozens of texts on semantics and syntax of language.

“I am struck again and again by how our field has progressed in the 50 years since I first entered it and the 40 years since my co-awardee and I contributed the work which won the award,” Heim said. “Those old contributions now look kind of simple-minded, in some spots even confused. But — like other influential ideas in this half-century of linguistics and philosophy of language — they have been influential not just because many people ran with them, but more so because many people picked them apart and explored ever more sophisticated and satisfying alternatives to them.”

Heim, a recognized leader in the fields of syntax and semantics, was born in Germany in 1954. She studied at the University of Konstanz and the Ludwig Maximilian University of Munich, where she earned an MA in philosophy while minoring in linguistics and mathematics. She later earned a PhD in linguistics at the University of Massachusetts at Amherst. She previously taught at the University of Texas at Austin and the University of California Los Angeles before joining MIT’s faculty in 1989. 

“I am proud to think of myself as Irene’s student,” says Danny Fox, linguistics section head and the Anshen-Chomsky Professor of Language and Thought. “Irene’s work has served as the foundation of so many areas of our field, and she is rightfully famous for it. But her influence goes even deeper than that. She has taught generations of researchers, primarily by example, how to think anew about entrenched ideas (including her own contributions), how much there is to gain from careful analysis of theoretical proposals, and at the same time, how not to entirely neglect our ambitious aspirations to move beyond this careful work and think about when it might be appropriate to take substantive risks.”

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Combining next-token prediction and video diffusion in computer vision and robotics

In the current AI zeitgeist, sequence models have skyrocketed in popularity for their ability to analyze data and predict what to do next. For instance, you’ve likely used next-token prediction models like ChatGPT, which anticipate each word (token) in a sequence to form answers to users’ queries. There are also full-sequence diffusion models like Sora, which convert words into dazzling, realistic visuals by successively “denoising” an entire video sequence. 

Researchers from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) have proposed a simple change to the diffusion training scheme that makes this sequence denoising considerably more flexible.

When applied to fields like computer vision and robotics, the next-token and full-sequence diffusion models have capability trade-offs. Next-token models can spit out sequences that vary in length. However, they make these generations while being unaware of desirable states in the far future — such as steering its sequence generation toward a certain goal 10 tokens away — and thus require additional mechanisms for long-horizon (long-term) planning. Diffusion models can perform such future-conditioned sampling, but lack the ability of next-token models to generate variable-length sequences.

Researchers from CSAIL want to combine the strengths of both models, so they created a sequence model training technique called “Diffusion Forcing.” The name comes from “Teacher Forcing,” the conventional training scheme that breaks down full sequence generation into the smaller, easier steps of next-token generation (much like a good teacher simplifying a complex concept).

Diffusion Forcing found common ground between diffusion models and teacher forcing: They both use training schemes that involve predicting masked (noisy) tokens from unmasked ones. In the case of diffusion models, they gradually add noise to data, which can be viewed as fractional masking. The MIT researchers’ Diffusion Forcing method trains neural networks to cleanse a collection of tokens, removing different amounts of noise within each one while simultaneously predicting the next few tokens. The result: a flexible, reliable sequence model that resulted in higher-quality artificial videos and more precise decision-making for robots and AI agents.

By sorting through noisy data and reliably predicting the next steps in a task, Diffusion Forcing can aid a robot in ignoring visual distractions to complete manipulation tasks. It can also generate stable and consistent video sequences and even guide an AI agent through digital mazes. This method could potentially enable household and factory robots to generalize to new tasks and improve AI-generated entertainment.

“Sequence models aim to condition on the known past and predict the unknown future, a type of binary masking. However, masking doesn’t need to be binary,” says lead author, MIT electrical engineering and computer science (EECS) PhD student, and CSAIL member Boyuan Chen. “With Diffusion Forcing, we add different levels of noise to each token, effectively serving as a type of fractional masking. At test time, our system can “unmask” a collection of tokens and diffuse a sequence in the near future at a lower noise level. It knows what to trust within its data to overcome out-of-distribution inputs.”

In several experiments, Diffusion Forcing thrived at ignoring misleading data to execute tasks while anticipating future actions.

When implemented into a robotic arm, for example, it helped swap two toy fruits across three circular mats, a minimal example of a family of long-horizon tasks that require memories. The researchers trained the robot by controlling it from a distance (or teleoperating it) in virtual reality. The robot is trained to mimic the user’s movements from its camera. Despite starting from random positions and seeing distractions like a shopping bag blocking the markers, it placed the objects into its target spots.

To generate videos, they trained Diffusion Forcing on “Minecraft” game play and colorful digital environments created within Google’s DeepMind Lab Simulator. When given a single frame of footage, the method produced more stable, higher-resolution videos than comparable baselines like a Sora-like full-sequence diffusion model and ChatGPT-like next-token models. These approaches created videos that appeared inconsistent, with the latter sometimes failing to generate working video past just 72 frames.

Diffusion Forcing not only generates fancy videos, but can also serve as a motion planner that steers toward desired outcomes or rewards. Thanks to its flexibility, Diffusion Forcing can uniquely generate plans with varying horizon, perform tree search, and incorporate the intuition that the distant future is more uncertain than the near future. In the task of solving a 2D maze, Diffusion Forcing outperformed six baselines by generating faster plans leading to the goal location, indicating that it could be an effective planner for robots in the future.

Across each demo, Diffusion Forcing acted as a full sequence model, a next-token prediction model, or both. According to Chen, this versatile approach could potentially serve as a powerful backbone for a “world model,” an AI system that can simulate the dynamics of the world by training on billions of internet videos. This would allow robots to perform novel tasks by imagining what they need to do based on their surroundings. For example, if you asked a robot to open a door without being trained on how to do it, the model could produce a video that’ll show the machine how to do it.

The team is currently looking to scale up their method to larger datasets and the latest transformer models to improve performance. They intend to broaden their work to build a ChatGPT-like robot brain that helps robots perform tasks in new environments without human demonstration.

“With Diffusion Forcing, we are taking a step to bringing video generation and robotics closer together,” says senior author Vincent Sitzmann, MIT assistant professor and member of CSAIL, where he leads the Scene Representation group. “In the end, we hope that we can use all the knowledge stored in videos on the internet to enable robots to help in everyday life. Many more exciting research challenges remain, like how robots can learn to imitate humans by watching them even when their own bodies are so different from our own!”

Chen and Sitzmann wrote the paper alongside recent MIT visiting researcher Diego Martí Monsó, and CSAIL affiliates: Yilun Du, a EECS graduate student; Max Simchowitz, former postdoc and incoming Carnegie Mellon University assistant professor; and Russ Tedrake, the Toyota Professor of EECS, Aeronautics and Astronautics, and Mechanical Engineering at MIT, vice president of robotics research at the Toyota Research Institute, and CSAIL member. Their work was supported, in part, by the U.S. National Science Foundation, the Singapore Defence Science and Technology Agency, Intelligence Advanced Research Projects Activity via the U.S. Department of the Interior, and the Amazon Science Hub. They will present their research at NeurIPS in December.

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An exotic materials researcher with the soul of an explorer

Riccardo Comin says the best part of his job as a physics professor and exotic materials researcher is when his students come into his office to tell him they have new, interesting data.

“It’s that moment of discovery, that moment of awe, of revelation of something that’s outside of anything you know,” says Comin, the Class of 1947 Career Development Associate Professor of Physics. “That’s what makes it all worthwhile.”

Intriguing data energizes Comin because it can potentially grant access to an unexplored world. His team has discovered materials with quantum and other exotic properties, which could find a range of applications, such as handling the world’s exploding quantities of data, more precise medical imaging, and vastly increased energy efficiency — to name just a few. For Comin, who has always been somewhat of an explorer, new discoveries satisfy a kind of intellectual wanderlust.

As a small child growing up in the city of Udine in northeast Italy, Comin loved geography and maps, even drawing his own of imaginary cities and countries. He traveled literally, too, touring Europe with his parents; his father was offered free train travel as a project manager on large projects for Italian railroads.

Comin also loved numbers from an early age, and by about eighth grade would go to the public library to delve into math textbooks about calculus and analytical geometry that were far beyond what he was being taught in school. Later, in high school, Comin enjoyed being challenged by a math and physics teacher who in class would ask him questions about extremely advanced concepts.

“My classmates were looking at me like I was an alien, but I had a lot of fun,” Comin says.

Unafraid to venture alone into more rarefied areas of study, Comin nonetheless sought community, and appreciated the rapport he had with his teacher.

“He gave me the kind of interaction I was looking for, because otherwise it would have been just me and my books,” Comin says. “He helped transform an isolated activity into a social one. He made me feel like I had a buddy.”

By the end of his undergraduate studies at the University of Trieste, Comin says he decided on experimental physics, to have “the opportunity to explore and observe physical phenomena.”

He visited a nearby research facility that houses the Elettra Synchrotron to look for a research position where he could work on his undergraduate thesis, and became interested in all of the materials science research being conducted there. Drawn to community as well as the research, he chose a group that was investigating how the atoms and molecules in a liquid can rearrange themselves to become a glass.

“This one group struck me. They seemed to really enjoy what they were doing, and they had fun outside of work and enjoyed the outdoors,” Comin says. “They seemed to be a nice group of people to be part of. I think I cared more about the social environment than the specific research topic.”

By the time Comin was finishing his master’s, also in Trieste, and wanted to get a PhD, his focus had turned to electrons inside a solid rather than the behavior of atoms and molecules. Having traveled “literally almost everywhere in Europe,” Comin says he wanted to experience a different research environment outside of Europe.

He told his academic advisor he wanted to go to North America and was connected with Andrea Damascelli, the Canada Research Chair in Electronic Structure of Quantum Materials at the University of British Columbia, who was working on high-temperature superconductors. Comin says he was fascinated by the behavior of the electrons in the materials Damascelli and his group were studying.

“It’s almost like a quantum choreography, particles that dance together” rather than moving in many different directions, Comin says.

Comin’s subsequent postdoctoral work at the University of Toronto, focusing on optoelectronic materials — which can interact with photons and electrical energy — ignited his passion for connecting a material’s properties to its functionality and bridging the gap between fundamental physics and real-world applications.

Since coming to MIT in 2016, Comin has continued to delight in the behavior of electrons. He and Joe Checkelsky, associate professor of physics, had a breakthrough with a new class of materials in which electrons, very atypically, are nearly stationary.

Such materials could be used to explore zero energy loss, such as from power lines, and new approaches to quantum computing.

“It’s a very peculiar state of matter,” says Comin. “Normally, electrons are just zapping around. If you put an electron in a crystalline environment, what that electron will want to do is hop around, explore its neighbors, and basically be everywhere at the same time.”

The more sedentary electrons occurred in materials where a structure of interlaced triangles and hexagons tended to trap the electrons on the hexagons and, because the electrons all have the same energy, they create what’s called an electronic flat band, referring to the pattern that is created when they are measured. Their existence was predicted theoretically, but they had not been observed.

Comin says he and his colleagues made educated guesses on where to find flat bands, but they were elusive. After three years of research, however, they had a breakthrough.

“We put a sample material in an experimental chamber, we aligned the sample to do the experiment and started the measurement and, literally, five to 10 minutes later, we saw this beautiful flat band on the screen,” Comin says. “It was so clear, like this thing was basically screaming, How could you not find me before?

“That started off a whole area of research that is growing and growing — and a new direction in our field.”

Comin’s later research into certain two-dimensional materials with the thickness of single atoms and an internal structural feature of chirality, or right-handedness or left-handedness similar to how a spiral has a twist in one direction or the other, has yielded another new realm to explore.

By controlling the chirality, “there are interesting prospects of realizing a whole new class of devices” that could store information in a way that’s more robust and much more energy-efficient than current methods, says Comin, who is affiliated with MIT’s Materials Research Laboratory. Such devices would be especially valuable as the amount of data available generally and technologies like artificial intelligence grow exponentially.

While investigating these previously unknown properties of certain materials, Comin is characteristically adventurous in his pursuit.

“I embrace the randomness that nature throws at you,” he says. “It appears random, but there could be something behind it, so we try variations, switch things around, see what nature serves you. Much of what we discover is due to luck — and the rest boils down to a mix of knowledge and intuition to recognize when we’re seeing something new, something that’s worth exploring.”

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Q&A: How the Europa Clipper will set cameras on a distant icy moon

With its latest space mission successfully launched, NASA is set to return for a close-up investigation of Jupiter’s moon Europa. Yesterday at 12:06 p.m. EDT, the Europa Clipper lifted off via SpaceX Falcon Heavy rocket on a mission that will take a close look at Europa’s icy surface. Five years from now, the spacecraft will visit the moon, which hosts a water ocean covered by a water-ice shell. The spacecraft’s mission is to learn more about the composition and geology of the moon’s surface and interior and to assess its astrobiological potential. Because of Jupiter’s intense radiation environment, Europa Clipper will conduct a series of flybys, with its closest approach bringing it within just 16 miles of Europa’s surface. 

MIT Department of Earth, Atmospheric and Planetary Sciences (EAPS) Senior Research Scientist Jason Soderblom is a co-investigator on two of the spacecraft’s instruments: the Europa Imaging System and the Mapping Imaging Spectrometer for Europa. Over the past nine years, he and his fellow team members have been building imaging and mapping instruments to study Europa’s surface in detail to gain a better understanding of previously seen geologic features, as well as the chemical composition of the materials that are present. Here, he describes the mission's primary plans and goals.

Q: What do we currently know about Europa’s surface?

A: We know from NASA Galileo mission data that the surface crust is relatively thin, but we don’t know how thin it is. One of the goals of the Europa Clipper mission is to measure the thickness of that ice shell. The surface is riddled with fractures that indicate tectonism is actively resurfacing the moon. Its crust is primarily composed of water ice, but there are also exposures of non-ice material along these fractures and ridges that we believe include material coming up from within Europa.

One of the things that makes investigating the materials on the surface more difficult is the environment. Jupiter is a significant source of radiation, and Europa is relatively close to Jupiter. That radiation modifies the materials on the surface; understanding that radiation damage is a key component to understanding the composition.

This is also what drives the clipper-style mission and gives the mission its name: we clip by Europa, collect data, and then spend the majority of our time outside of the radiation environment. That allows us time to download the data, analyze it, and make plans for the next flyby.

Q: Did that pose a significant challenge when it came to instrument design?

A: Yes, and this is one of the reasons that we're just now returning to do this mission. The concept of this mission came about around the time of the Galileo mission in the late 1990s, so it's been roughly 25 years since scientists first wanted to carry out this mission. A lot of that time has been figuring out how to deal with the radiation environment.

There's a lot of tricks that we've been developing over the years. The instruments are heavily shielded, and lots of modeling has gone into figuring exactly where to put that shielding. We've also developed very specific techniques to collect data. For example, by taking a whole bunch of short observations, we can look for the signature of this radiation noise, remove it from the little bits of data here and there, add the good data together, and end up with a low-radiation-noise observation.

Q: You're involved with the two different imaging and mapping instruments: the Europa Imaging System (EIS) and the Mapping Imaging Spectrometer for Europa (MISE). How are they different from each other?

A: The camera system [EIS] is primarily focused on understanding the physics and the geology that's driving processes on the surface, looking for: fractured zones; regions that we refer to as chaos terrain, where it looks like icebergs have been suspended in a slurry of water and have jumbled around and mixed and twisted; regions where we believe the surface is colliding and subduction is occurring, so one section of the surface is going beneath the other; and other regions that are spreading, so new surface is being created like our mid-ocean ridges on Earth.

The spectrometer’s [MISE] primary function is to constrain the composition of the surface. In particular, we're really interested in sections where we think liquid water might have come to the surface. Understanding what material is from within Europa and what material is being deposited from external sources is also important, and separating that is necessary to understand the composition of those coming from Europa and using that to learn about the composition of the subsurface ocean.

There is an intersection between those two, and that's my interest in the mission. We have color imaging with our imaging system that can provide some crude understanding of the composition, and there is a mapping component to our spectrometer that allows us to understand how the materials that we're detecting are physically distributed and correlate with the geology. So there's a way to examine the intersection of those two disciplines — to extrapolate the compositional information derived from the spectrometer to much higher resolutions using the camera, and to extrapolate the geological information that we learn from the camera to the compositional constraints from the spectrometer.

Q: How do those mission goals align with the research that you've been doing here at MIT?

A: One of the other major missions that I've been involved with was the Cassini mission, primarily working with the Visual and Infrared Spectrometer team to understand the geology and composition of Saturn's moon Titan. That instrument is very similar to the MISE instrument, both in function and in science objective, and so there's a very strong connection between that and the Europa Clipper mission. For another mission, for which I’m leading the camera team, is working to retrieve a sample of a comet, and my primary function on that mission is understanding the geology of the cometary surface.

Q: What are you most excited about learning from the Europa Clipper mission?

A: I'm most fascinated with some of these very unique geologic features that we see on the surface of Europa, understanding the composition of the material that is involved, and the processes that are driving those features. In particular, the chaos terrains and the fractures that we see on the surface.

Q: It's going to be a while before the spacecraft finally reaches Europa. What work needs to be done in the meantime?

A: A key component of this mission will be the laboratory work here on Earth, expanding our spectral libraries so that when we collect a spectrum of Europa's surface, we can compare that to laboratory measurements. We are also in the process of developing a number of models to allow us to, for example, understand how a material might process and change starting in the ocean and working its way up through fractures and eventually to the surface. Developing these models now is an important piece before we collect these data, then we can make corrections and get improved observations as the mission progresses. Making the best and most efficient use of the spacecraft resources requires an ability to reprogram and refine observations in real-time.

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