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The view down Main Street showcases the transformation of Kendall Square. Building E37, a new 29-story graduate residence, is at center.

Inside the MIT Campaign for a Better World

Opening for Innovation

2020 marks the unveiling of two new MIT buildings in Kendall Square

The view down Main Street showcases the transformation of Kendall Square. Building E37, a new 29-story graduate residence, is at center.

Two of Kendall Square’s newest and most prominent buildings will open in 2020, marking the first official building openings in MIT’s Kendall Square Initiative. The structures, E37 and E38, will house the MIT Admissions Office, a more extensive innovation network, and hundreds of MIT graduate students and their families.

Both buildings are centrally located next to the inbound MBTA Red Line station, which draws thousands of commuters each day. Frequently referred to as “the most innovative square mile in America,” Kendall Square is evolving in multiple ways. New retail spaces, including a grocery store that opened in 2019, and housing aim to make the square more livable as a destination beyond work. The opening of E37 and E38 marks a significant milestone for MIT, which has been playing a central role in the area’s development.

E38: MIT Admissions, the MIT Forum, and the Innovation and Entrepreneurship Hub
“Welcoming visitors in the heart of Kendall Square will allow us to display the incredible vibrancy of MIT,” says Stuart Schmill ’86, dean of admissions and student financial services. The modernized MIT Admissions Office in E38 will be central to that effort as the new face of the Institute for more than 40,000 admissions visitors annually. Additionally, E38 will house the new 200-seat MIT Forum, a flexible event space that will serve the admissions office, other groups across MIT, and the broader Cambridge community—providing much needed convening space on the east side of campus. It will also include retail spaces on the first floor that are separate from MIT and open to the public.

Schmill stresses that relocating the admissions office from Massachusetts Avenue to Kendall Square not only strengthens MIT’s visibility but also highlights the critical connection the Institute has with the innovative high-tech enterprises that now flourish within the square. “With our new front door in Kendall Square, visitors will really get a feel for our focus on the future,” he says. “But perhaps most importantly, this new location will allow us to more effectively showcase MIT’s values and community.”

The top-five floors of E38 will house the MIT Innovation and Entrepreneurship Hub (I&E Hub), an anchor for the campus-wide ecosystem that moves ideas to marketplaces. The I&E Hub will create spaces for students, researchers, and staff to gather, train, work, and build prototypes. “With the I&E Hub, we have a great opportunity to push MIT’s innovation programming to the forefront,” says Gene Keselman MBA ’17, executive director of the MIT Innovation Initiative. “We’re also looking forward to hosting new activities that bring students, alumni, and professionals together as well as programs around diversity and inclusion.”

The MIT Innovation Initiative will call the new I&E Hub home, as will cornerstones of the MIT innovation landscape such as the MIT Deshpande Center, MIT Venture Mentoring Services, MIT Sandbox, and the Legatum Center for Development and Entrepreneurship at MIT. MIT Proto Ventures, an ambitious effort launched by the MIT Innovation Initiative in 2019, will make dynamic use of the new space in its mission to bring domain experts to campus, exploring transformational technologies and pursuing business opportunities with members of the community. Three key sustainability-focused groups will also move to the facility: the MIT Environmental Solutions Initiative, the Abdul Latif Jameel Water and Food Systems Lab, and the MIT Office of Sustainability.

Keselman points out that the hub’s location will influence the perception of innovation as a core value of MIT and a catalyst for groundbreaking work. “Many people have an idea that gathering spaces are going virtual, but I think the opposite is true,” he says. “To have a physical place where everything comes together multiplies the strength and potential of everything that happens inside of it. That’s the most exciting thing about the I&E Hub to me: seeing what happens when you put MIT’s innovation programming together.”

E37: Graduate residence and childcare center
With nearly 7,000 graduate students enrolled, MIT has seen an increasing need for housing both individual students and those with families. The fall 2020 semester will mark the first wave of graduate residents in new MIT housing in Kendall Square. The 29-story graduate residence will not only embed graduate students more fully in the Cambridge innovation landscape but place them in close proximity to their MIT labs and classrooms.

“MIT graduate students come from all over the world to conduct their research here, and it is critical that the Institute provide an array of housing options for them,” says Cynthia Barnhart SM ’85, PhD ’88, MIT chancellor. “Building graduate housing in the heart of Kendall Square, where education and industry unite to form one of the most innovative districts in the country, will enhance MIT students’ experience and add to the vitality of the area.”

The new residence for graduate students and their families will have approximately 450 living units, including studios, one-bedroom, and two-bedroom units. The building will also house a new childcare center, providing the MIT community with programs for both toddlers and preschoolers. The center will include a dedicated drop-off area, classrooms, a gross-motor-skills playroom, an art room, and an outdoor play space.

Looking ahead
In the coming years, two more vibrant spaces will open at the same east campus “gateway to MIT”: the MIT Museum and the Kendall Square Open Spaces. While the MIT Museum is still operating in its longtime home at 265 Massachusetts Avenue, it will move in early 2022 to occupy its first purpose-designed facility. The new museum will feature galleries, classrooms, hands-on activity spaces, and public meeting areas—all of which will highlight MIT’s impact for a broad audience. The two-acre Open Spaces will incorporate outdoor seating areas, green space, a stage, and a lawn for film screenings. These open spaces are designed to enhance the streetscape while featuring dynamic programming by MIT that is welcoming to all.

“Every element of the Kendall Square Initiative promises to benefit the MIT community as well as the area’s innovation ecosystem,” says Martin Schmidt SM ’83, PhD ’88, MIT provost and the Ray and Maria Stata Professor of Electrical Engineering and Computer Science. “The opening of E37 and E38 is just the beginning. We are looking forward to a future where Kendall Square engages, educates, and informs, and advances our work to make a better world.” — Joelle Carson

Photos: M. Scott Brauer (left); Len Rubenstein (right)


A Responsible Path to Computing Advances

Ethical and social impacts drive efforts in education, research, policy

Photos: M. Scott Brauer (left); Len Rubenstein (right)

It’s little wonder that David Kaiser and Julie Shah ’04, SM ’06, PhD ’11 feel a sense of urgency in their new positions. “Whether it’s the large-scale collection of seemingly innocent data from individuals, or the use of artificial intelligence to create deep fakes in political disinformation campaigns, our norms, rules, and laws haven’t caught up,” says Kaiser, the Germeshausen Professor of the History of Science, and professor of physics. “We need to address many challenging questions head on, and right away.”

Named associate deans of the MIT Stephen A. Schwarzman College of Computing (SCC) in September, Kaiser and Shah are spearheading an audacious initiative to embed the social and ethical dimensions of computing into the teaching, research, and public engagement tasks of the new college.

“In my work, I have a full appreciation for the opportunities and challenges of integrating these kinds of considerations into computing,” says Shah, associate professor of aeronautics and astronautics, and a roboticist who designs systems in which humans and machines operate side by side. “There are areas where we could and should be doing much better.”

Their initiative, the Social and Ethical Responsibilities of Computing (SERC), evolved during months of meetings with faculty from across the Institute. Catalyzed by these sessions, Shah and Kaiser are developing an approach that draws on the expertise of colleagues from a wide range of fields.

“There is a huge body of knowledge from the social sciences, humanities, and arts to help us frame problems in computing and develop systems for the betterment of mankind, and we need to start tapping into it,” says Shah.

“We need new ideas and insights coming from multiple directions,” says Kaiser. “Getting discussions and collaborations going across different disciplines, and with groups outside the Institute, is both a goal and a measure of our success.”

Fostering ethical thinking

This commitment to cooperation and bridging courses of study is apparent in SERC projects already taking shape in the areas of teaching, research, and public engagement. For instance, collaborations between faculty teaching computing classes and those from fields across the humanities, arts, and social sciences will enable new emphases on global policy implications and social responsibility. The effective integration of such content will not be a trivial add-on.

“At the top of our list of learning objectives is the idea that technology alone can’t solve many problems, and that our tools come with values incorporated in them,” says Shah. “We need to complicate students’ thinking, so as they code, experiment, and build systems, they are cognizant of ethics and impacts.”

One way SERC will accomplish this goal, says Shah, is through courses co-taught by computing faculty and in such subjects as anthropology, philosophy, history, sociology, and management. Another way is by creating a series of short, curated case studies written by experts on such topics as algorithmic bias or automation and the future of work, which could be incorporated into a variety of classes and taught in collaboration with faculty from the humanities, arts, and social sciences.

“We want to make sure that there are substantial, unavoidable moments throughout undergraduate training that equip our students to analyze and make sense of hard problems involving social and ethical responsibility,” says Kaiser. “To do this, they need to get tools and ideas about how different disciplines assess these challenges.” This deliberate effort to spark pedagogical alliances includes the arts, where MIT faculty have much to offer the SCC.

“Amazing scholars here are thinking about what it means to be human and about our interactions with machines,” says Kaiser, and they are already laying the groundwork for partnerships. “The School of Humanities, Arts, and Social Sciences recently approved a new concentration in computing and society that includes courses from nine different departments, including literature.” SERC, say Kaiser and Shah, will build upon resources like these to integrate field-spanning classroom experiences into a coherent mission for the SCC.

New research dimensions

The vision for SERC also includes a robust research arm encompassing computing, allied fields, and areas of study that have not typically been included in collaborative projects.

“We want to spur discussions that should be happening but aren’t,” says Shah. “We plan to bring together an interdisciplinary community on a regular basis to look at the social, ethical, or policy implications of technologies, projects, and current events.”

For example, SERC would provide opportunities for SCC faculty and graduate students to connect with faculty from the other fields of science and engineering as well as humanities, arts, and social sciences who could offer new perspectives on computing-related research problems. And, computing graduate students could engage in a yearlong clinic to tease out the ethical, social, and policy implications of their research—gaining insights they could then include in their dissertations.

“Our goal is to provide structure and opportunity for faculty and graduate students to discover intersections and build relationships with other disciplines,” says Shah. “Then we anticipate that those collaborations will generate new course content that flows back, enriching the MIT curriculum.”

Informal discussions are already sparking such novel content, adds Kaiser, noting that one historian of finance and capitalism is looking forward to incorporating new materials about blockchain and cryptocurrency into his classes, which can be developed in partnership with computing specialists.

Wide impact

In the domain of public engagement, the SERC team hopes to make substantial impacts in both the near- and long-term. One pathway, suggests Kaiser, will be uniting MIT’s “world-class policy experts in computing, data, and society with anthropologists, historians, and philosophers” to produce white papers and proposals that influence government and industry.

But the SERC associate deans are also intrigued by another kind of public engagement. “Many people who are affected by our technologies are not at the table when these tools are being developed,” says Shah. “So we think it’s incredibly important to start building relationships and partnerships with local communities and organizations.”

Kaiser cites a current, non-hypothetical case: Cambridge and Somerville are considering bans on facial recognition software within city limits, as a way of curbing surveillance of citizens and protecting privacy. “All-or-nothing solutions might not be the best way to go,” he says. “Is there a way of getting lots of people in the room from MIT and these communities to discuss contentious issues?”

There’s a precedent for this kind of dialogue. In the 1970s, Kaiser notes, university scientists, Cambridge city officials, and local community members debated the pros and cons of recombinant DNA research. The sometimes fraught discussions yielded a framework of rules and regulations that ultimately laid the groundwork for Kendall Square’s thriving biotechnology industry, an economic driver for Cambridge and beyond.

It’s early days still for SERC, and such public engagement will likely take some time to evolve. But as the two associate deans continue to build their ambitious agenda, they hope the vision they have been articulating will quickly take form on campus. “A big win would be if we generate new collaborations for classrooms, research, and policy, get folks together to talk in new ways, and see new content percolate through the curriculum across a range of departments,” says Kaiser. “That’s a hard thing to do at a university.” Says Shah, “If we can get students and faculty to reflect on the potential ethical, social, and policy implications of new technologies so they develop different habits of mind and action, and then move forward productively with good questions, that would be the ultimate success.”

This graphic illustrates molecules at bottom left going through a neural network model (center). The single compound at the top right represents the product that the model believes will be formed. Illustration: Connor Coley


Computational Tools for Better Chemistry

Connor Coley finds bond between computing, chemistry

This graphic illustrates molecules at bottom left going through a neural network model (center). The single compound at the top right represents the product that the model believes will be formed. Illustration: Connor Coley

Chemistry and computer science may not seem like the most obvious pairing: one conjures the image of a lab-coated and begoggled scientist titrating agents in test tubes and beakers, while the other brings to mind a scientist hunched over a computer, typing code and analyzing vast data sets. And yet, Connor Coley SM ’16, PhD ’19 is building his career at the interface of these fields, developing algorithms and machine-learning systems to streamline the work chemical engineers do in the lab—tools he hopes can accelerate the process of discovering and synthesizing useful molecules.

“I would consider myself very application-driven,” says Coley, who was named to Forbes’s 30 Under 30 health care innovators in 2019. “I want to work on problems where I can improve the way that other people are able to approach their own research.”

While Coley has always enjoyed coding and programming, he considers these interests secondary to his passion for chemical engineering—his undergraduate major and the focus of his master’s degree. It wasn’t until Coley started working on his PhD in chemical engineering, supervised by Klavs Jensen, the Warren K. Lewis Professor of Chemical Engineering, and William Green, the Hoyt C. Hottel Professor of Chemical Engineering, that he thought to combine his interests.

Coley was in the lab, building automated reaction platforms that use algorithms to optimize conditions for existing chemical reactions, when he realized that another part of the process could be made more efficient: designing the reactions themselves.

“Once you’ve figured out what molecular structure you want to make, you still need to come up with a recipe—all the ingredients, all the instructions, all the steps that it will actually take to physically make it,” Coley explains. This process requires chemical engineers to draw on published papers, previous experiments, and general chemistry knowledge. “My interest was trying to use that background information in a more principled way.”

Working with group members, Coley has built an algorithm-based, machine-learning system, trained on millions of previously published reactions, that analyzes this background information and offers chemists options and suggestions for making molecules. “It’s a way to supplement, not replace, the more traditional approaches,” Coley says.

The research has been published in Science, and an open-source version of the system is available through MIT’s Machine Learning for Pharmaceutical Discovery and Synthesis Consortium. This version has been adopted by chemists and chemical engineers in industry and academia, many of whom conduct pharmaceutical research. “A lot of the molecules that we think about are or one day could be drugs,” Coley says.

Now a postdoctoral researcher at the Broad Institute of MIT and Harvard, Coley has temporarily shifted his focus to molecule discovery using a technology called DNA-encoded libraries. In this approach, Coley explains, chemists put millions of DNA-tagged compounds in a tube and simultaneously screen those compounds to see which ones have the greatest affinity for a target—for example, a protein linked to a disease. A selection process then identifies the molecules most inclined to “stick” to the target, measured through DNA amplification and sequencing. Chemists typically look only at measurements related to those top molecules, ignoring the rest.

Coley wants to improve this process by developing computational tools that can sift through the entire collection of measurements and pull out anything that may improve the design of molecules selected for development. “If we have a better understanding of all the different molecular structures that correlate with affinity to our protein, it will be easier for us to tweak the other properties that matter,” Coley says.

Whatever the future brings, Coley knows his next step: in fall 2020 he will become an assistant professor in the Department of Chemical Engineering. “MIT is a very fun ecosystem to be a part of,” a place that recognizes the value of applied research and interdisciplinary collaboration, Coley says.

Ultimately, Coley hopes his work will improve the research process for thousands of scientists—making all of their discoveries and advancements a little bit faster. “That can have a pretty sizeable impact.

Hive Mind Garden. Image: M. Scott Brauer

Wide Angle

Hive Mind

Urban garden

Hive Mind Garden. Image: M. Scott Brauer

In true MIT collaborative spirit, five campus organizations have come together to create a first-of-its-kind space at MIT—an urban garden named the Hive, which is designed to attract the kinds of pollinators that are fundamental to sustainable ecosystems and food systems.

In 2017, members of the MIT Undergraduate Association Committee on Sustainability pursued an opportunity to launch a large-scale project on campus. The committee generated multiple ideas and then polled the undergraduate population, which voted for a collaboratively designed and maintained garden. This idea became a reality this past September, with the additional goals of educating and engaging students in sustainability efforts, providing a community gathering space, and offering a supportive environment for bees, birds, butterflies, and moths.

“We envision the garden functioning as an observational tool to explore important questions about our environment,” says Susy Jones, senior project manager at the MIT Office for Sustainability, who worked closely with the students and supervised the project. “We can ask: How do our plants respond to stress from extreme weather events? When do they flower year over year? Which plants attract the most bees? We look forward to exploring these questions with students, researchers, and community members.”

Collaborators are equally excited to see how the garden will impact the MIT community, from serving as a peaceful reading space to a place to share a meal and chat. In the warm months, they expect the space to be buzzing with activity from students, as well as from birds and insects.

“Our hope is that the Hive will serve as a model for future urban gardens, both on the MIT campus and elsewhere,” says Julie Newman, director of sustainability at MIT. “Ideas from students include integrating water capture, solar energy, and public art into open spaces like this on campus.”

Meanwhile, students who helped build the Hive began designing and building interpretative signs for the garden this winter, hoping to have them ready for spring. “That’s been part of the student learning experience—how do you communicate the value of the garden, tell the story, engage passersby in science and ecology, and activate this outdoor site as a place of learning?” says Jones. By consulting with partners in campus operations and makerspaces on the physical process of building signage, this project takes on yet another cross-disciplinary component, paralleling the diverse natural ecosystem of the garden.

Sinan Aral PhD '07. Image: courtesy of Poptech Institute


How Hype Proliferates

Sinan Aral examines social media’s impact on health, economy, and democracy

Sinan Aral PhD ’07. Image: courtesy of Poptech Institute

It’s been said “a lie can travel halfway around the world while the truth is still putting on its shoes”—a quote that’s been (ironically) falsely attributed to Mark Twain, Winston Churchill, and Jonathan Swift. But none could have foreseen the power of social media to spread disinformation worldwide.

Sinan Aral PhD ’07, the David Austin Professor of Management at the MIT Sloan School of Management, where he holds a joint appointment in the IT and Marketing groups, recently put the adage to the test by examining all the tweets sent in Twitter’s first 10 years. Published in Science with colleagues Soroush Vosoughi ’08, SM ’10, PhD ’15 (now an assistant professor at Dartmouth) and MIT professor of media arts Deb Roy SM ’95, PhD ’99 last year, the study found that false news stories on Twitter spread six times faster than true ones, and reached 100,000 people on average compared to 1,000.

“False stories diffused further, faster, deeper, and more broadly than the truth, in every category of information that we studied,” says Aral. “Sometimes by an order of magnitude.” For two decades, Aral has studied “social contagion” between connected users online. His work will culminate with a new book, The Hype Machine, to be published by Crown this September, on the eve of the 2020 US election. The timing is fitting, given concerns over Russian interference in the last election, as well as the political disinformation trolls continue to propagate. Not all social contagion is bad, however. “This technology has the potential for tremendous promise and tremendous peril,” says Aral. “It depends on how you use it.”

Aral began examining how information spread online in 2001 as a managerial economics PhD student at MIT. He has been leading one of the primary research groups within the MIT Initiative on the Digital Economy (IDE) at MIT Sloan since its inception six years ago, and in July, will become the IDE’s director. He examines how advertisers, governments, and nonprofits harness social media to influence online users. “Social media is really just a behavior change agent,” he says. “If we point it toward problems we want to solve, we can do a lot of good in the world.”

In an ongoing controlled study in South Africa, for example, Aral is examining the efficacy of a program to encourage HIV testing using phone messages from loved ones. In another study, he examined peer influence on exercise using a running app, finding people were more apt to run during inclement weather if they had a friend also running on the app that day.

Determining causation between false news and voting has been trickier. Even though 126 million Americans were exposed to Russian propaganda in 2016, researchers have been unable to tell how that affected the election, in large part due to Facebook and other companies’ refusal to share data on individuals, something Aral calls the transparency paradox. “On one hand, they are facing tremendous pressure to show us how it all works,” he says. “On the other, they are facing tremendous pressure to lock it all down to not violate people’s privacy.”

Techniques do exist, however, to anonymize data and fulfill both needs. In another Science article last year, Aral and Dean Eckles, the KDD Career Development Professor in Communications and Technology at MIT Sloan, argue that it is essential to employ them, both to determine the effects in the last election and to protect the next one. “Voting is a cornerstone of our democracy,” Aral says. “If we are going to harden our democracy against that threat, we have to understand how it works.”

The new Schwarzman College of Computing draws on people and resources across MIT to advance computing and shape its impact on research, education, and the world. Photo Credit: Mr. Cole_Photographer


The Future Is Now

Schwarzman College of Computing inspires bold vision for MIT

The new Schwarzman College of Computing draws on people and resources across MIT to advance computing and shape its impact on research, education, and the world. Photo Credit: Mr. Cole_Photographer

From the earliest days of computer science (CS) and artificial intelligence (AI), MIT has been a global leader in these fields. Now, the MIT Stephen A. Schwarzman College of Computing will take MIT’s next leap into the future, to develop boundary-breaking advances in CS, AI, and computing across disciplines, while rigorously attending to their ethical and societal dimensions. As this bold new endeavor gets under way, MIT faculty members and students describe their vision for how the Schwarzman College will transform interdisciplinary learning, research, and discovery.


Eran Ben-Joseph is a professor of landscape architecture and urban planning in the Department of Urban Studies and Planning . His research and teaching include urban and physical design, standards and regulations, sustainable site planning technologies, urban retrofitting, and public interest technology.

James DiCarlo is the Peter de Florez Professor of Neuroscience, head of the Department of Brain and Cognitive Sciences, an investigator at the McGovern Institute for Brain Research at MIT, and a co-director of MIT’s Quest for Intelligence. His research centers on understanding the neuronal representations and computational mechanisms that underlie visual object recognition in primates.

Eden Medina PhD ’05 is an associate professor in the Program in Science, Technology, and Society in the MIT School of Humanities, Arts, and Social Sciences. Her research explores technology as a means to understanding historical processes. She is particularly interested in the history of science and technology in Latin America and the ways that political projects shape—and are shaped by— technology.

Asu Ozdaglar SM ’98, PhD ’03 is deputy dean of academics for the MIT Schwarzman College of Computing, head of the Department of Electrical Engineering and Computer Science (EECS), and the School of Engineering Distinguished Professor of Engineering. She is affiliated with the Laboratory for Information and Decision Systems and the Operations Research Center. Her research focuses on problems that arise in the analysis and optimization of large-scale dynamic multiagent networked systems, including communication networks, transportation networks, and social and economic networks.

stock photo of computing.

Aman S. Patel ’20 recently completed his undergraduate studies in computer science and molecular biology with a particular interest in machine learning and data science as applied to biology and health care. He is now pursuing a master’s degree at MIT. Patel has been a Landsman Undergraduate Research and Innovation Scholar in MIT’s Advanced Undergraduate Research Opportunities Program. He is also a research intern at the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL).

Georgia Perakis is the William F. Pounds Professor of Management at the MIT Sloan School of Management. As a professor of operations research/statistics and operations management, and co-director of the Operations Research Center, Perakis teaches and conducts research on analytics, optimization, revenue management, supply chains, energy, and health care. Her goal is to help enterprises and individual leaders understand and utilize the power of data.

Daniela Rus is the deputy dean of research for the Schwarzman College, director of CSAIL, and the Andrew and Erna Viterbi Professor of Electrical Engineering and Computer Science. Her research focuses on robotics, mobile computing, and data science.

Harini Suresh ’16, MNG ’17 is a doctoral candidate in computer science in EECS. Her research centers on the societal implications of machine learning, including deep-learning approaches to machine-guided medical decision making. Her goal is to make these automated systems easier to understand and to use responsibly.

Mattie F. Wasiak ’20 is a master’s candidate in computer science with an artificial intelligence concentration. Wasiak, who recently completed an SB in computer science at MIT, is applying machine learning and statistical techniques to challenges such as optimization of patient care in neonatal intensive care units, detection of employer bias in job postings, and improved patient outcomes in treating sepsis and hypertension.

How does the Schwarzman College of Computing leverage existing strengths at MIT and fuel new forms of interdisciplinary learning and collaboration?

stock photo illustrating technology. Image: AdobeSURESH: The college offers new incentives and opportunities to develop the computer science field—and computing applications in many different fields— thoughtfully and responsibly. MIT has a lot of influence, and we can demonstrate that it is both important and possible to commit time, space, and resources to teaching and researching computing in a way that incorporates ethical and societal considerations.

BEN-JOSEPH: The Schwarzman College means we can conduct research that examines the complexities of society’s relationship with new and expanding computational technologies, including issues of access and unintended negative consequences. It is a true collaborative and interdisciplinary hub that brings together unique MIT faculty who focus on the use and evolution of computing in artful and impactful ways, across many fields.

PERAKIS: What excites me about the Schwarzman College is that it will bring together people from across the Institute working in computing as it connects to predictive and prescriptive analytics, which involve extracting information from big data and using that information to create recommendations and predictive models. The new college gives MIT a great opportunity to utilize economies of scale and solidify our leadership in these areas.

WASIAK: I anticipate that the college will give researchers and students at MIT new, concrete opportunities to accelerate research in artificial intelligence and machine learning by drawing together individuals from diverse disciplines, such as health care and computer science.

RUS: Our scholars are laying the theoretical foundations of computing and applying those foundations to big ideas in computing and across disciplines. Some are even starting businesses based on their research.

MEDINA: I hope the college will change how our students approach questions of human-computer interaction. Studying how people use and interact with computer systems is important, but so is thinking about computers as part of a larger set of organizational, governmental, and community relationships. This sociotechnical approach broadens our understanding of how humans and computers interact and the ethical and policy implications of these interactions.

DICARLO: Breakthrough advances often come when people make a concerted effort to take on challenges that were previously deemed “in the future.” This new endeavor requires us to break out of our research silos and collaborate in ways that go well beyond the boundaries of business as usual. That’s really what MIT is all about, and I believe that the Schwarzman College within the MIT ecosystem will nucleate this—and many other—unprecedented, concerted efforts.

How will the Schwarzman College of Computing empower your research—and your field?

stock photo illustrating technology. Image: AdobeRUS: One example is a collaboration we launched between the Schwarzman College and the US Air Force. The goal is to make major advances in AI both to improve Air Force operations and address larger societal needs. There are 15 funded projects that will address a variety of topics, including foundational aspects of machine learning, new systems architectures for machine learning, optimization for scheduling and task allocation, weather prediction, autonomous vehicles training and control, and medical readiness.

DICARLO: My lab’s work in visual object recognition and perception employs a “reverse-engineering” approach, which means that we use engineered neural networks, simulated on computers, as our alternative hypotheses or models for human visual processing. We then select among them using neural and behavioral data to discover even better models. My colleagues and I believe that strengthening our connections to MIT engineering and computing through the new college will allow us to generalize this reverse-engineering approach to other brain systems and other types of computational models, leading to major breakthroughs in human cognition, language, and emotional intelligence as well as in understanding the parallels and differences between human learning and machine learning.

OZDAGLAR: The college has an ambitious and holistic agenda for research in computing and at its intersections with several other disciplines. My group’s research focuses on several aspects of human-computing interactions. For example, we look at how digital platforms may improve economic, financial, and social decisions. Conversely, we consider how human decisions may lead to market failures or strategic manipulation could result in platform malfunctions.

WASIAK: The Schwarzman College promises to advance data science, which is central to the work I do. My research leverages massive amounts of data from Beth Israel Deaconess Medical Center to find potential factors that may be affecting how often preterm infants leave their optimal oxygen saturation range. These insights will help close the loop between the researchers and clinicians.

PERAKIS: The focus of my research is developing predictive and prescriptive computational models and algorithms, with applications that range from retail to the energy sector, as well as how they relate to nonprofit organizations and health care. One of my current collaborations is with Lahey Clinic and is focused on addressing the opioid crisis by predicting overdose and prescribing the right treatment path for patients, in both holistic and personalized ways. The new college should advance work like this, which can have a positive influence on individual outcomes and on health care policy.

PATEL: Much of my work is in the field of computational biology, which entails using computational techniques to solve important biological problems. For example, computational biology has allowed us to make more effective patient diagnoses and gain a clearer picture of our underlying genetic regulatory mechanisms, among a multitude of other applications. Although MIT is already an established leader in the field, I believe the Schwarzman College will enable us to have even greater impact.

MEDINA: As a historian of technology who studies the relationship of computer technologies to processes of political change, I am excited that the college has made the social and ethical responsibilities of computing part of its organizational structure. This commitment is central to teaching, but it also highlights an important and growing area of research and an opportunity to broaden the kinds of questions and methods used in the study of computing.

BEN-JOSEPH: My colleagues and I aim to drive urban science and computer science forward to integrate ethics, justice, public participation, policy, and design with statistics, data science, geospatial analysis visualization, robotics, and machine learning to craft equitable and innovative solutions to tomorrow’s complex urban problems. The result: a new generation of data science, AI, and technology focused on solving the profound challenges posed by urbanization—and one that will be optimized to better serve the public interest.

What big questions do you want to see the college tackle?

stock photo illustrating technology. Image: AdobeMEDINA: The famed MIT mathematician Norbert Wiener remarked that instead of celebrating our technical know-how, we should give greater attention to questions of “know-what,” or what we want—and don’t want—our technologies to do. In an age of deep fakes, ubiquitous data collection, and the weaponization of social media platforms to promote misinformation, intolerance, and violence, it seems we need to be asking more “know-what” questions about technology.

OZDAGLAR: A distinctive feature of the college is its explicit focus on social impacts of computing. This motivates our broader community to investigate how advances in computing and AI will impact the work of the future and other societal priorities.

RUS: The college will expand and deepen the connection between computing and other disciplines. With an approach MIT President L. Rafael Reif calls “creating bilinguals,” our students will be equipped to help us answer some of the major questions facing our field and our world.

Photo: Sarah Bastille


A Fast Track for Machine Learning

Tamara Broderick scaling challenges of Bayesian inference

Photo: Sarah Bastille

Machine-learning systems use data to understand patterns and make predictions. When the system is predicting which photos are of cats, you may not care how certain it is about its results. But if it’s predicting the fastest route to the hospital, the amount of uncertainty becomes critically important.

“Imagine the system tells you ‘Route A takes 9 minutes’ and ‘Route B takes 10 minutes.’ Route A sounds better,” says Tamara Broderick, an associate professor in the Department of Electrical Engineering and Computer Science. “But now it turns out that Route A takes 9 minutes plus-or-minus 5, and Route B takes 10 minutes plus-or-minus 1. If you need a life-saving procedure in 12 minutes, suddenly your decision making really changes.”

A high-school outreach program, MIT’s Women’s Technology Program (WTP), first brought Broderick to campus. “My experience at WTP was formative,” she says. Now Broderick studies how machine-learning systems can be made to quantify the “known unknowns” in their predictions, using a mathematical technique called Bayesian inference. “The idea is to learn not just what we know [from the data], but how well we know it,” she explains.

The catch is that traditional algorithms for “Bayesian machine learning” take a very long time to work on complex data sets like those in biology, physics, or social science. “It’s not just that we’re getting more data points, it’s that we’re asking more questions of those data points,” says Broderick, who is a principal investigator at MIT’s Computer Science and Artificial Intelligence Laboratory and affiliated with MIT’s Institute for Data, Systems, and Society. “If I have gene-expression levels for a thousand genes, that’s a thousand-dimensional [machine-learning] problem. But if I try to look at interactions between just one gene with another, that’s now a million-dimensional problem. The computational and statistical challenges go through the roof.”

These challenges impose a bottleneck on using Bayesian machine learning for many applications where quantifying uncertainty is essential. Some complex data analyses might take an infeasible amount of time to run—months or more. And in so-called “high-dimensional” data sets, such as ones with millions of gene interactions, it can be difficult to find the signal among the noise. “It’s harder to find out what’s really associated with what, when you have that many variables,” Broderick says.

In other words, Bayesian machine learning has a scaling problem. Broderick’s research devises mathematical work-arounds that reduce computational and statistical complexity “so that our methods run fast, but with theoretical guarantees on accuracy.” Her recent work includes techniques with colorful names—“kernel interaction trick,” “infinitesimal jackknife”—that evoke a sense of technical wizardry crossed with down-to-earth pragmatism. Indeed, Broderick says she sees scalable Bayesian machine learning as “a service profession” aimed at amplifying the discovery efforts of her fellow scientists.

One such effort came to Broderick’s attention from an economist colleague studying how microcredit—small, low-interest loans made to entrepreneurs in developing economies—affects household incomes. “She’s interested in finding out whether these small loans actually help people, but it was taking her a really long time to run her experiments with existing Bayesian software,” Broderick says. Broderick’s team has been developing methods for this work that are both accurate and orders of magnitude faster.

In another collaboration, her team is using Bayesian machine learning to quantify the uncertainty in different kinds of genomics experiments, work that opens the door to a wealth of new, interesting science, Broderick says. This will help biologists use the data they already have to make informed decisions on how to allocate their research funds to best support future work. Think of it as the science-focused version of predicting the fastest route to a hospital with the least uncertainty.

“Even when we’re writing a purely theoretical paper, I’d like to think that the theory is very much inspired by problems that arise in people’s applications,” Broderick says. “We’re trying to make science easier for biologists, for chemists, for physicists, so they can focus on their really cool problems and just get the data analysis out of the way.”


Inside the MIT Campaign for a Better World

Economics Department Hailed as “Rare Jewel”

Roger Altman


Roger Altman has a long history of working with top economists, from serving in the US Department of the Treasury to his role as cofounder and chairman of the investment banking advisory firm Evercore. Many of the economists he praises most highly, however, are at MIT.

“The MIT economics department is a rare jewel,” says Altman, who also cofounded and serves on the advisory board of The Hamilton Project, an economic policy initiative at the Brookings Institution. “Most years it’s ranked number one in the country, yet it exists in the middle of a leading science and engineering school. This is an extraordinary accomplishment, and I’m quite interested in contributing to the preservation of that record at MIT.”

To that end, Altman chairs the Department of Economics Visiting Committee, which convenes distinguished scholars, graduates, and members of the MIT Corporation to advise the department. “Roger is an invaluable partner in advancing our mission to lead in both economics research and education,” says Department of Economics head Nancy Rose PhD ’85, the Charles P. Kindleberger Professor of Applied Economics. “He is a great sounding board on many of our most pressing challenges,” she adds, “and rolls up his sleeves to help work on them.” Rose is appreciative of Altman’s enthusiasm for one of the department’s top priorities, need-blind admissions for its doctoral program, and grateful that he made a major gift to support expendable graduate fellowships: “His gift has had an immediate impact on what we’re able to do.”

Altman’s support for MIT extends far beyond one department, however. He made a major gift to MIT’s Task Force on Work of the Future, established in 2017 to study the evolution of jobs in the age of technological advancement, and chairs its advisory board. He gave his first gift to MIT in 2016, endowing a scholarship that has already provided financial support for five undergraduates.

A native of Boston, Altman is pleased to be of service to the Institute. “Growing up, I always admired MIT. I think everyone does,” he says. “Much of MIT’s support comes from non-alumni like me, often because they’re trying to further an area of research that’s personally interesting to them. MIT is the leader in so many areas.”

Altman served as assistant secretary of the treasury during the Carter administration and as deputy secretary of the treasury in the Clinton administration. Today, he is a Life Member of the MIT Corporation, the Institute’s governing body.

“It’s been a richly rewarding experience,” he says of his Corporation service. “In addition to attending Corporation and committee meetings, I try to spend regular time with faculty members. Those interactions represent a very steep learning curve for me! Although I did not concentrate in science as a student, I’ve always had a strong interest in it. My involvement with MIT gives me the opportunity to do many interesting things at once.”

When possible, Altman enjoys spending time with students as well. “MIT students represent an extraordinary collection of talent and motivation,” he remarks. “Every time I’m on the campus, I’m awed by students that I interact with even briefly, and I’ve never been exposed to a more impressive student body anywhere.” Altman hopes that the scholarship fund he created “will bring students to MIT who wouldn’t otherwise be able to attend and also increase the diversity of the Institute. That’s important to me.”

These days, Altman says he is particularly enthusiastic about the work of the Abdul Latif Jameel Poverty Action Lab. Cofounded by 2019 Nobel Prize winners and MIT economists Esther Duflo PhD ’99, the Abdul Latif Jameel Professor of Poverty Alleviation and Development Economics, and Abhijit Banerjee, the Ford Foundation International Professor of Economics, the lab has helped transform antipoverty research and relief efforts. “I have a long-standing, serious interest in public policy as it intersects with economics,” he says. “MIT economics and the Poverty Action Lab represent many exciting opportunities for positive impact on public policy.”


A Microcosm of Research

SuperUROP showcases breadth of computing applications

MIT undergraduates are using computing to tackle critical research questions, delving into fields as diverse as robotics, health care, and transportation through the Advanced Undergraduate Research Opportunities Program (SuperUROP).

A yearlong research experience supported by coursework, SuperUROP is an expanded version of MIT’s Undergraduate Research Opportunities Program. SuperUROP was launched by the Department of Electrical Engineering and Computer Science and quickly expanded across the School of Engineering. Thanks to philanthropic support, it also now brings together projects in the School of Humanities, Arts, and Social Sciences with computer science.

“SuperUROP has evolved into a microcosm that showcases the research taking place around the Institute,” says Ted Equi ’81, SM ’84, former SuperUROP industrial sponsor liaison. Equi, who is now the MIT Leaders for Global Operations director of academics, research, and career engagement, noted that 102 students enrolled in the advanced program this year. Here are project examples from this year’s class.

Space Exploration

Jaeyoung Jung ’21, Texas Instruments Undergraduate Research and Innovation Scholar

Project title: Gallium-Nitride Complementary MOS Microprocessor for High-Temperature Applications

Advisors: Tomás A. Palacios, professor, Department of Electrical Engineering and Computer Science (EECS), with PhD student Nadim Chowdhury
SM ’18

Silicon-based electronics have transformed life on Earth, but they are ill-suited to the demands of space. This project’s goal is to equip computers for a trip to Venus, where surface temperatures can reach 471ºC (880ºF).

Semiconductors made with gallium nitride (GaN) rather than silicon can function at temperatures as high as 1,000ºC. However, GaN circuits typically consume too much power to be used practically in microprocessors. Nadim Chowdhury, working with Tomás A. Palacios, has developed a new transistor that addresses this issue, work that could prove critical in deploying electronics in harsh environments.

An electrical engineering major, Jaeyoung Jung is working with Chowdhury and Palacios on the next step: designing the world’s first energy-efficient GaN microprocessor. “This work will allow for sophisticated computing systems in spacecraft,” says Jung, who uses industry- standard software for semiconductor device analysis and circuit design.

“If everything goes well, we expect Jaeyoung to start fabricating the GaN microprocessor at the new MIT.nano cleanroom facility in early 2020,” says Palacios. The team hopes the microprocessor will be used to control a rover on a future NASA trip to Venus. “The SuperUROP program has allowed us to try a moon shot kind of project—in fact, a Venus-shot—and have an amazing MIT undergraduate student at the center of it.”


Ashay Athalye ’20, Angle Undergraduate Research and Innovation Scholar

Project Title: Sensor Fusion of Visual and Tactile Sensory Data for Object Localization and Robotic Manipulation

Advisors: Alberto Rodriguez, associate professor, Department of Mechanical Engineering (MechE), with MechE PhD student Maria Bauza SM ’18

Like humans, robots need to perceive and understand their environment to manage tasks. Unlike humans, robots still can’t easily and reliably track moving objects. Ashay Athalye’s project combines visual and sensory data to assist a robotic arm in better estimating object location.

Currently, many robots employ deep-learning algorithms such as Deep Object Pose Estimation (DOPE), which uses images to estimate object position. However, DOPE doesn’t consider information about where the object was previously or how it might be moving. Athalye, who is majoring in EECS with minors in mechanical engineering and economics, is endeavoring to incorporate such information by applying probabilistic filtering to the output of such algorithms, a method that has shown promise in preliminary testing.

“His work builds from state-of-the-art techniques based on deep learning to estimate the pose of objects under occlusions and fuse them with classic techniques for filtering that aim at providing smoother and temporally coherent object tracking,” says advisor Alberto Rodriguez. “The particular approach involves adding a probabilistic interpretation to outputs of a deep neural network, which then can be used as measures of confidence to do robust object tracking.”

Next, Athalye plans to apply similar filtering techniques to tactile data drawn from robot sensors. His goal is to effectively combine tactile and visual information to help robots with manipulation tasks.

“This project, which involves inference, machine learning, and control theory, has been a perfect way to apply what I’ve learned in my classes,” Athalye says.


Avital Vainberg ’21, Undergraduate Research and Innovation Scholar

Project Title: Visualizing Spatiotemporal-Activity Travel Patterns

Advisors: Joseph Ferreira Jr. ’67, EE ’70, SM ’70, PhD ’71, professor, Department of Urban Studies and Planning (DUSP) with DUSP PhD student Rounaq Basu MCP ’19, SM ’19

Location-tagged data are widely available but often underutilized by urban planners and policy makers. Avital Vainberg is working to put such data to better use by developing visualizations that are accessible to nontechnical audiences.

Vainberg, who is majoring in urban science and planning with computer science, and minoring in theater arts, is using travel survey data from Singapore to develop an interactive dashboard. “The goal is to inform planners and policy makers of where, when, and why people are traveling in order to encourage better decisions regarding land use, zoning, and transportation infrastructure.”

Advisor Joseph Ferreira Jr. says, “Avital is focusing on a data-processing pipeline that isolates and parallelizes the computing-intensive image generation steps so that the activity patterns of subgroups can be visualized and compared on the fly from an interactive dashboard.”

For example, Vainberg has created an animation that maps the activity patterns of Singapore’s residents, revealing commuting habits and other trends. Her dashboard will enable users to filter the data by such criteria as demographics and time of day.

Ferreira says that these visualizations can reveal patterns that could otherwise be hard to detect, such as activity clusters that might signal a need for additional transportation.

“This project has simultaneously sharpened my coding and data science skills, pushed me to think critically of the world around me, and encouraged me to take on impactful projects,” Vainberg says.

Computer Systems

Amir Farhat ’20, Hewlett Foundation Undergraduate Research and Innovation Scholar

Project Title: Understanding the Fundamentals of Reconfigurable Data Center Networks

Advisor: Manya Ghobadi, TIBCO Career Development Assistant Professor, Department of Electrical Engineering and Computer Science; Computer Science and Artificial Intelligence Laboratory

The explosion of data in every field from health care to business has spurred growing demand for big data analytics. This has led to increased use of big data server farms, where up to a million servers work together to tackle complex computations and run large applications such as web search engines.

A computer science and engineering major, Amir Farhat is endeavoring to make large-scale data centers more efficient by changing the physical topology of a wired data center network to increase its throughput. The goal is to develop a “smart” data center.

“By engineering the network to be reconfigurable to adapt to demand, we hope to increase the application performance in large- scale data centers,” he says.

In traditional data center networks, operators decide in advance how much capacity to provide. Farhat is developing a simulation framework to experiment with alternative data center architectures and scheduling algorithms in the hopes of designing a reconfigurable data center.

“It might seem impossible to change the topology of a network without physically changing the cables,” says advisor Manya Ghobadi. But she says optical networking, which encodes information in light waves, opens the door to new design options. Since optical waves can be redirected using mirrors, they are capable of quick changes: no rewiring required.

“This is a realm where the network is no longer a static entity but a dynamic structure of interconnections that may change depending on the workload,” Ghobadi says, noting that Farhat is helping to lay the groundwork for the future. “This work promises to revolutionize the way networks are designed in practice, defined in textbooks, and taught in classrooms.”

Esther Duflo PhD ’99 and Abhijit Banerjee shared the 2019 Nobel Prize in Economics. Photo: Bryce Vickmark

Breakthroughs and Insights

Why Fight Poverty? Nobelists Explain

Good Economics for Hard Times excerpt

Esther Duflo PhD ’99 and Abhijit Banerjee shared the 2019 Nobel Prize in Economics. Photo: Bryce Vickmark

In October, MIT economists Esther Duflo PhD ’99 and Abhijit Banerjee were named co-winners, with Harvard University economist Michael Kremer, of the 2019 Nobel Prize in Economics for their groundbreaking research on combatting global poverty. The duo co-directs MIT’s Abdul Latif Jameel Poverty Action Lab. Duflo holds the Abdul Latif Jameel Professorship of Poverty Alleviation and Development Economics, and Banerjee is the Ford Foundation International Professor of Economics. Last fall, they released a new book, Good Economics for Hard Times (PublicAffairs, 2019), in which they explain how and why intelligent interventions can reap societal benefits.

[Creating successful policies to fight poverty] is patient work; spending money by itself does not necessarily deliver real education or good health. But the good news is that… [while we do not always know how to foster growth,] we know how to make progress here. One big advantage of focusing on clearly defined interventions is that these policies have measurable objectives and therefore can be directly evaluated. We can experiment with them, abandon the ones that do not work, and improve the ones with potential.

The recent history of malaria is a good example. Malaria is one of the biggest killers of small children and a disease preventable by avoiding mosquito bites. Since the 1980s, the number of malaria deaths had been rising every year. At the peak in 2004 there were 1.8 million deaths from malaria. Then in 2005 there was a dramatic turning point. Between 2005 and 2016, the number of deaths from malaria declined by 75 percent.

Many factors probably contributed to the decrease in the number of malaria deaths, but the widespread distribution of insecticide-treated bed nets almost surely played a key role. Overall, the benefits of nets are well established. In 2004, a review of the evidence from 22 carefully done randomized controlled trials [RCTs] found that, on average, 1,000 more nets distributed contributed to a reduction of 5.5 deaths per year. As we described in Poor Economics [PublicAffairs, 2011], however, there was a big debate at the time on whether nets should be sold to beneficiaries (at a subsidized price) or given for free. But an RCT by Pascaline Dupas and Jessica Cohen, replicated since then by several other studies, established that free nets are in fact used just as much as nets that are paid for, and free distribution achieves a much higher effective coverage than cost sharing.

Since Poor Economics was published in 2011, this evidence eventually convinced the key players that massive distribution was the most effective way to fight malaria. Between 2014 and 2016, a total of 582 million insecticide-treated mosquito nets were delivered globally. Of these, 505 million were delivered in sub-Saharan Africa, and 75 percent were distributed through mass distribution campaigns of free bed nets. The magazine Nature concluded that insecticide-treated net distributions averted 450 million malaria cases between 2000 and 2015.

The accumulation of evidence took some time, but it worked. Even the skeptics were convinced. Bill Easterly, who in 2011 was an outspoken critic of free bed net distribution, gracefully acknowledged in a tweet that his nemesis Jeff Sachs was more right than he was on this particular issue. The right policy choices were made, leading to tremendous progress against a terrible scourge.

The bottom line is that despite the best efforts of generations of economists, the deep mechanisms of persistent economic growth remain elusive. No one knows if growth will pick up again in rich countries, or what to do to make it more likely. The good news is that we do have things to do in the meantime; there is a lot that both poor and rich countries could do to get rid of the most egregious sources of waste in their economies. While these things may not propel countries to permanently faster growth, they could dramatically improve the welfare of their citizens.

Investing in human capital

Moreover, while we do not know when the growth locomotive will start, if and when it does, the poor will be more likely to hop onto that train if they are in decent health, can read and write, and can think beyond their immediate circumstances. It may not be an accident that many of the winners of globalization were ex-communist countries that had invested heavily in the human capital of their populations in the communist years (China, Vietnam) or countries threatened with communism that had pursued similar policies for that reason (Taiwan, South Korea). The best bet, therefore, for a country like India is to attempt to do things that can make the quality of life better for its citizens with the resources it already has: improving education, health, and the functioning of the courts and the banks, and building better infrastructure (better roads and more livable cities, for example).

For the world of policy makers, this perspective suggests that a clear focus on the well-being of the poorest offers the possibility of transforming millions of lives much more profoundly than we could by finding the recipe to increase growth from 2 percent to 2.3 percent in the rich countries…It may even be better for the world if we did not find that recipe.