Giving the people what they want?

At times it can feel like public opinion does not matter in U.S. politics. When the U.S. Congress or state legislatures ignore issues that have broad public support, there seems to be a glaring gap between what people want and what politicians will deliver.

But in due course, public opinion does sway elected officials, according to MIT political scientist Devin Caughey. Indeed, Caughey’s work has shown that at the state level in the U.S. over the last several decades, government policies have followed public views — often incrementally, but consistently.

“Over the long term, policymaking tends to be responsive to public opinion and move into alignment with what the public wants,” says Caughey. That has become more apparent due to innovative research Caughey and his colleagues have performed while using thousands of public-opinion opinion surveys from the 1930s onward.

But Caughey, who calls himself “a political scientist who studies historical things,” has also found the power of public opinion at work at the federal level. In his 2018 book “The Unsolid South,” published by the Princeton University Press, Caughey explores the varieties of Southern responses to the New Deal, showing how public attitudes about it varied across time and place, with Washington following suit.

Now Caughey, along with political scientist Chris Warshaw of George Washington University, is working on another large book project, “Dynamic Democracy: Citizens, Parties, and Policymakers in the American State,” about their state-level findings. On either scale, the research shows something important: Democracy works, albeit in fits and starts.

Yes, at any given moment, Caughey notes, “Policies are often mismatched with public opinion. A majority of the public may want a minimum wage of $15, but the minimum wage is $7. It happens a lot, for a variety of reasons. Then gradually the match improves. And then often polling stops, because the issues that are in alignment aren’t as controversial any more.”

Working across disciplines

Caughey hails from California, but attended high school in Pennsylvania. As an undergraduate at Yale University, he received his BA in history, mostly focusing on  Latin America and ancient Greece. But in his senior year, a seminar with political scientist David Mayhew, a leading scholar of Congress, sparked Caughey’s interest. Caughey entered a master’s program at Cambridge University, receiving an MPhil in history while writing a thesis on the New Deal and the South. Finally he pursued a PhD in political science at the University of California at Berkeley.

“I was interested in representation, the relationship between public opinion, what the people say they want, and what elites are doing, members of Congress in particular,” Caughey says. His thesis at Berkeley became the foundation for “The Unsolid South.” Caughey received his PhD in 2012 and joined MIT later that year. Now an associate professor, he was awarded tenure in 2020.

Caughey’s research at MIT has had three fronts: his work on the South and the New Deal; his research on state-level politics; and methodological work about polling data. On the last subject, Caughey and six colleagues published a short monograph in 2020 about extracting useful data from older surveys.

By contrast, “The Unsolid South” blended both political science and history to update received thinking about the South in the 1930s and 1940s.

“The conventional wisdom was and perhaps still is that Southern members of Congress were essentially unresponsive to public opinion,” Caughey says. With many of them assured of reelection, and with nearly all Black Southerners disenfranchised, the idea goes, U.S. representatives could ignore their constituents.

“What I tried to show in my book is, I don’t think that’s true,” says Caughey. “White Southerners were very supportive of the New Deal until the mid-1930s and turned very sharply against it, and so did their representatives. And similarly the kinds of states that were more supportive of the New Deal within the South had representatives that were more supportive.”

Ultimately “The Unsolid South” spoke to both political scientists and historians by highlighting how the New Deal coalition shrunk once its measures seemed likely to help Black people. In addition to winning the American Political Science Association’s award for best book on parties and political organizations, Caughey’s book received an honorable mention from the Social Science History Association.

“That for me was really gratifying, that it was speaking to a broader audience,” Caughey says.

A full picture of politics

At present, Caughey is focused on the “Dynamic Democracy” project, in which he and Warshaw scrutinize all states from 1936 to 2014.

“We can really paint this holistic picture of the political process, where we can look at public opinion, and elections, and parties, and policymaking, all within this common framework, and look at how those different pieces of the political process respond to each other over time,” Caughey says.

The project explores many intricacies regarding public opinion. Passing legislation, for one thing, can itself help solidify the public popularity of certain ideas.

“Initially Social Security was fairly popular when it was first passed [in the 1930s], but not overwhelmingly popular,” Caughey says. “But once people got Social Security, it became very, very popular.”

Public opinion also limits state-level policy radicalism by hovering in the political middle: “When policy moves to the right, it increases the number of people who thinks it should move back to the left again, and vice versa,” Caughey observes.

There is one way that political parties can get around the restraining force of public opinion: gerrymandering, which lets parties perpetuate their hold on legislatures.

“One thing that really seems to have a bad effect on the relationship between public opinion and policy outcomes is partisan gerrymandering,” Caughey notes. “The best thing we’ve found for improving the translation between public opinion and policy outcomes is taking [redistricting] power outside the hands of parties and putting in a citizens’ redistricting commission.”

Caughey and Warshaw are not taking a panglossian view of U.S. politics. Of the 1930s, Caughey says, “I don’t like to call the one-party South a democracy, because it had a number of features like the disenfranchisement of a big part of the population.”

He emphasizes the “gradations between authoritarianism and democracy. There are some democracies that don’t work quite right, that have some authoritarian features even today. But there are also a lot of authoritarian regimes that have democratic-like features and they’re not just window dressing; they do change the incentives of elites. Exploring that gray area has become a core part of the book.”

But given an appropriate level of critical thinking, Caughey’s research still suggests that democracy reflects the will of the people, over time.

“The message we’re trying to drive home in this book is that when you take a longer-term view of representation, things look better than when you look in the short term,” Caughey says. “In some ways our work is relatively optimistic about this subject.”

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3 Questions: Ian Waitz and Blanche Staton on MIT’s continuing commitment to graduate students

One of the cornerstones of the Office of the Vice Chancellor’s (OVC) mission is improving the graduate student experience at MIT. Since it was established in 2017, OVC has continued to move forward with programs and initiatives focused on alleviating financial insecurity, supporting graduate families, enhancing advising, augmenting professional development, and other key issues — even amid the disruption of the past year. Here, Ian A. Waitz, vice chancellor for undergraduate and graduate education, and Blanche Staton, senior associate dean for graduate education in the Office of Graduate Education, describe some of the Institute’s latest efforts to support graduate students.

Q: How has MIT responded to the needs of graduate students, given the challenges of the pandemic?

A: The pandemic has been tough on everyone. So much of what makes MIT special is the vibrancy of the campus. Fortunately, our phased reopening has been very successful, but there are still necessary restrictions and many of our students are living elsewhere. We all long for the day when we can once again see folks walking and biking across campus, bump into a friend or colleague, or strike up an impromptu conversation at the food trucks.

Although we have continued to make steady progress on a number of our priorities, given the urgency of the pandemic we’ve focused more attention on graduate students’ immediate needs: financial security; addressing the unique challenges facing our international student population; and easing the transition to online learning.

Short and long-term financial distress among graduate students, including financial needs due to the pandemic, have been a top priority. These efforts built on our work in 2019 with the Graduate Student Council (GSC) to better understand and address acute financial insecurity faced by some doctoral students. This work led to a commitment from each school to implement policies and practices that reduce financial insecurity among specific populations of doctoral students, namely those on nine-month appointments or with nonresident status. 

More recently, we’ve partnered with the schools to try to meet the needs of graduate students who lost summer funding, either through work opportunities or other sources. We have also created three new sources of financial support: short-term emergency funding, doctoral student long-term financial hardship funding, and a need-blind pilot program, the MIT Grant for Graduate Students with Children. The short-term emergency fund situated in OGE has disbursed over $298,000 to help graduate students with the loss of 2020 summer funding opportunities, housing, moving costs, and other basic living expenses, like food and utilities, from the onset of the pandemic. Our process to identify doctoral students in financial hardship has helped 14 students with financial assistance, and the grant for graduate student parents disbursed 72 awards of between $2,000 and $4,000 last fall and is continuing this spring. 

We have also responded to the unique challenges facing our international students. Last summer and fall, MIT reviewed and approved over 800 requests for students to pursue their appointments from outside the U.S. Many of these requests were for students who remained in the U.S at the start of the pandemic, but who wished to return to their home countries to pursue their studies and appointments. MIT also took a leading role in a successful lawsuit challenging a federal government policy that would have impacted many international students’ ability to study in the U.S. if their classes were fully online.

For spring 2021, we had to modify our approach to remote international appointments due to the increasing complexities in U.S. and foreign regulations, the fluid pandemic conditions, and other factors. We have worked very closely with students, departments, and the International Students Office to try to find solutions on a case-by-case basis. Fortunately, we have managed to resolve almost every appointment, enabling students who need to remain remote from the U.S. to do so. Moving forward, we do not anticipate having the same flexibility, but we will continue to monitor the issue closely. 

Last, but certainly not least, we ran a Student Success Coaching Program last spring to help students adjust to the unfamiliar, virtual environment we suddenly found ourselves in. The program matched faculty and staff with students, providing much-needed support and resources for the spring term as we transitioned to our new normal. Fourteen graduate programs opted-in to the initiative and over 1,100 graduate students participated.

Q: Part of the rationale for forming your office in 2017 was to better leverage resources and staff to serve the growing graduate student population. What other progress has been made?

A: Given the decentralized nature of our graduate educational programs, we are always looking for new ways to collaborate across departments, offices, and programs. And we are working to address any gaps that we find. So we’re really pleased about two new staff positions that we believe will go a long way toward better supporting graduate students.

In September, the GradSupport team in the Office of Graduate Education (OGE) hired Gaurav Jashnani, a new assistant dean. Gaurav is a mental health counselor with prior experience in roles at Columbia and the City University of New York, where he focused on student development and well-being.

We also recognize we need to strengthen our support for graduate students with families. So in addition to the previously mentioned MIT Grant for Graduate Students with Children, we are very excited to welcome our new program administrator for graduate student families, Adj Marshall. This position was created in response to a recommendation of the Graduate Family Support Working Group. Adj brings wonderful expertise from her recent work at Tufts University and other educational institutions and nonprofits. She will collaborate closely with Naomi Carton, associate dean of graduate student support in the Residential Education office, to support graduate families both on and off campus. 

Another area we are working on is professional development. Based on national data and our own surveys, we know there is a growing demand for this at MIT. Two ideas that are gaining momentum are an Institute-wide professional development requirement for graduate students, and expanding curricular experiential opportunities.

In addition, this spring Career Advising & Professional Development (CAPD) and OGE will pilot Graduate Mentoring Circles for graduate students of color. Current students will connect with alumni for culturally relevant guidance in academic and industry careers. The program focuses on leadership, upward mobility strategies, and relationship-building. Students interested in participating can email gradmentoringcircles@mit.edu. 

These are a few examples, but the bottom line is that many staff across MIT are actively working on graduate professional development. Also, CAPD is in the process of hiring an associate director of graduate student professional development (a new position), so we look forward to making tangible progress in this area.    

Q: What are some other big ideas under consideration to improve the MIT graduate student experience?

A: One idea that we are excited to roll out this spring is a graduate student online training module on mental health and well-being. It was designed in partnership with the Division of Student Life (DSL), OGE, and MIT Medical and developed by Everfi, which provides the platform for our other online modules like sexual assault prevention. The training addresses essential skills and information to help graduate students manage common emotional stressors and challenges. Although many schools provide such training to undergraduate students, we believe this is the only effort in the U.S. to provide it to graduate students.

Graduate student advising continues to be a huge priority; studies clearly show the correlation between mentoring and graduate students’ personal satisfaction and academic progress. Consequently, we are exploring many different avenues to improve advising.

Last fall, MIT’s Academic Council approved a revision to the tenure process, making excellence in mentoring and advising an explicit criterion in the tenure review process. On the heels of that, we are working to launch an ad hoc committee for a strategic plan on graduate mentoring and advising to create a framework on how to implement best practices more widely.

During spring 2020, the School of Engineering (SOE) ran a successful training pilot for junior faculty on evidence-based mentoring. SOE partnered with OVC, OGE, the Teaching and Learning Laboratory, and MindHandHeart to develop the pilot, which is designed to help research advisors improve their skills for engaging in productive, culturally responsive, research mentoring relationships. The majority of junior faculty found the training helpful, and many reported they planned to implement new tools, like Individual Development Plans, in their research groups.

The pilot is a great example of a program that we believe can be scaled up, as part of a broader Institute-wide initiative to focus on graduate mentoring and advising. Another example is a Graduate Advising Playbook that the same team developed — a framework of best practices in advising and mentoring. The Dean’s Group, graduate officers and administrators, the Committee on Graduate Programs, and many others are actively engaged in conversations about the best way to frame this initiative and move it forward. The GSC has been gathering feedback, as well, through a graduate research advising survey. So, while we have much to do, we believe this could really be a game-changer at MIT.

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Eight from MIT named 2021 Sloan Research Fellows

The Alfred P. Sloan Foundation announced Feb. 16 that it has awarded Sloan Research Fellowships to eight MIT professors in the MIT Media Lab and in the departments of Biology, Brain and Cognitive Sciences, Chemical Engineering, Electrical Engineering and Computer Science, and Mathematics. The fellowships, which honor pre-tenure faculty members, will support their research with two-year, $75,000 awards.

“The Sloan Research Fellowship Program recognizes and rewards outstanding early-career faculty who have the potential to revolutionize their fields of study,” according to the Sloan Foundation.

Fadel Adib, associate professor and Doherty Chair in Ocean Utilization, directs the Signal Kinetics group at the MIT Media Lab. His group invents, builds, and deploys wireless and sensor technologies to address complex problems in society, industry, and ecology. His team’s work focuses on bringing wireless capabilities to extreme domains like the ocean and the human body and to enable new applications that are infeasible using today’s technologies. His research extends beyond communication and networking to enabling novel micro-sensing, powering, and perception tasks. These capabilities aim at helping address major societal challenges in health care, climate change, and automation.

“We are excited about continuing to push our technologies deeper into the oceans and the human body,” says Adib, whose team invented the world’s first net-zero power underwater communication technology and wireless systems that power and communicate with batteryless micro-implants inside the human body. He aims to use this funding to further his team’s efforts in underwater GPS, in-body sensing, and robotic automation. “This Sloan fellowship will allow my team to continue taking risks in pursuing high-impact projects to understand and address global challenges ranging from climate change to health care and automation.”

Joseph "Joey" Davis, the Whitehead Career Development Assistant Professor in Biology, investigates the massive molecular “machines” that carry out important cellular processes, such as protein synthesis and degradation. He uses cryo-electron microscopy (cryoEM) to visualize these molecules at near-atomic resolution as they are being assembled and changing shape while they work. In collaboration with Simons Professor of Mathematics Bonnie Berger, his team has developed a new computational tool. Called cryoDRGN, it leverages neural networks to extract molecular motions from cryoEM data and create 3D movies. The Sloan Foundation award will help Davis combine cryoDRGN with a related imaging technique — electron cryotomography — to observe molecular structures directly inside living cells. Using this powerful combination, he hopes to uncover how machines like the ribosome, which synthesizes proteins, assemble in their native cellular environment. Ultimately, he aims to identify new antibiotic targets in this assembly pathway.

“We hope that the combination of cryoDRGN and electron cryotomography will enable us to directly visualize how key molecular machines are assembled within the cell,” Davis says. “This information will be critical in truly understanding how nature builds these machines so rapidly and efficiently, and will help us understand what aspects of the assembly process fail when cells are mutated and as they age. I am incredibly grateful to the Sloan Foundation for their support of our work.”

Steven Flavell, the Lister Brothers Career Development Assistant Professor in Brain and Cognitive Sciences and The Picower Institute for Learning and Memory, said the Sloan Foundation’s award will help him conduct experiments to uncover how animal nervous systems generate internal states that represent needs and desires, such as hunger, and then produce behaviors, such as roaming around in search of food. His lab plans to use a multidisciplinary experimental approach in their studies, which employ the simple model of the C. elegans worm whose nervous system contains only 302 neurons. Though simple, the model has proven to produce important insights across many areas of biology.

“Over the course of each day, an animal’s nervous system may transition between a wide range of internal states that influence how sensory information is processed and how behaviors are generated,” Flavell says. “These states of arousal, motivation, and mood can persist for hours, play a central role in organizing human behavior, and are commonly disrupted in psychiatric disease. However, the fundamental neural mechanisms that generate these states remain poorly understood. We envision that these studies will ultimately reveal fundamental principles of neural circuit function that may generalize across animals.”

Heather Kulik, associate professor in chemical engineering, advances first-principles and machine learning computational chemistry to accelerate materials and catalyst discovery. Her group has developed the first machine learning models capable of predicting normally time-consuming quantum mechanical properties of transition metal complexes, rapidly uncovering design principles in weeks instead of lifetimes. Her group develops large-scale quantum mechanical modeling methods and applies them to reveal how enzymes work and how to take inspiration from nature to design next-generation catalysts.

“The award from the Sloan Foundation will enable my group to continue advancing computational materials and bio-inspired catalyst discovery,” Kulik says. “The flexible nature of the support ensures we can continue to push forward these interdisciplinary efforts at the boundaries between fields.”

Luquiao Liu, associate professor in the Department of Electrical Engineering and Computer Science, focuses on understanding and exploiting spin-related physics in solid-state material and devices. Most recently, Luqiao has been doing research on developing material and carrying out electrical measurement on charge-spin interactions to achieve electrically induced magnetic switching, and exploring new methods to realize quantum control over the transport of magnons and other quasiparticles, which could be useful in future hybrid quantum systems for information processing. 

“This fellowship will strengthen our capabilities in identifying new material and physics mechanisms that can be used to achieve functions that are unique to spintronic systems, with the long-term goal of realizing efficient computing in the classical and quantum domains,” he says.

Karthish Manthiram, the Theodore T. Miller Career Development Chair and assistant professor in chemical engineering, studies the carbon footprint behind most chemicals and materials that we encounter every day — there is a carbon footprint associated even with the fabric of the clothes we wear, the food we eat, and the disinfectants we spray, he says. To find ways to synthesize these chemicals and materials in a sustainable manner that eliminates the carbon footprint, the Manthiram lab is pioneering the development of a paradigm in which carbon dioxide, dinitrogen, and water can be converted into a wide range of chemicals and materials using renewable electricity. In essence, this would mean that a device that breathes air, drinks water, and takes in solar photons could in principle someday make many of the chemicals that society relies on. The lab specifically looks for ways to facilitate the molecular-level dance through which chemical bonds are broken and formed, so that desired molecules can be made more selectively, efficiently, and at faster rates.

“The support of the Sloan Research Fellowship will allow my group to advance the decarbonization of the material world, through electrically driven synthesis of critical chemicals beginning with just carbon dioxide, dinitrogen, and water,” Manthiram says. “We will pursue new frontiers in synthesizing even more complex molecules starting with these ubiquitous feedstocks.”

Dor Minzer, assistant professor of mathematics, works in the fields of mathematics and theoretical computer science. His interests revolve around computational complexity theory, or — more explicitly — probabilistically checkable proofs, Boolean function analysis, and combinatorics. Minzer’s more recent research has utilized and extended some of the insights gained from the work on probabilistically checkable proofs in order to make progress on several open problems in the field of analysis of Boolean functions, such as the Fourier Entropy conjecture and the stability problem for the edge isoperimetric inequality, as well as to other problems in theoretical computer science.
 
“The Sloan fellowship will allow us to continue pursuing difficult and important challenges in theoretical computer science, whose solution is likely to have wide impact on the field,” Minzer says.

Lisa Piccirillo, assistant professor mathematics, specializes in the study of three- and four-dimensional spaces. She is broadly interested in low-dimensional topology and knot theory, and employs constructive techniques in four-manifolds. Her work in four-manifold topology has surprising applications to the study of mathematical knots. She received an inaugural 2021 Maryam Mirzakhani New Frontiers Prize, created in 2019 by the Breakthrough Foundation to recognize outstanding early-career women in mathematics, for “resolving the classic problem that the Conway knot is not smoothly sliced.” For all other small knots, “sliceness” is readily determined, but this particular knot had remained a mystery since John Conway presented it in the mid-1900s. After hearing about the problem at a conference, Piccirillo took only a week to formulate a proof.

In all, the Sloan Foundation awarded fellowships to 128 tenure-track, but not-yet-tenured, scholars in the United States and Canada this year.

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Metabolic mutations help bacteria resist drug treatment

Bacteria have many ways to evade the antibiotics that we use against them. Each year, at least 2.8 million people in the United States develop an antibiotic-resistant infection, and more than 35,000 people die from such infections, according to the U.S. Centers for Disease Control.

Most of the mutations known to confer resistance occur in the genes targeted by a particular antibiotic. Other resistance mutations allow bacteria to break down antibiotics or pump them out through their cell membranes.

MIT researchers have now identified another class of mutations that helps bacteria develop resistance. In a study of E. coli, they discovered that mutations to genes involved in metabolism can also help bacteria to evade the toxic effects of several different antibiotics. The findings shed light on a fundamental facet of how antibiotics work, and suggest potential new avenues for developing drugs that could enhance the effectiveness of existing antibiotics, the researchers say.

“This study gives us insights into how we can boost the effectiveness of existing antibiotics because it emphasizes that downstream metabolism plays an important role. Specifically, our work indicates that the killing efficacy of an antibiotic can be enhanced if one can elevate the metabolic response of the treated pathogen,” says James Collins, the Termeer Professor of Medical Engineering and Science in MIT’s Institute for Medical Engineering and Science (IMES) and Department of Biological Engineering.

Collins is the senior author of the study, which appears today in Science. The paper’s lead author is Allison Lopatkin, a former MIT postdoc who is now an assistant professor of computational biology at Barnard College at Columbia University.

Metabolic control

The new study builds on previous work from Collins’ lab showing that when treated with antibiotics, many bacteria are forced to ramp up their metabolism, leading to an accumulation of toxic byproducts. These byproducts damage the cells and contribute to their death.

However, despite the role of overactive metabolism in cell death, scientists had not found any evidence that this metabolic pressure leads to mutations that help bacteria evade the drugs. Collins and Lopatkin set out to see if they could find such mutations.

First, they performed a study similar to those normally used to look for antibiotic resistance mutations. In this type of screen, known as adaptive evolution, researchers begin with a laboratory strain of E. coli and then treat the cells with gradually increasing doses of a particular antibiotic. Researchers then sequence the cells’ genomes to see what kinds of mutations arose during the course of the treatment. This approach has not previously yielded mutations to genes involved in metabolism, because of limitations in the number of genes that could be sequenced.

“Many of the studies before now have looked at a few individual evolved clones, or they sequence maybe a couple of the genes where we expect to see mutations because they’re related to how the drug acts,” Lopatkin says. “That gives us a very accurate picture of those resistance genes, but it limits our view of anything else that's there.”

For example, the antibiotic ciprofloxacin targets DNA gyrase, an enzyme involved in DNA replication, and forces the enzyme to damage cells’ DNA. When treated with ciprofloxacin, cells often develop mutations in the gene for DNA gyrase that allow them to evade this mechanism.

In their first adaptive evolution screen, the MIT team analyzed more E. coli cells and many more genes than had been studied before. This allowed them to identify mutations in 24 metabolic genes, including genes related to amino acid metabolism and the carbon cycle — the set of chemical reactions that allows cells to extract energy from sugar, releasing carbon dioxide as a byproduct.

To tease out even more metabolism-related mutations, the researchers ran a second screen in which they forced the cells into a heightened metabolic state. In these studies, E. coli were treated with a high concentration of an antibiotic every day, at incrementally increasing temperatures. The temperature changes gradually drove the cells into a very active metabolic state, and at the same time, they also gradually evolved resistance to the drug.

The researchers then sequenced the genomes of those bacteria and found some of the same metabolism-related mutations they saw in the first screen, plus additional mutations to metabolism genes. These included genes involved in synthesis of amino acids, especially glutamate, in addition to the carbon cycle genes. They then compared their results to a library of genomes of resistant bacteria isolated from patients, and found many of the same mutations.

New targets

The researchers then engineered some of these mutations into typical E. coli strains and found that their rates of cellular respiration were significantly reduced. When they treated these cells with antibiotics, much larger doses were required to kill the bacteria. This suggests that by turning down their metabolism after drug treatment, bacteria can prevent the buildup of harmful byproducts.

The findings raise the possibility that forcing bacteria into a heightened metabolic state could increase the effectiveness of existing antibiotics, the researchers say. They now plan to further investigate how these metabolic mutations help bacteria evade antibiotics, in hopes of discovering more specific targets for new adjuvant drugs.

“I think these results are really exciting because it unleashes gene targets that could improve antibiotic efficacy, that are not being currently investigated,” Lopatkin says. “New resistance mechanisms are really exciting because they give many new avenues of research to follow up on and to see to what extent is this going to improve the efficacy for treating clinical strains.”

The research was funded by the Defense Threat Reduction Agency, the National Institutes of Health, the National Science Foundation Graduate Research Fellowship Program, the Broad Institute of MIT and Harvard, and a gift from Anita and Josh Bekenstein.

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Institute Professor Emeritus Isadore Singer, renowned mathematician who united math and physics, dies at 96

Institute Professor Emeritus Isadore M. Singer, an enormously influential figure in 20th-century science whose work united mathematics and physics, died on Feb. 11. He was 96.

In a career that spanned more than 50 years, Singer not only profoundly affected the development of mathematics, but discovered connections between math and physics that led to the creation of a new field, index theory. Singer was the recipient of numerous awards and honors for his pioneering work, including the National Medal of Science and the Abel Prize, often considered the Nobel Prize of mathematics.

Among his greatest achievements, Singer and Richard Kadison formulated the Kadison-Singer Conjecture in 1959 as part of their work on formalizing the foundations of English physicist Paul Dirac’s quantum mechanics. It was later found to be equivalent to key problems in applied mathematics, engineering, and theoretical computer science and was proved only in 2013, more than half a century years after it was initially posed.

In 1963, Singer and Michael Atiyah hit upon an even more profound connection with the Atiyah-Singer Index Theorem. This theorem deeply and irrecoverably tied together the mathematical fields of analysis, geometry, topology. A key part of their work was Singer’s rediscovery and generalization of the Dirac operator, fundamental to the understanding of the quantum theory of the electron. The newly generalized Dirac operator unlocked deep mysteries in mathematics, setting mathematics and physics on a collision course that continues to play out to this day.

Since first arriving at MIT in 1950, Singer always credited the Institute for giving him the freedom to pursue that interdisciplinary research. For years, his well-known weekly physics-mathematics seminar served as a hotbed for new ideas, inspiring new collaborations between mathematicians and physicists.

His success was all the more remarkable because of his humble beginnings. Born May 3, 1924, to Polish immigrants, Singer grew up in Detroit during the Great Depression in a household where money was tight. His father was a printer and his mother was a seamstress; his younger brother, Sidney Singer, would later become a particle physicist at the Los Alamos National Laboratory.

Singer attended the University of Michigan on a scholarship, where he worked in Professor Harrison Randall’s spectroscopy lab. He often recalled how he sold the weekly football tickets that Michigan students were given to pay for his food. After graduation, he served as a Signal Corps lieutenant in the Philippines, before attending graduate school.

Singer’s drive for understanding physics through mathematics was already formed by this time. “My inclination toward intellectual pursuits was encouraged by my English and chemistry teachers in Central High School, Detroit. I majored in physics at the University of Michigan (1941-1944) but regret not availing myself of their marvelous mathematics department,” Singer said in a lecture at the Smithsonian in 1979. “Puzzled by both relativity and quantum mechanics, I tried to master both these subjects while serving in the U.S. Army. Having failed, I concluded I needed a year of mathematics before I returned to physics, and I became a graduate student at the University of Chicago in 1947. That [one] year stretched to a [lifetime].”

Singer graduated from the University of Chicago with both a master’s (1948) and doctorate (1950) in mathematics, studying under Irving Segal. He later attributed his strong background in analysis to Segal’s instruction. During Singer’s final graduate year, mathematician Shiing-Shen Chern arrived from Europe to introduce American scholars to the latest advances in geometry. Singer took notes from Chern’s class that were to prove critical to developing his research program in differential geometry at MIT.

Singer arrived at MIT in 1950 as a CLE Moore Instructor working with Warren Ambrose and influenced by George Whitehead. Often, when they were working late on geometry as revolutionized by Chern, he and Ambrose would head over to Jack and Marion’s, then a popular deli on Harvard Street in Brookline, Massachusetts, to order rounds of corned beef sandwiches and coffee, and keep working until the early hours of the morning.

“What with interpreting my notes [from Chern’s University of Chicago lectures], reading Chern’s papers and Ambrose insisting on absolute clarity in every detail, we learned differential geometry together,” he said in a tribute to Ambrose. Equally important, “Ambrose taught me jazz.”

Between 1952 and 1956, Singer took appointments at UCLA, the Institute for Advanced Study, and Columbia University. He made deep contributions to analysis and geometry during this period.

In 1963 Singer’s career took a decisive turn during a sabbatical at Oxford University at the invitation of Michael Atiyah. Within the first day, Atiyah challenged Singer to look further into a well-established theorem in topology.

“What Michael had in mind are what are now known as integrality theorems, explaining why certain integrals are integers,” Singer later stated. Atiyah’s query was compelling to Singer, who couldn’t stop thinking about it. In six or so weeks, he approached Atiyah with an answer.

“Surprisingly, it involved analysis and the generalization of the Dirac operator to Riemannian spin manifolds,” Singer said. “I explained to Michael what I thought was going on and how most of the known integrality theorems fit together using the Dirac operator. It was not hard to conjecture the index formula; we obtained the proof of the index theorem in September.”

The major implications of their theorem would become clear only years later. Looking back, Singer would recall: “In 1962, while a Sloan Fellow ... Michael Atiyah and I discovered an index theorem that combined topology, geometry, and elliptical partial differential operators in a new way. Our results extended, unified, and gave insights to some older theories. Exploring the consequences of this startling combination of different fields has kept us busy since then. Deep applications continue to be discovered. Some of the most interesting ... are in high-energy theoretical physics. Mathematicians and physicists now realize the underlying gauge theories is the mathematical structure of fiber bundles. As a result, global geometry has applications to elementary particle physics, and at the same time, physicists are asking many new geometric questions. It is exciting to search for the answers.”

After the work on the index theorem, Singer’s career moved closer to the theoretical high-energy physics community, making numerous contributions there including to gauge theory, the theory of quarks, and anomaly cancellation.

His work garnered a tremendous number of distinctions. Singer was a Sloan Research Fellow from 1959 to 1962, and twice received a John D. Guggenheim fellowship in 1968 and 1975. In 1969 he received the Bôcher Memorial Prize from the American Mathematical Society. In 1985 he was awarded the National Medal of Science. The following year, Singer was selected for MIT’s highest faculty appointment as Institute Professor. In 1988 he received the Eugene Wigner Medal. In 1993, he was honored with the Distinguished Public Service Award, and in 2000 the Leroy P. Steele Prize for Lifetime Achievement, both by the American Mathematical Society. In 2004, Singer, jointly with Sir Michael Atiyah, received the Abel Prize from the Norwegian Academy of Science and Letters, and he was selected for the 2005 MIT James Rhyne Killian Faculty Achievement Award.

Singer was a fellow of the American Academy of Arts and Sciences (1959) and the American Mathematical Society (2012); a member of the American Philosophical Society (1985) and the National Academy of Sciences (1968); honorary member of the London Mathematical Society (2004); and foreign member of the Norwegian Academy of Science and Letters (2009).

Singer’s service to the mathematical and broader scientific community was also prodigious. He chaired the Committee of Science and Public Policy of the National Academy of Sciences from 1973 to 1979. He co-founded The Mathematical Sciences Research Institute (MSRI) in 1982 with Shiing-Shen Chern and Calvin Moore. From 1982 to 1988, Singer served on the White House Science Council. He was a member of the President’s Committee for selection of the National Medal of Science, ending in 1989. Between 1995 and 1999, he was on the governing board of the National Research Council.

Singer was equally committed to teaching. Singer advised many graduate student advisees — 31 from MIT and 2 from the University of California at Berkeley — and had nearly 200 mathematical descendants. Among these students were Dan Burns, Dan Freed, Dan Friedan, John Lott, Hugo Rossi, Linda Rothschild, and Nancy Stanton. He was a mentor to computer scientist Lenore Blum, helping her get into graduate school in 1963. Singer also influenced the budding young MIT student James Simons, who after a distinguished but short career in mathematics went on to found a hugely successful hedge fund.

Even late into his career, Singer insisted on teaching undergraduates, volunteering to work for several semesters as a teaching assistant for the introductory calculus course for first-year students at MIT. He liked to say that empathy made him a good teacher.

Singer is survived by his wife, Rosemarie Singer; four children, Eliot, Natasha, Emily, and Annabelle; two stepchildren, Giles and Melissa; and four grandchildren.

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Less-wasteful laser-cutting

Laser-cutting is an essential part of many industries, from car manufacturing to construction. However, the process isn’t always easy or efficient: Cutting huge sheets of metal requires time and expertise, and even the most careful users can still produce huge amounts of leftover material that go to waste. The underlying technologies that use lasers to cut edges aren’t actually all that cutting-edge: their users are often in the dark about how much of each material they’ve used, or if a design they have in mind can even be fabricated.

With this in mind, researchers from MIT’s Computer Science and Artificial Intelligence Lab (CSAIL) have created a new tool called Fabricaide that provides live feedback on how different parts of the design should be placed onto their sheets — and can even analyze exactly how much material is used. 

“By giving feedback on the feasibility of a design as it’s being created, Fabricaide allows users to better plan their designs in the context of available materials,” says PhD student Ticha Sethapakdi, who led the development of the system alongside MIT Professor Stefanie Mueller, undergraduate Adrian Reginald Chua Sy, and Carnegie Mellon University PhD student Daniel Anderson.

Fabricaide has a workflow that the team says significantly shortens the feedback loop between design and fabrication. The tool keeps an archive of what the user has done, tracking how much of each material they have left. It also allows the user to assign multiple materials to different parts of the design to be cut, which simplifies the process so that it’s less of a headache for multi-material designs. 

Another important element of Fabricaide is a custom 2D packing algorithm that can arrange parts onto sheets in an optimally efficient way, in real time. The team showed that their algorithm was faster than existing open-source tools, while producing comparable quality. (The algorithm can also be turned off, if the user already knows how they want to arrange the materials.)

“A lot of these materials are very scarce resources, and so a problem that often comes up is that a designer doesn’t realize that they’ve run out of a material until after they’ve already cut the design,” says Sethapakdi. “With Fabricaide, they’d be able to know earlier so that they can proactively determine how to best allocate materials.”

As the user creates their design, the tool optimizes the placement of parts onto existing sheets and provides warnings if there is insufficient material, with suggestions for material substitutes (for example, using 1 millimeter-thick yellow acrylic instead of 1 mm red acrylic). Fabricaide acts as an interface that integrates with existing design tools, and is compatible with both 2D and 3D CAD software like AutoCAD, SolidWorks, and even Adobe Illustrator.

In the future the team hopes to incorporate more sophisticated properties of materials, like how strong or flexible they need to be. The team says that they could envision Fabricaide being used in shared makerspaces as a way to reduce waste. A user might see that, say, 10 people are trying to use a particular material, and can then switch to a different material for their design in order to conserve resources.

The project was supported, in part, by the National Science Foundation.

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Toward a disease-sniffing device that rivals a dog’s nose

Numerous studies have shown that trained dogs can detect many kinds of disease —  including lung, breast, ovarian, bladder, and prostate cancers, and possibly Covid-19 — simply through smell. In some cases, involving prostate cancer for example, the dogs had a 99 percent success rate in detecting the disease by sniffing patients’ urine samples.

But it takes time to train such dogs, and their availability and time is limited. Scientists have been hunting for ways of automating the amazing olfactory capabilities of the canine nose and brain, in a compact device. Now, a team of researchers at MIT and other institutions has come up with a system that can detect the chemical and microbial content of an air sample with even greater sensitivity than a dog’s nose. They coupled this to a machine-learning process that can identify the distinctive characteristics of the disease-bearing samples.

The findings, which the researchers say could someday lead to an automated odor-detection system small enough to be incorporated into a cellphone, are being published today in the journal PLOS One, in a paper by Clare Guest of Medical Detection Dogs in the U.K., Research Scientist Andreas Mershin of MIT, and 18 others at Johns Hopkins University, the Prostate Cancer Foundation, and several other universities and organizations.

 “Dogs, for now 15 years or so, have been shown to be the earliest, most accurate disease detectors for anything that we’ve ever tried,” Mershin says. And their performance in controlled tests has in some cases exceeded that of the best current lab tests, he says. “So far, many different types of cancer have been detected earlier by dogs than any other technology.”

What’s more, the dogs apparently pick up connections that have so far eluded human researchers: When trained to respond to samples from patients with one type of cancer, some dogs have then identified several other types of cancer — even though the similarities between the samples weren’t evident to humans.

These dogs can identify “cancers that don’t have any identical biomolecular signatures in common, nothing in the odorants,” Mershin says. Using powerful analytical tools including gas chromatography mass spectrometry (GCMS) and microbial profiling, “if you analyze the samples from, let’s say, skin cancer and bladder cancer and breast cancer and lung cancer — all things that the dog has been shown to be able to detect — they have nothing in common.” Yet the dog can somehow generalize from one kind of cancer to be able to identify the others.

Mershin and the team over the last few years have developed, and continued to improve on, a miniaturized detector system that incorporates mammalian olfactory receptors stabilized to act as sensors, whose data streams can be handled in real-time by a typical smartphone’s capabilities. He envisions a day when every phone will have a scent detector built in, just as cameras are now ubiquitous in phones. Such detectors, equipped with advanced algorithms developed through machine learning, could potentially pick up early signs of disease far sooner than typical screening regimes, he says — and could even warn of smoke or a gas leak as well.

In the latest tests, the team tested 50 samples of urine from confirmed cases of prostate cancer and controls known to be free of the disease, using both dogs trained and handled by Medical Detection Dogs in the U.K. and the miniaturized detection system. They then applied a machine-learning program to tease out any similarities and differences between the samples that could help the sensor-based system to identify the disease. In testing the same samples, the artificial system was able to match the success rates of the dogs, with both methods scoring more than 70 percent.

The miniaturized detection system, Mershin says, is actually 200 times more sensitive than a dog’s nose in terms of being able to detect and identify tiny traces of different molecules, as confirmed through controlled tests mandated by DARPA. But in terms of interpreting those molecules, “it’s 100 percent dumber.” That’s where the machine learning comes in, to try to find the elusive patterns that dogs can infer from the scent, but humans haven’t been able to grasp from a chemical analysis.

 “The dogs don’t know any chemistry,” Mershin says. “They don’t see a list of molecules appear in their head. When you smell a cup of coffee, you don’t see a list of names and concentrations, you feel an integrated sensation. That sensation of scent character is what the dogs can mine.”

While the physical apparatus for detecting and analyzing the molecules in air has been under development for several years, with much of the focus on reducing its size, until now the analysis was lacking. “We knew that the sensors are already better than what the dogs can do in terms of the limit of detection, but what we haven’t shown before is that we can train an artificial intelligence to mimic the dogs,” he says. “And now we’ve shown that we can do this. We’ve shown that what the dog does can be replicated to a certain extent.”

This achievement, the researchers say, provides a solid framework for further research to develop the technology to a level suitable for clinical use. Mershin hopes to be able to test a far larger set of samples, perhaps 5,000, to pinpoint in greater detail the significant indicators of disease. But such testing doesn’t come cheap: It costs about $1,000 per sample for clinically tested and certified samples of disease-carrying and disease-free urine to be collected, documented, shipped, and analyzed he says.

Reflecting on how he became involved in this research, Mershin recalled a study of bladder cancer detection, in which a dog kept misidentifying one member of the control group as being positive for the disease, even though he had been specifically selected based on hospital tests as being disease free. The patient, who knew about the dog’s test, opted to have further tests, and a few months later was found to have the disease at a very early stage. “Even though it’s just one case, I have to admit that did sway me,” Mershin says.

The team included researchers at MIT, Johns Hopkins University in Maryland, Medical Detection Dogs in Milton Keynes, U.K., the Cambridge Polymer Group, the Prostate Cancer Foundation, the University of Texas at El Paso, Imagination Engines, and Harvard University. The research was supported by the Prostate Cancer Foundation, the National Cancer Institute, and the National Institutes of Health.

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