Professor Emeritus Richard “Dick” Eckaus, who specialized in development economics, dies at 96

Richard “Dick” Eckaus, Ford Foundation International Professor of Economics, emeritus, in the Department of Economics, died on Sept. 11 in Boston. He was 96 years old.

Eckaus was born in Kansas City, Missouri on April 30, 1926, the youngest of three children to parents who had emigrated from Lithuania. His father, Julius Eckaus, was a tailor, and his mother, Bessie (Finkelstein) Eckaus helped run the business. The family struggled to make ends meet financially but academic success offered Eckaus a way forward.

He graduated from Westport High School, joined the United States Navy, and was awarded a college scholarship via the V-12 Navy College Training Program during World War II to study electrical engineering at Iowa State University. After graduating in 1944, Eckaus served on a base in New York State until he was discharged in 1946 as lieutenant junior grade.

He attended Washington University in St. Louis, Missouri, on the GI Bill, graduating in 1948 with a master’s degree in economics, before relocating to Boston and serving as instructor of economics at Babson Institute, and then assistant and associate professor of economics at Brandeis University from 1951 to 1962. He concurrently earned a PhD in economics from MIT in 1954.

The following year, the American Economic Review published “The Factor Proportions Problem in Economic Development,” a paper written by Eckaus that remained part of the macroeconomics canon for decades. He returned to MIT in 1962 and went on to teach development economics to generations of MIT students, serving as head of the department from 1986 to 1990 and continuing to work there for the remainder of his career.

The development economist Paul Rosenstein-Rodan (1902-85), Eckaus’ mentor at MIT, took him to live and work first in Italy in 1954 and then in India in 1961. These stints helping governments abroad solidified Eckaus’ commitment to not only excelling in the field, but also creating opportunities for colleagues and students to contribute as well — occasionally in conjunction with the World Bank.

Longtime colleague Abhijit Banerjee, a Nobel laureate, Ford Foundation International Professor of Economics, and director of the Abdul Latif Jameel Poverty Action Lab at MIT, recalls reading a reprint of Eckaus’ 1955 paper as an undergraduate in India. When he subsequently arrived at MIT as a doctoral candidate, he remembers “trying to tread lightly and not to take up too much space,” around the senior economist. “In fact, he made me feel so welcome,” Banerjee says. “He was both an outstanding scholar and someone who had the modesty and generosity to make younger scholars feel valued and heard.”

The field of development economics provided Eckaus with a broad, powerful platform to work with governments in developing countries — including India, Egypt, Bhutan, Mexico, and Portugal — to set up economic systems. His development planning models helped governments to forecast where their economies were headed and how public policies could be implemented to shift or accelerate the direction.

The Government of Portugal awarded Eckaus the Great-Cross of the Order of Prince Henry the Navigator after he brought teams from MIT to assist the country in its peaceful transition to democracy following the 1974 Carnation Revolution. Initiated at the request of the Portuguese Central Bank, these graduate students became some of the most prominent economists of their generation in America. They include Paul Krugman, Andrew Abel, Jeremy I. Bulow, and Kenneth Rogoff.

His colleague for five decades, Paul Joskow, the Elizabeth and James Killian Professor of Economics at MIT, says that’s no surprise. “He was a real rock of the economics department. He deeply cared about the graduate students and younger faculty. He was a very supportive person.”

Eckaus was also deeply interested in economic aspects of energy and environment, and in 1991 was instrumental in the formation of the MIT Joint Program on the Science and Policy of Global Change, a program that integrates the natural and social sciences in analysis of global climate threat. As Joint Program co-founder Henry Jacoby observes, “Dick provided crucial ideas as to how that kind of interdisciplinary work might be done at MIT. He was already 65 at the time, and continued for three decades to be active in guiding the research and analysis.”

Although Eckaus retired officially in 1996, he continued to attend weekly faculty lunches, conduct research, mentor colleagues, and write papers related to climate change and the energy crisis. He leaves behind a trove of more than 100 published papers and eight authored and co-authored books.

“He was continuously retooling himself and creating new interests. I was impressed by his agility of mind and his willingness to shift to new areas,” says his oldest living friend and peer, Jagdish Bhagwati, Columbia University professor of economics, law, and international relations, emeritus, and director of the Raj Center on Indian Economic Policies. “In their early career, economists usually write short theoretical articles that make large points, and Dick did that with two seminal articles in the leading professional journals of the time, the Quarterly Journal of Economics and the American Economic Review. Then, he shifted his focus to building large computable models. He also diversified by working in an advisory capacity in countries as diverse as Portugal and India. He was a ‘complete’ economist who straddled all styles of economics with distinction.” 

Eckaus is survived by his beloved wife of 32 years Patricia Leahy Meaney of Brookline, Massachusetts. The two traveled the world, hiked the Alps, and collected pre-Columbian and contemporary art. He is lovingly remembered by his daughter Susan Miller; his step-son James Meaney (Bruna); step-daughter Caitlin Meaney Burrows (Lee); and four grandchildren, Chloe Burrows, Finley Burrows, Brandon Meaney, and Maria Sophia Meaney.

In lieu of flowers, please consider a donation in Eckaus’ name to MIT Economics (77 Massachusetts Ave., Building E52-300, Cambridge, MA 02139). A memorial in his honor will be held later this year.

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Making each vote count

Graduate student Jacob Jaffe wants to improve the administration of American elections. To do that, he is posing “questions in political science that we haven’t been asking enough,” he says, “and solving them with methods we haven’t been using enough.”

Considerable research has been devoted to understanding “who votes, and what makes people vote or not vote,” says Jaffe. He is training his attention on questions of a different nature: Does providing practical information to voters about how to cast their ballots change how they will vote? Is it possible to increase the accuracy of vote-counting, on a state-by-state and even precinct-by-precinct basis? How do voters experience polling places? These problems form the core of his dissertation.

Taking advantage of the resources at the MIT Election Data and Science Lab, where he serves as a researcher, Jaffe conducts novel field experiments to gather highly detailed information on local, state, and federal elections, and analyzes this trove with advanced statistical techniques. Whether investigating the probability of miscounts in voting, or the possibility of changing a voter’s mode of voting, Jaffe intends to strengthen the scaffolding that supports representative government. “Elections are both theoretically and normatively important; they’re the basis of our belief in the moral rightness of the state to do the things the state does,” he says.

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For one of his keystone projects, Jaffe seized a unique opportunity to run a big field experiment. In summer 2020, at the height of the Covid-19 pandemic, he emailed 80,000 Floridians instructions on how to vote in an upcoming primary by mail. His email contained a link enabling recipients to fill out two simple questions to receive a ballot. “I wanted to learn if this was an effective method for getting people to vote by mail, and I proved it is, statistically,” he says. “This is important to know because if elections are held in times when we might need people to vote nonlocally or vote using one method over another — if they’re displaced by a hurricane or another emergency, for instance — I learned that we can effect a new vote mode practically and quickly.”

One of Jaffe’s insights from this experiment is that “people do read their voting-related emails, but the content of the email has to be something they can act on proximately,” he says. “A message reminding them to vote two weeks from now is not so helpful.” The lower the burden on an individual to participate in voting, whether due to proximity to a polling site or instructions on how to receive and cast a ballot, the greater the likelihood of that person engaging in the election.

“If we want people to vote by mail, we need to reduce the informational cost so it’s easier for voters to understand how the system works,” he says.

Another significant research thrust for Jaffe involves scrutinizing accuracy in vote counting, using instances of recounts in presidential elections. Ensuring each vote counts, he says, “is one of the most fundamental questions in democracy,” he says.

With access to 20 elections in 2020, Jaffe is comparing original vote totals for each candidate to the recounted, correct tally, on a precinct-level basis. “Using original combinatorial techniques, I can estimate the probability of miscounting ballots,” he says. The ultimate goal is to generate a granular picture of the efficacy of election administration across the country.

“It varies a lot by state, and most states do a good job,” he says. States that take their time in counting perform better. “There’s a phenomenon where some towns race to get results in as quickly as possible, and this affects their accuracy.”

In spite of the bright spots, Jaffe sees chronic underfunding of American elections. “We need to give local administrators the resources, the time and money to fund employees to do their jobs,” he says. The worse the situation is, “the more likely that elections will be called wrong, with no one knowing.” Jaffe believes that his analysis can offer states useful information for improving election administration. “Determining how good a place is historically at counting ballots can help determine the likelihood of needing costly recounts in future elections,” he says.

The ballot box and beyond

It didn’t take Jaffe long to decide on a life dedicated to studying politics. Part of a Boston-area family who, he says, “liked discussing what was going on in the world,” he had his own subscriptions to Time magazine at age 9, and to The Economist in middle school. During high school, he volunteered for then-Massachusetts Representative Barney Frank and Senator John Kerry, working on constituent services. At Rice University, he interned all four years with political scientist Robert M. Stein, an expert on voting and elections. With Stein’s help, Jaffe landed a position the summer before his senior year with the Department of Justice (DOJ), researching voting rights cases.

“The experience was fascinating, and the work felt super important,” says Jaffe. His portfolio involved determining whether legal challenges to particular elections met the statistical standard for racial gerrymandering. “I had to answer hard quantitative questions about the relationship between race and voting in an area, and whether minority candidates were systematically prevented from winning,” he says.

But while Jaffe cared a lot about this work, he didn’t feel adequately challenged. “As a 21-year-old at DOJ, I learned that I could address problems in the world using statistics,” he says. “But I felt I could have a greater impact addressing tougher questions outside of voting rights.”

Jaffe was drawn to political science at MIT, and specifically to the research of Charles Stewart III, the Kenan Sahin Distinguished Professor of Political Science, director of the MIT Election Lab, and head of Jaffe’s thesis committee. It wasn’t just the opportunity to plumb the lab’s singular repository of voting data that attracted Jaffe, but its commitment to making every vote count. For Jaffe, this was a call to arms to investigate the many, and sometimes quotidian, obstacles, between citizens and ballot boxes.

To this end, he has been analyzing, with the help of mathematical methods from queuing theory, why some elections involve wait lines of six hours and longer at polling sites. “We know that simpler ballots mean people move don’t get stuck in these lines, where they might potentially give up before voting,” he says. “Looking at the content of ballots and the interval between voter check-in and check-out, I learned that adding races, rather than candidates, to a ballot, means that people take more time completing ballots, leading to interminable lines.”

A key takeaway from his ensemble of studies is that “while it’s relatively rare that elections are bad, we shouldn’t think that we’re good to go,” he says. “Instead, we need to be asking under what conditions do things get bad, and how can we make them better.”

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“Whoever you are, this is your place.” Reimagined MIT Museum encourages visitors to join MIT’s community

The atmosphere of discovery generated by MIT’s research and innovation activities has been described as magic by many. But that magic can sometimes seem obscure or even intimidating to outsiders.

Now the MIT Museum, which opens to the public on Oct. 2, is inviting everyone to take part in MIT’s magic with a new 56,000-square-foot space in the heart of Cambridge’s Kendall Square. The reimagined museum invites visitors to explore the Institute’s innovations in science, technology, engineering, arts, and math (STEAM) — and to take part in that work with hands-on learning labs and maker spaces, interactive exhibits, and venues to discuss the impact of science and technology on society.

“We’re taking MIT’s great mission and making it more accessible to the wider community,” MIT Museum Director John Durant says. “What MIT does and stands for is too important to be held within the community of researchers, students, and staff. If MIT is world-changing, then its work needs to be out there in the wider community, and the wider community needs to be able to access and understand it, and to ask questions about how we’re going to apply all this new knowledge and innovation to make the world a better place. The museum is all about turning MIT inside out.”

“The opening of the new MIT Museum is a cause for celebration,” says L. Rafael Reif, MIT’s president. “We are excited to welcome the world in to this brilliantly reimagined space. Museum visitors will get a real sense of the Institute’s spirit of curiosity, boldness, and ingenuity, and will find countless ways to explore and engage with MIT’s remarkable contributions to human progress.”

Praising the efforts of Museum staff and leaders, he adds, “Despite enormous challenges, they came together to build the MIT Museum a beautiful new home.”

The museum’s opening exhibits address big questions in areas like the potential and risks of artificial intelligence — including a deepfake video of President Nixon giving a speech about the failed moon landing — and the moral challenges brought by advances in genetic engineering.

The space also shows art and artefacts from the museum’s collection of over 1 million objects, many for the first time, from Rainer Weiss’s Laser Interferometer Gravitational-wave Observatory (LIGO) prototype to recordings from community members about the Black experience at MIT.

All of the museum’s sections are designed to be surprising and welcoming, but also to provoke conversations about how unfolding innovations should shape the world. To encourage diverse perspectives in those conversations, the museum has taken a number of steps to welcome the public, including offering free general admission to Cambridge residents, promoting free spaces in the museum, hosting open workshops, and more.

“Access is a central piece of this whole endeavor, and it’s a value we’re underscoring to support changing views of who is a scientist, who is an engineer, who gets to know about these issues, and who cares,” MIT Museum Director of Collections Deborah Douglas explains. “These are big questions in our society, and I think we can be a place that feels open and welcome, but also a place for hard and interesting conversations to happen.”

An inspired design

Nestled among the Kendall Square T stop and MIT’s new welcome center, the museum’s glass-walled lobby was purpose-built to dissolve the boundaries between Kendall Square and MIT’s campus.

An amphitheater dubbed The Exchange beckons visitors with a massive media wall made to facilitate presentations, discussions, debates, and anything else community members decide to do with it.

“One big theme of the new museum is conversation,” Durant says. “We see the museum serving as a kind of forum or meeting ground for different groups. It’s a place where MIT researchers, staff, and students can meet with entrepreneurs, civic leaders, members of the general public — anybody who has a stake in the future of research and innovation.”

Broad, open staircases take visitors through a journey of galleries that begins on the first floor with a welcome message, leads to second floor research stories from MIT and exhibits addressing technology topics of global importance, and finishes on the third floor with displays from the museum’s collection.

Displayed in the freely accessible lobby is an art piece from the Media Lab’s Poetic Justice Group that celebrates the diverse spoken and sign languages of visitors through a count from 1 to 100, with each number displayed in a different language.

“We’re trying to say, whoever you are, this is your place,” Durant says of the exhibit. “As MIT often says to its incoming students, ‘You belong!’”

The second- and third-floor galleries feature interactive displays that let users manipulate the genomes of virtual mice and work with neural nets that learn how to recognize facial expressions.

“So much of innovation and science research is still about culture, so we tried to balance that and use the museum to display the conversations happening at the intersection of science and culture right now,” Durant says.

On the top floor, objects from the MIT Museum’s collections are arranged by topic areas including computer programming, the role of play and curiosity in discovery, photography, and even a virtual time capsule exploring the community that came together to recreate MIT online during the pandemic.

All of the displays in the collections gallery are designed to change on a regular basis, reflecting the organizing committee’s decision to mold the space around community preferences.

“We hope visitors will see the gallery as a tool as much as a treasure house,” Douglas explains. “We have all these cool things in our collections, and so many different stories we could tell,  but we want our visitors to feel empowered to come in and tell entirely different stories than the ones the curators have suggested,” Douglas explains. “We’re like a supermarket that doesn’t tell you what to do with the flour, sugar, and butter.”

Each floor also features spaces that allow visitors to take part in MIT’s research, from its Maker Hub to wet labs and other workshop spaces that will offer daily, drop-in activities. In fact, the new museum has roughly three times more space for face-to-face, hands-on activities than the old museum.

“We aspire to be so much more than a series of exhibition spaces,” says Ann Neuman, director of MIT Museum’s galleries and exhibitions. “In the spirit of MIT’s ‘mind and hand’ experimental sensibilities, we’re a venue for the broader community to participate in science, examine emerging technologies, and engage with ideas that are shaping our world in every way.”

The highly anticipated opening will be celebrated in conjunction with a redesigned Cambridge Science Festival, which is based out of the museum but will extend far beyond its doors, from Oct. 3-9.

“We’re in an ideal location as a gateway between the technology district Kendall Square and MIT,” Durant says. “Our mission is to be an interface institution, so it suits us perfectly to have one foot firmly in MIT and one foot in the wider community.”

A chance to learn

The planning team for the new museum had to overcome challenges related to the Covid-19 pandemic, which not only made the vast majority of their meetings virtual but also forced them to close the doors of the old museum even before they started moving things over to the new location.

With the grand opening, organizers will finally get the chance to get real-time feedback from the community.

“We’re going to learn so much as soon as the doors are open,” Durant says. “I want to see our programs grow and strengthen, our outreach efforts grow and strengthen. From day one we have to be learning and adapting.”

Indeed, the idea of the museum as a living, evolving space was echoed by other members of the museum’s leadership, who described Oct. 2 as the beginning of something rather than an ending.

“My colleagues like to say the museum is a hypothesis, not a well-established theory just yet,” Douglas says. “Science and technology can be intimidating, and our goal is to get people to realize that these are some of the most exciting ways in which human creativity and ingenuity express themselves. It’s improved lives. It’s made this nation and many others great. There have been negative consequences from technology, but it also provides one of our best hopes for the future, and we want everyone to feel a part of that.”

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Processing waste biomass to reduce airborne emissions

To prepare fields for planting, farmers the world over often burn corn stalks, rice husks, hay, straw, and other waste left behind from the previous harvest. In many places, the practice creates huge seasonal clouds of smog, contributing to air pollution that kills 7 million people globally a year, according to the World Health Organization.

Annually, $120 billion worth of crop and forest residues are burned in the open worldwide — a major waste of resources in an energy-starved world, says Kevin Kung SM ’13, PhD ’17. Kung is working to transform this waste biomass into marketable products — and capitalize on a billion-dollar global market — through his MIT spinoff company, Takachar.

Founded in 2015, Takachar develops small-scale, low-cost, portable equipment to convert waste biomass into solid fuel using a variety of thermochemical treatments, including one known as oxygen-lean torrefaction. The technology emerged from Kung’s PhD project in the lab of Ahmed Ghoniem, the Ronald C. Crane (1972) Professor of Mechanical Engineering at MIT.

Biomass fuels, including wood, peat, and animal dung, are a major source of carbon emissions — but billions of people rely on such fuels for cooking, heating, and other household needs. “Currently, burning biomass generates 10 percent of the primary energy used worldwide, and the process is used largely in rural, energy-poor communities. We’re not going to change that overnight. There are places with no other sources of energy,” Ghoniem says.

What Takachar’s technology provides is a way to use biomass more cleanly and efficiently by concentrating the fuel and eliminating contaminants such as moisture and dirt, thus creating a “clean-burning” fuel — one that generates less smoke. “In rural communities where biomass is used extensively as a primary energy source, torrefaction will address air pollution head-on,” Ghoniem says.

Thermochemical treatment densifies biomass at elevated temperatures, converting plant materials that are typically loose, wet, and bulky into compact charcoal. Centralized processing plants exist, but collection and transportation present major barriers to utilization, Kung says. Takachar’s solution moves processing into the field: To date, Takachar has worked with about 5,500 farmers to process 9,000 metric tons of crops.

Takachar estimates its technology has the potential to reduce carbon dioxide equivalent emissions by gigatons per year at scale. (“Carbon dioxide equivalent” is a measure used to gauge global warming potential.) In recognition, in 2021 Takachar won the first-ever Earthshot Prize in the clean air category, a £1 million prize funded by Prince William and Princess Kate’s Royal Foundation.

Roots in Kenya

As Kung tells the story, Takachar emerged from a class project that took him to Kenya — which explains the company’s name, a combination of takataka, which mean “trash” in Swahili, and char, for the charcoal end product.

It was 2011, and Kung was at MIT as a biological engineering grad student focused on cancer research. But “MIT gives students big latitude for exploration, and I took courses outside my department,” he says. In spring 2011, he signed up for a class known as 15.966 (Global Health Delivery Lab) in the MIT Sloan School of Management. The class brought Kung to Kenya to work with a nongovernmental organization in Nairobi’s Kibera, the largest urban slum in Africa.

“We interviewed slum households for their views on health, and that’s when I noticed the charcoal problem,” Kung says. The problem, as Kung describes it, was that charcoal was everywhere in Kibera — piled up outside, traded by the road, and used as the primary fuel, even indoors. Its creation contributed to deforestation, and its smoke presented a serious health hazard.

Eager to address this challenge, Kung secured fellowship support from the MIT International Development Initiative and the Priscilla King Gray Public Service Center to conduct more research in Kenya. In 2012, he formed Takachar as a team and received seed money from the MIT IDEAS Global Challenge, MIT Legatum Center for Development and Entrepreneurship, and D-Lab to produce charcoal from household organic waste. (This work also led to a fertilizer company, Safi Organics, that Kung founded in 2016 with the help of MIT IDEAS. But that is another story.)

Meanwhile, Kung had another top priority: finding a topic for his PhD dissertation. Back at MIT, he met Alexander Slocum, the Walter M. May and A. Hazel May Professor of Mechanical Engineering, who on a long walk-and-talk along the Charles River suggested he turn his Kenya work into a thesis. Slocum connected him with Robert Stoner, deputy director for science and technology at the MIT Energy Initiative (MITEI) and founding director of MITEI’s Tata Center for Technology and Design. Stoner in turn introduced Kung to Ghoniem, who became his PhD advisor, while Slocum and Stoner joined his doctoral committee.

Roots in MIT lab

Ghoniem’s telling of the Takachar story begins, not surprisingly, in the lab. Back in 2010, he had a master’s student interested in renewable energy, and he suggested the student investigate biomass. That student, Richard Bates ’10, SM ’12, PhD ’16, began exploring the science of converting biomass to more clean-burning charcoal through torrefaction.

Most torrefaction (also known as low-temperature pyrolysis) systems use external heating sources, but the lab’s goal, Ghoniem explains, was to develop an efficient, self-sustained reactor that would generate fewer emissions. “We needed to understand the chemistry and physics of the process, and develop fundamental scaling models, before going to the lab to build the device,” he says.

By the time Kung joined the lab in 2013, Ghoniem was working with the Tata Center to identify technology suitable for developing countries and largely based on renewable energy. Kung was able to secure a Tata Fellowship and — building on Bates’ research — develop the small-scale, practical device for biomass thermochemical conversion in the field that launched Takachar.

This device, which was patented by MIT with inventors Kung, Ghoniem, Stoner, MIT research scientist Santosh Shanbhogue, and Slocum, is self-contained and scalable. It burns a little of the biomass to generate heat; this heat bakes the rest of the biomass, releasing gases; the system then introduces air to enable these gases to combust, which burns off the volatiles and generates more heat, keeping the thermochemical reaction going.

“The trick is how to introduce the right amount of air at the right location to sustain the process,” Ghoniem explains. “If you put in more air, that will burn the biomass. If you put in less, there won’t be enough heat to produce the charcoal. That will stop the reaction.”

About 10 percent of the biomass is used as fuel to support the reaction, Kung says, adding that “90 percent is densified into a form that’s easier to handle and utilize.” He notes that the research received financial support from the Abdul Latif Jameel Water and Food Systems Lab and the Deshpande Center for Technological Innovation, both at MIT. Sonal Thengane, another postdoc in Ghoniem’s lab, participated in the effort to scale up the technology at the MIT Bates Lab (no relation to Richard Bates).

The charcoal produced is more valuable per ton and easier to transport and sell than biomass, reducing transportation costs by two-thirds and giving farmers an additional income opportunity — and an incentive not to burn agricultural waste, Kung says. “There’s more income for farmers, and you get better air quality.”

Roots in India

When Kung became a Tata Fellow, he joined a program founded to take on the biggest challenges of the developing world, with a focus on India. According to Stoner, Tata Fellows, including Kung, typically visit India twice a year and spend six to eight weeks meeting stakeholders in industry, the government, and in communities to gain perspective on their areas of study.

“A unique part of Tata is that you’re considering the ecosystem as a whole,” says Kung, who interviewed hundreds of smallholder farmers, met with truck drivers, and visited existing biomass processing plants during his Tata trips to India. (Along the way, he also connected with Indian engineer Vidyut Mohan, who became Takachar’s co-founder.)

“It was very important for Kevin to be there walking about, experimenting, and interviewing farmers,” Stoner says. “He learned about the lives of farmers.”

These experiences helped instill in Kung an appreciation for small farmers that still drives him today as Takachar rolls out its first pilot programs, tinkers with the technology, grows its team (now up to 10), and endeavors to build a revenue stream. So, while Takachar has gotten a lot of attention and accolades — from the IDEAS award to the Earthshot Prize — Kung says what motivates him is the prospect of improving people’s lives.

The dream, he says, is to empower communities to help both the planet and themselves. “We’re excited about the environmental justice perspective,” he says. “Our work brings production and carbon removal or avoidance to rural communities — providing them with a way to convert waste, make money, and reduce air pollution.”

This article appears in the Spring 2022 issue of Energy Futures, the magazine of the MIT Energy Initiative.

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MIT AgeLab awards five scholarships to students who further intergenerational connections

Since 2015, the MIT AgeLab has awarded scholarships to high school students who developed intergenerational programs — initiatives that bring together younger and older people for knowledge-sharing and social connection — in their communities. On Sept. 9, five $5,000 OMEGA scholarships were given to high school students across the United States, supported by the sponsorship of AlerisLife, a senior living and rehabilitation and wellness services company headquartered in Newton, Massachusetts, and AARP.

OMEGA, which stands for Opportunities for Multigenerational Exchange, Growth, and Action, develops programming and offers scholarships to facilitate intergenerational connections between younger people and older adults in their communities.

The scholarships were awarded at a virtual ceremony hosted by the MIT AgeLab, with representatives from the AgeLab, AARP, and AlerisLife in attendance, along with the scholarship winners, their parents, and mentors.

Intergenerational programs have numerous potential benefits. They may have positive impacts for the health and well-being of older participants, reducing social isolation and fostering a sense of meaningfulness. They may provide a similar sense of meaning for younger people, as well as exposing younger participants to perspectives and wisdom that often come only with age. And younger participants may have their own knowledge to impart to older adults.

But the simplest reason to develop such programming, suggests Steven Griffon, interim director of AARP Massachusetts, is the enjoyment that it can bring to participants of all ages. “At AARP, we work with those 50 and older, but really we work with everybody,” Griffon said at the OMEGA award ceremony. “In my normal day-to-day role, I do a lot of work on issue campaigns, and the No. 1 thing that I try to remind folks is [that] it's key to have fun. Folks who are older love to have fun, and folks who are younger love to have fun.”

The five scholarship winners and their winning programs are:

• Cora Funk, senior at Valor Collegiate Academy in Nashville, Tennessee. After attending an OMEGA Summit in 2020, Funk developed “Students Connecting with Seniors,” a club connecting local high school students with older adults in the Nashville community. SCS primarily partners with FiftyForward, a local nonprofit organization.
• Maya Joshi, senior at Walter Payton College Preparatory High School in Chicago, Illinois. Joshi is the president and founder of a chapter-based nonprofit “Lifting Hearts with the Arts,” which connects older adults and youth for arts-based, one-on-one activities as well as group programming including trivia, art lessons, and tai chi.
• Maya Lall, senior at Holton-Arms School in Bethesda, Maryland. Lall founded and serves as executive director of “Supporting Seniors,” which provides older adults with technology support through video demonstrations, virtual and in-person troubleshooting, and technology courses at local senior living communities including Five Star Premier Residences of Chevy Chase and Aspenwood Senior Living Community.
• Steven Yang, senior at Wayzata High School in Plymouth, Minnesota. Yang is founder and president of “Zenith,” which partners with TCM Health Center to train high school student volunteers to teach tai chi classes in local residential and assisted living communities.
• Michael Wilson, now a student at Rose-Hulman Institute of Technology in Terre Haute, Indiana. Wilson coordinated a local chapter of the Arizona Old Time Fiddlers Association. His program, “Bridging the Gap through Music,” fosters intergenerational interactions through acoustic music jams and performances. He is also a lead speaker, singer, and mandolin player in the band “Six Gal ‘n Hat,” which plays music for older adults at local events.

In the remarks he gave in accepting his award, Wilson emphasized the benefits he received from intergenerational connections as well as those gained by his older counterparts. “Just hanging out with people who are my age, even though it might be comfortable, I don't stand to benefit very much,” Wilson said. “It's not only that I’m willing to sacrifice my time to enrich someone else's life, but they're enriching my life. That's something that I really want to convey to my generation. We have the opportunity to glean things that would take another 50 or 60 years to learn.”

In addition to recognizing their work with college scholarships, the AgeLab’s OMEGA program works year-round with students to develop their intergenerational programs. Students interested in intergenerational programming and careers in aging are invited to attend the virtual 2022 OMEGA Summit on Oct. 15.

The MIT AgeLab was created in 1999 within the MIT Center for Transportation and Logistics in order to invent new ideas and creatively translate technologies into practical solutions that improve people's health and enable them to “do things” throughout their lifespan. Equal to the need for ideas and new technologies is the belief that innovations in how products are designed, services are delivered, or policies are implemented are of critical importance to our quality of life tomorrow.

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Breaking through the mucus barrier

One reason that it’s so difficult to deliver large protein drugs orally is that these drugs can’t pass through the mucus barrier that lines the digestive tract. This means that insulin and most other “biologic drugs” — drugs consisting of proteins or nucleic acids — have to be injected or administered in a hospital. 

A new drug capsule developed at MIT may one day be able to replace those injections. The capsule has a robotic cap that spins and tunnels through the mucus barrier when it reaches the small intestine, allowing drugs carried by the capsule to pass into cells lining the intestine.

“By displacing the mucus, we can maximize the dispersion of the drug within a local area and enhance the absorption of both small molecules and macromolecules,” says Giovanni Traverso, the Karl van Tassel Career Development Assistant Professor of Mechanical Engineering at MIT and a gastroenterologist at Brigham and Women’s Hospital.

In a study appearing today in Science Robotics, the researchers demonstrated that they could use this approach to deliver insulin as well as vancomycin, an antibiotic peptide that currently has to be injected.

Shriya Srinivasan, a research affiliate at MIT’s Koch Institute for Integrative Cancer Research and a junior fellow at the Society of Fellows at Harvard University, is the lead author of the study.

Tunneling through

For several years, Traverso’s lab has been developing strategies to deliver protein drugs such as insulin orally. This is a difficult task because protein drugs tend to be broken down in acidic environment of the digestive tract, and they also have difficulty penetrating the mucus barrier that lines the tract.

To overcome those obstacles, Srinivasan came up with the idea of creating a protective capsule that includes a mechanism that can tunnel through mucus, just as tunnel boring machines drill into soil and rock.

“I thought that if we could tunnel through the mucus, then we could deposit the drug directly on the epithelium,” she says. “The idea is that you would ingest this capsule and the outer layer would dissolve in the digestive tract, exposing all these features that start to churn through the mucus and clear it.”

The “RoboCap” capsule, which is about the size of a multivitamin, carries its drug payload in a small reservoir at one end and carries the tunnelling features in its main body and surface. The capsule is coated with gelatin that can be tuned to dissolve at a specific pH.

When the coating dissolves, the change in pH triggers a tiny motor inside the RoboCap capsule to start spinning. This motion helps the capsule to tunnel into the mucus and displace it. The capsule is also coated with small studs that brush mucus away, similar to the action of a toothbrush.

The spinning motion also helps to erode the compartment that carries the drug, which is gradually released into the digestive tract.

“What the RoboCap does is transiently displace the initial mucus barrier and then enhance absorption by maximizing the dispersion of the drug locally,” Traverso says. “By combining all of these elements, we’re really maximizing our capacity to provide the optimal situation for the drug to be absorbed.”

Enhanced delivery

In tests in animals, the researchers used this capsule to deliver either insulin or vancomycin, a large peptide antibiotic that is used to treat a broad range of infections, including skin infections as well as infections affecting orthopedic implants. With the capsule, the researchers found that they could deliver 20 to 40 times more drug than a similar capsule without the tunneling mechanism.

Once the drug is released from the capsule, the capsule itself passes through the digestive tract on its own. The researchers found no sign of inflammation or irritation in the digestive tract after the capsule passed through, and they also observed that the mucus layer reforms within a few hours after being displaced by the capsule.

Another approach that some researchers have used to enhance oral delivery of drugs is to give them along with additional drugs that help them cross through the intestinal tissue. However, these enhancers often only work with certain drugs. Because the MIT team’s new approach relies solely on mechanical disruptions to the mucus barrier, it could potentially be applied to a broader set of drugs, Traverso says.

“Some of the chemical enhancers preferentially work with certain drug molecules,” he says. “Using mechanical methods of administration can potentially enable more drugs to have enhanced absorption.”

While the capsule used in this study released its payload in the small intestine, it could also be used to target the stomach or colon by changing the pH at which the gelatin coating dissolves. The researchers also plan to explore the possibility of delivering other protein drugs such as GLP1 receptor agonist, which is sometimes used to treat type 2 diabetes. The capsules could also be used to deliver topical drugs to treat ulcerative colitis and other inflammatory conditions by maximizing the local concentration of the drugs in the tissue to help treat the inflammation.

The research was funded, in part, by the National Institutes of Health and MIT’s Department of Mechanical Engineering.

Other authors of the paper include Amro Alshareef, Alexandria Hwang, Zilianng Kang, Johannes Kuosmanen, Keiko Ishida, Joshua Jenkins, Sabrina Liu, Wiam Abdalla Mohammed Madani, Jochen Lennerz, Alison Hayward, Josh Morimoto, Nina Fitzgerald, and Robert Langer.

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MIT biologist Richard Hynes wins Lasker Award

MIT Professor Richard Hynes, a pioneer in studying cellular adhesion, has been named a recipient of the 2022 Albert Lasker Basic Medical Research Award.

Hynes, the Daniel K. Ludwig Professor for Cancer Research and a member of MIT’s Koch Institute for Integrative Cancer Research, was honored for the discovery of integrins, proteins that are key to cell-cell and cell-matrix interactions in the body. He will share the prize with Erkki Ruoslahti of Sanford Burnham Prebys and Timothy Springer of Harvard University.

“I’m delighted, and it’s a pleasure to be sharing it with them,” Hynes says. “It’s great for the field, and for the trainees who did much of the work.”

Hynes’ research focuses on proteins that allow cells to adhere to each other and to the extracellular matrix — a mesh-like network that provides structural support for cells. These proteins include integrins, a type of cell surface receptor, and fibronectins, a family of extracellular adhesive proteins. Integrins are the major adhesion receptors connecting the extracellular matrix to the intracellular cytoskeleton.

During embryonic development, cell adhesion is critical for cells to move to the correct locations in the embryo. Hynes’ work has also revealed that dysregulation of cell-to-matrix contact plays an important role in cancer cells’ ability to detach from a tumor and spread to other parts of the body, in a process known as metastasis.

“Professor Hynes’ contributions to the field of cancer biology, and more broadly, cellular biology, are numerous,” says Nergis Mavalvala, the Curtis and Kathleen Marble Professor of Astrophysics and the dean of the School of Science. “His investigations of fundamental biological questions — How do cells interact? How do they stick together? — changed how scientists approach cancer research and opened up avenues in developing potential therapeutics to disrupt metastatic disease.”

Born in Kenya, Hynes grew up in Liverpool, in the United Kingdom. Both of his parents were scientists: His father was a freshwater ecologist, and his mother a physics teacher. Hynes and all three of his siblings followed their parents into scientific fields.

“We talked science at home, and if we asked questions, we got questions back, not answers. So that conditioned me into being a scientist, for sure,” Hynes says.

After earning his bachelor’s and master’s degrees in biochemistry at Cambridge University, Hynes decided to head to the United States to continue graduate school. Colleagues at Cambridge suggested MIT, so he came to the Institute and earned his PhD in 1971. After doing a postdoc at the Imperial Cancer Research Fund Laboratories in London, he returned to MIT in 1975 as a faculty member in the Department of Biology and a founding member of MIT’s Center for Cancer Research (the predecessor of today’s Koch Institute).

Hynes began his career as a developmental biologist, studying how cells move to the correct locations during embryonic development. As a postdoc, he began studying the differences in the surface landscapes of healthy cells and tumor cells. This led to the discovery of a protein called fibronectin, which is often lost when cells become cancerous. 

He and others found that fibronectin is part of the extracellular matrix, the network of proteins and other molecules that support cells and tissues in the body. When fibronectin is lost, cancer cells can more easily free themselves from their original location and metastasize to other sites in the body. Cells bind to the matrix through cell surface receptors known as integrins. In humans, 24 integrin proteins have been identified. These proteins help give tissues their structure, enable blood to clot, and are essential for embryonic development.

“These cell-matrix adhesion proteins hold us all together,” Hynes says. “If we didn’t have them, we’d be a pool of cells on the floor. And they’re contributors to lots of diseases: fibrosis, cancer, thrombosis, immune and autoimmune diseases. So, cell adhesion has become a huge field at both the basic science level and the therapeutic level.”

Since joining the MIT faculty, Hynes has also served as head and associate head of the Department of Biology, and as director of the Center for Cancer Research. He has also served as scientific governor of the Wellcome Trust in the United Kingdom, and as co-chair of National Academy committees establishing guidelines for stem cell and genome editing research.

His many awards include the Gairdner Foundation International Award, the Distinguished Investigator Award from the International Society for Matrix Biology, the Robert and Claire Pasarow Medical Research Award, the E.B. Wilson Medal from the American Society for Cell Biology and the Paget-Ewing Award, Metastasis Research Society. Hynes is also a member of the National Academy of Sciences, the National Academy of Medicine, the Royal Society of London, the American Association for the Advancement of Science, and the American Academy of Arts and Sciences.

The Lasker Award comes with a $250,000 prize, which will be shared between the three recipients.

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Exploring how new technologies are changing finance

MIT Hong Kong Innovation Node held its annual financial technology (fintech) entrepreneurship boot camp this summer, connecting university students with corporate partners to tackle real-world business challenges.  

Building on the belief that innovative, creative solutions deliver more value and a better experience, the MIT Entrepreneurship and Fintech Integrator (MEFTI) program featured unique problem statements proposed by Prudential Hong Kong and Openhive.

“These challenges are unique opportunities to bring ideas and talent together to address opportunities in the areas of digital engagement, the metaverse, and leveraging alternative data and artificial intelligence,” says Charles Sodini, the LeBel Professor of Electrical Engineering at MIT and faculty director at the node. 

Embodying a blended reality

Business models and the rules of engagement are evolving with changing consumer behaviors and emerging new patterns, opening a floodgate for companies to seize opportunities to innovate in the digital space.

For Nesu Nhamo, a junior at MIT studying computer science and engineering, this year’s challenges were “a great catalyst for thinking outside of the box and leveraging new technologies,” he says. “Prudential, combined with the metaverse prompt, broadened my understanding of what a fintech app could be.”

His team, consisting of students from MIT and from Hong Kong, designed an incentive-based social running app to motivate millennials to maintain a healthy lifestyle. Differentiating from other apps on the market, the app combines fitness, partnership rewards, and social connectivity wherever runners are. The idea came when user interviews revealed the challenge of exercising and doing physical activities with friends encumbered by travel limitations.

Tackling market problems requires testing early and failing fast. For Nhamo, who aspires to become an entrepreneur and angel investor, the disciplined entrepreneurship framework applied in MEFTI is “a consistent way to identify problems and rapidly test ideas,” he says.

A core feature of the boot camp is to figure out what customer problems exist and what problem to solve. Staying faithful to the framework, Nhamo added that his team “overcame this challenge by making assumptions and testing them through primary market research.” This process helped distill the problem and isolate an emerging opportunity to integrate a mixed-reality experience into their proposal.

Achieving synergy between industry and academia

There are tremendous benefits to giving students access to companies as a sandbox for creative problem-solving. The exposure facilitates action learning by helping students apply theory into a practical context. But the learning gains are mutual.

“We actually learned a lot from everybody else around us and the students,” says Sam Lim MBA ’04, chief operations and transformation officer at Prudential Hong Kong. A circular style of engagement “in the spirit of collaboration and building community” enabled mentors to draw on the millennial digital intelligence as well as offer industry insights.

Jasmine Zeng ’22, who studied electrical engineering and computer science at MIT, enjoyed the opportunity to “work closely with industry partners — learning about their concerns, core business logic, company mission, and future vision. It’s rewarding to see how our final project met their expectations in a way that they think is profitable and innovative.”

The 2022 showcase marked the fifth year of MEFTI, featuring an ensemble of industry experts and business leaders who provided feedback on these student projects:

• Z-Lion, a health and wealth super-app plugin for millennials to boost awareness of financial knowledge and engagement of financial products;
• Metasurance, an insurance product offering digital asset owners protection from physical damage to NFT wallets and cybersecurity threats;
• Metabolic, an incentive-based social running app to motivate millennials to maintain a healthy lifestyle featuring a combination of fitness, rewards, and social connectivity wherever runners are;
• Nexus, an online platform matching potential borrowers to bank lenders using predictive modeling techniques drawing from alternative and traditional data; and
• Eco-Cash, a lending platform providing micro loans to millennials to meet their financial goals, while prioritizing their spending on environmental, social, and governance (ESG)-focused products.

Lim, who was among the judges, hopes that students who are interested in entrepreneurship pursue their passion. “With that passion, you’ll find that you can really succeed in anything you do,” he says.

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Investigating at the interface of data science and computing

A visual model of Guy Bresler’s research would probably look something like a Venn diagram. He works at the four-way intersection where theoretical computer science, statistics, probability, and information theory collide.

“There are always new things to do be done at the interface. There are always opportunities for entirely new questions to ask,” says Bresler, an associate professor who recently earned tenure in MIT’s Department of Electrical Engineering and Computer Science (EECS).

A theoretician, he aims to understand the delicate interplay between structure in data, the complexity of models, and the amount of computation needed to learn those models. Recently, his biggest focus has been trying to unveil fundamental phenomena that are broadly responsible for determining the computational complexity of statistics problems — and finding the “sweet spot” where available data and computation resources enable researchers to effectively solve a problem.

When trying to solve a complex statistics problem, there is often a tug-of-war between data and computation. Without enough data, the computation needed to solve a statistical problem can be intractable, or at least consume a staggering amount of resources. But get just enough data and suddenly the intractable becomes solvable; the amount of computation needed to come up with a solution drops dramatically.

The majority of modern statistical problems exhibits this sort of trade-off between computation and data, with applications ranging from drug development to weather prediction. Another well-studied and practically important example is cryo-electron microscopy, Bresler says. With this technique, researchers use an electron microscope to take images of molecules in different orientations. The central challenge is how to solve the inverse problem — determining the molecule’s structure given the noisy data. Many statistical problems can be formulated as inverse problems of this sort.

One aim of Bresler’s work is to elucidate relationships between the wide variety of different statistics problems currently being studied. The dream is to classify statistical problems into equivalence classes, as has been done for other types of computational problems in the field of computational complexity. Showing these sorts of relationships means that, instead of trying to understand each problem in isolation, researchers can transfer their understanding from a well-studied problem to a poorly understood one, he says.

Adopting a theoretical approach

For Bresler, a desire to theoretically understand various basic phenomena inspired him to follow a path into academia.

Both of his parents worked as professors and showed how fulfilling academia can be, he says. His earliest introduction to the theoretical side of engineering came from his father, who is an electrical engineer and theoretician studying signal processing. Bresler was inspired by his work from an early age. As an undergraduate at the University of Illinois at Urbana-Champaign, he bounced between physics, math, and computer science courses. But no matter the topic, he gravitated toward the theoretical viewpoint.

In graduate school at the University of California at Berkeley, Bresler enjoyed the opportunity to work in a wide variety of topics spanning probability, theoretical computer science, and mathematics. His driving motivator was a love of learning new things.

“Working at the interface of multiple fields with new questions, there is a feeling that one had better learn as much as possible if one is to have any chance of finding the right tools to answer those questions,” he says.

That curiosity led him to MIT for a postdoc in the Laboratory for Information and Decision Systems (LIDS) in 2013, and then he joined the faculty two years later as an assistant professor in EECS. He was named an associate professor in 2019.

Bresler says he was drawn to the intellectual atmosphere at MIT, as well as the supportive environment for launching bold research quests and trying to make progress in new areas of study.

Opportunities for collaboration

“What really struck me was how vibrant and energetic and collaborative MIT is. I have this mental list of more than 20 people here who I would love to have lunch with every single week and collaborate with on research. So just based on sheer numbers, joining MIT was a clear win,” he says.

He’s especially enjoyed collaborating with his students, who continually teach him new things and ask deep questions that drive exciting research projects. One such student, Matthew Brennan, who was one of Bresler’s closest collaborators, tragically and unexpectedly passed away in January, 2021.

The shock from Brennan’s death is still raw for Bresler, and it derailed his research for a time.

“Beyond his own prodigious capabilities and creativity, he had this amazing ability to listen to an idea of mine that was almost completely wrong, extract from it a useful piece, and then pass the ball back,” he says. “We had the same vision for what we wanted to achieve in the work, and we were driven to try to tell a certain story. At the time, almost nobody was pursuing this particular line of work, and it was in a way kind of lonely. But he trusted me, and we encouraged one another to keep at it when things seemed bleak.”

Those lessons in perseverance fuel Bresler as he and his students continue exploring questions that, by their nature, are difficult to answer.

One area he’s worked in on-and-off for over a decade involves learning graphical models from data. Models of certain types of data, such as time-series data consisting of temperature readings, are often constructed by domain experts who have relevant knowledge and can build a reasonable model, he explains.

But for many types of data with complex dependencies, such as social network or biological data, it is not at all clear what structure a model should take. Bresler’s work seeks to estimate a structured model from data, which could then be used for downstream applications like making recommendations or better predicting the weather.

The basic question of identifying good models, whether algorithmically in a complex setting or analytically, by specifying a useful toy model for theoretical analysis, connects the abstract work with engineering practice, he says.

“In general, modeling is an art. Real life is complicated and if you write down some super-complicated model that tries to capture every feature of a problem, it is doomed,” says Bresler. “You have to think about the problem and understand the practical side of things on some level to identify the correct features of the problem to be modeled, so that you can hope to actually solve it and gain insight into what one should do in practice.”

Outside the lab, Bresler often finds himself solving very different kinds of problems. He is an avid rock climber and spends much of his free time bouldering throughout New England.

“I really love it. It is a good excuse to get outside and get sucked into a whole different world. Even though there is problem solving involved, and there are similarities at the philosophical level, it is totally orthogonal to sitting down and doing math,” he says.

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Neurodegenerative disease can progress in newly identified patterns

Neurodegenerative diseases — like amyotrophic lateral sclerosis (ALS, or Lou Gehrig's disease), Alzheimer’s, and Parkinson’s — are complicated, chronic ailments that can present with a variety of symptoms, worsen at different rates, and have many underlying genetic and environmental causes, some of which are unknown. ALS, in particular, affects voluntary muscle movement and is always fatal, but while most people survive for only a few years after diagnosis, others live with the disease for decades. Manifestations of ALS can also vary significantly; often slower disease development correlates with onset in the limbs and affecting fine motor skills, while the more serious, bulbar ALS impacts swallowing, speaking, breathing, and mobility. Therefore, understanding the progression of diseases like ALS is critical to enrollment in clinical trials, analysis of potential interventions, and discovery of root causes.

However, assessing disease evolution is far from straightforward. Current clinical studies typically assume that health declines on a downward linear trajectory on a symptom rating scale, and use these linear models to evaluate whether drugs are slowing disease progression. However, data indicate that ALS often follows nonlinear trajectories, with periods where symptoms are stable alternating with periods when they are rapidly changing. Since data can be sparse, and health assessments often rely on subjective rating metrics measured at uneven time intervals, comparisons across patient populations are difficult. These heterogenous data and progression, in turn, complicate analyses of invention effectiveness and potentially mask disease origin.

Now, a new machine-learning method developed by researchers from MIT, IBM Research, and elsewhere aims to better characterize ALS disease progression patterns to inform clinical trial design.

“There are groups of individuals that share progression patterns. For example, some seem to have really fast-progressing ALS and others that have slow-progressing ALS that varies over time,” says Divya Ramamoorthy PhD ’22, a research specialist at MIT and lead author of a new paper on the work that was published this month in Nature Computational Science. “The question we were asking is: can we use machine learning to identify if, and to what extent, those types of consistent patterns across individuals exist?”

Their technique, indeed, identified discrete and robust clinical patterns in ALS progression, many of which are non-linear. Further, these disease progression subtypes were consistent across patient populations and disease metrics. The team additionally found that their method can be applied to Alzheimer’s and Parkinson’s diseases as well.

Joining Ramamoorthy on the paper are MIT-IBM Watson AI Lab members Ernest Fraenkel, a professor in the MIT Department of Biological Engineering; Research Scientist Soumya Ghosh of IBM Research; and Principal Research Scientist Kenney Ng, also of IBM Research. Additional authors include Kristen Severson PhD ’18, a senior researcher at Microsoft Research and former member of the Watson Lab and of IBM Research; Karen Sachs PhD ’06 of Next Generation Analytics; a team of researchers with Answer ALS; Jonathan D. Glass and Christina N. Fournier of the Emory University School of Medicine; the Pooled Resource Open-Access ALS Clinical Trials Consortium; ALS/MND Natural History Consortium; Todd M. Herrington of Massachusetts General Hospital (MGH) and Harvard Medical School; and James D. Berry of MGH.

Reshaping health decline

After consulting with clinicians, the team of machine learning researchers and neurologists let the data speak for itself. They designed an unsupervised machine-learning model that employed two methods: Gaussian process regression and Dirichlet process clustering. These inferred the health trajectories directly from patient data and automatically grouped similar trajectories together without prescribing the number of clusters or the shape of the curves, forming ALS progression “subtypes.” Their method incorporated prior clinical knowledge in the way of a bias for negative trajectories — consistent with expectations for neurodegenerative disease progressions — but did not assume any linearity. “We know that linearity is not reflective of what's actually observed,” says Ng. “The methods and models that we use here were more flexible, in the sense that, they capture what was seen in the data,” without the need for expensive labeled data and prescription of parameters.

Primarily, they applied the model to five longitudinal datasets from ALS clinical trials and observational studies. These used the gold standard to measure symptom development: the ALS functional rating scale revised (ALSFRS-R), which captures a global picture of patient neurological impairment but can be a bit of a “messy metric.” Additionally, performance on survivability probabilities, forced vital capacity (a measurement of respiratory function), and subscores of ALSFRS-R, which looks at individual bodily functions, were incorporated.

New regimes of progression and utility

When their population-level model was trained and tested on these metrics, four dominant patterns of disease popped out of the many trajectories — sigmoidal fast progression, stable slow progression, unstable slow progression, and unstable moderate progression — many with strong nonlinear characteristics. Notably, it captured trajectories where patients experienced a sudden loss of ability, called a functional cliff, which would significantly impact treatments, enrollment in clinical trials, and quality of life.

The researchers compared their method against other commonly used linear and nonlinear approaches in the field to separate the contribution of clustering and linearity to the model’s accuracy. The new work outperformed them, even patient-specific models, and found that subtype patterns were consistent across measures. Impressively, when data were withheld, the model was able to interpolate missing values, and, critically, could forecast future health measures. The model could also be trained on one ALSFRS-R dataset and predict cluster membership in others, making it robust, generalizable, and accurate with scarce data. So long as 6-12 months of data were available, health trajectories could be inferred with higher confidence than conventional methods.

The researchers’ approach also provided insights into Alzheimer’s and Parkinson’s diseases, both of which can have a range of symptom presentations and progression. For Alzheimer’s, the new technique could identify distinct disease patterns, in particular variations in the rates of conversion of mild to severe disease. The Parkinson’s analysis demonstrated a relationship between progression trajectories for off-medication scores and disease phenotypes, such as the tremor-dominant or postural instability/gait difficulty forms of Parkinson’s disease.

The work makes significant strides to find the signal amongst the noise in the time-series of complex neurodegenerative disease. “The patterns that we see are reproducible across studies, which I don't believe had been shown before, and that may have implications for how we subtype the [ALS] disease,” says Fraenkel. As the FDA has been considering the impact of non-linearity in clinical trial designs, the team notes that their work is particularly pertinent.

As new ways to understand disease mechanisms come online, this model provides another tool to pick apart illnesses like ALS, Alzheimer’s, and Parkinson’s from a systems biology perspective.

“We have a lot of molecular data from the same patients, and so our long-term goal is to see whether there are subtypes of the disease,” says Fraenkel, whose lab looks at cellular changes to understand the etiology of diseases and possible targets for cures. “One approach is to start with the symptoms … and see if people with different patterns of disease progression are also different at the molecular level. That might lead you to a therapy. Then there's the bottom-up approach, where you start with the molecules” and try to reconstruct biological pathways that might be affected. “We're going [to be tackling this] from both ends … and finding if something meets in the middle.”

This research was supported, in part, by the MIT-IBM Watson AI Lab, the Muscular Dystrophy Association, Department of Veterans Affairs of Research and Development, the Department of Defense, NSF Gradate Research Fellowship Program, Siebel Scholars Fellowship, Answer ALS, the United States Army Medical Research Acquisition Activity, National Institutes of Health, and the NIH/NINDS.

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New program to support translational research in AI, data science, and machine learning

The MIT School of Engineering and Pillar VC today announced the MIT-Pillar AI Collective, a one-year pilot program funded by a gift from Pillar VC that will provide seed grants for projects in artificial intelligence, machine learning, and data science with the goal of supporting translational research. The program will support graduate students and postdocs through access to funding, mentorship, and customer discovery.

Administered by the MIT Deshpande Center for Technological Innovation, the MIT-Pillar AI Collective will center on the market discovery process, advancing projects through market research, customer discovery, and prototyping. Graduate students and postdocs will aim to emerge from the program having built minimum viable products, with support from Pillar VC and experienced industry leaders.

“We are grateful for this support from Pillar VC and to join forces to converge the commercialization of translational research in AI, data science, and machine learning, with an emphasis on identifying and cultivating prospective entrepreneurs,” says Anantha Chandrakasan, dean of the MIT School of Engineering and Vannevar Bush Professor of Electrical Engineering and Computer Science. “Pillar’s focus on mentorship for our graduate students and postdoctoral researchers, and centering the program within the Deshpande Center, will undoubtedly foster big ideas in AI and create an environment for prospective companies to launch and thrive.” 

Founded by Jamie Goldstein ’89, Pillar VC is committed to growing companies and investing in personal and professional development, coaching, and community.

“Many of the most promising companies of the future are living at MIT in the form of transformational research in the fields of data science, AI, and machine learning,” says Goldstein. “We’re honored by the chance to help unlock this potential and catalyze a new generation of founders by surrounding students and postdoctoral researchers with the resources and mentorship they need to move from the lab to industry.”

The program will launch with the 2022-23 academic year. Grants will be open only to MIT faculty and students, with an emphasis on funding for graduate students in their final year, as well as postdocs. Applications must be submitted by MIT employees with principal investigator status. A selection committee composed of three MIT representatives will include Devavrat Shah, faculty director of the Deshpande Center, the Andrew (1956) and Erna Viterbi Professor in the Department of Electrical Engineering and Computer Science and the Institute for Data, Systems, and Society; the chair of the selection committee; and a representative from the MIT Schwarzman College of Computing. The committee will also include representation from Pillar VC. Funding will be provided for up to nine research teams.

“The Deshpande Center will serve as the perfect home for the new collective, given its focus on moving innovative technologies from the lab to the marketplace in the form of breakthrough products and new companies,” adds Chandrakasan. 

“The Deshpande Center has a 20-year history of guiding new technologies toward commercialization, where they can have a greater impact,” says Shah. “This new collective will help the center expand its own impact by helping more projects realize their market potential and providing more support to researchers in the fast-growing fields of AI, machine learning, and data science.”

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Q&A: Global challenges surrounding the deployment of AI

The AI Policy Forum (AIPF) is an initiative of the MIT Schwarzman College of Computing to move the global conversation about the impact of artificial intelligence from principles to practical policy implementation. Formed in late 2020, AIPF brings together leaders in government, business, and academia to develop approaches to address the societal challenges posed by the rapid advances and increasing applicability of AI.

The co-chairs of the AI Policy Forum are Aleksander Madry, the Cadence Design Systems Professor; Asu Ozdaglar, deputy dean of academics for the MIT Schwarzman College of Computing and head of the Department of Electrical Engineering and Computer Science; and Luis Videgaray, senior lecturer at MIT Sloan School of Management and director of MIT AI Policy for the World Project. Here, they discuss talk some of the key issues facing the AI policy landscape today and the challenges surrounding the deployment of AI. The three are co-organizers of the upcoming AI Policy Forum Summit on Sept. 28, which will further explore the issues discussed here.

Q: Can you talk about the ­ongoing work of the AI Policy Forum and the AI policy landscape generally?

Ozdaglar: There is no shortage of discussion about AI at different venues, but conversations are often high-level, focused on questions of ethics and principles, or on policy problems alone. The approach the AIPF takes to its work is to target specific questions with actionable policy solutions and engage with the stakeholders working directly in these areas. We work “behind the scenes” with smaller focus groups to tackle these challenges and aim to bring visibility to some potential solutions alongside the players working directly on them through larger gatherings.

Q: AI impacts many sectors, which makes us naturally worry about its trustworthiness. Are there any emerging best practices for development and deployment of trustworthy AI?

Madry: The most important thing to understand regarding deploying trustworthy AI is that AI technology isn’t some natural, preordained phenomenon. It is something built by people. People who are making certain design decisions.

We thus need to advance research that can guide these decisions as well as provide more desirable solutions. But we also need to be deliberate and think carefully about the incentives that drive these decisions. 

Now, these incentives stem largely from the business considerations, but not exclusively so. That is, we should also recognize that proper laws and regulations, as well as establishing thoughtful industry standards have a big role to play here too.

Indeed, governments can put in place rules that prioritize the value of deploying AI while being keenly aware of the corresponding downsides, pitfalls, and impossibilities. The design of such rules will be an ongoing and evolving process as the technology continues to improve and change, and we need to adapt to socio-political realities as well.

Q: Perhaps one of the most rapidly evolving domains in AI deployment is in the financial sector. From a policy perspective, how should governments, regulators, and lawmakers make AI work best for consumers in finance?

Videgaray: The financial sector is seeing a number of trends that present policy challenges at the intersection of AI systems. For one, there is the issue of explainability. By law (in the U.S. and in many other countries), lenders need to provide explanations to customers when they take actions deleterious in whatever way, like denial of a loan, to a customer’s interest. However, as financial services increasingly rely on automated systems and machine learning models, the capacity of banks to unpack the “black box” of machine learning to provide that level of mandated explanation becomes tenuous. So how should the finance industry and its regulators adapt to this advance in technology? Perhaps we need new standards and expectations, as well as tools to meet these legal requirements.

Meanwhile, economies of scale and data network effects are leading to a proliferation of AI outsourcing, and more broadly, AI-as-a-service is becoming increasingly common in the finance industry. In particular, we are seeing fintech companies provide the tools for underwriting to other financial institutions — be it large banks or small, local credit unions. What does this segmentation of the supply chain mean for the industry? Who is accountable for the potential problems in AI systems deployed through several layers of outsourcing? How can regulators adapt to guarantee their mandates of financial stability, fairness, and other societal standards?

Q: Social media is one of the most controversial sectors of the economy, resulting in many societal shifts and disruptions around the world. What policies or reforms might be needed to best ensure social media is a force for public good and not public harm?

Ozdaglar: The role of social media in society is of growing concern to many, but the nature of these concerns can vary quite a bit — with some seeing social media as not doing enough to prevent, for example, misinformation and extremism, and others seeing it as unduly silencing certain viewpoints. This lack of unified view on what the problem is impacts the capacity to enact any change. All of that is additionally coupled with the complexities of the legal framework in the U.S. spanning the First Amendment, Section 230 of the Communications Decency Act, and trade laws.

However, these difficulties in regulating social media do not mean that there is nothing to be done. Indeed, regulators have begun to tighten their control over social media companies, both in the United States and abroad, be it through antitrust procedures or other means. In particular, Ofcom in the U.K. and the European Union is already introducing new layers of oversight to platforms. Additionally, some have proposed taxes on online advertising to address the negative externalities caused by current social media business model. So, the policy tools are there, if the political will and proper guidance exists to implement them.

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Featured video: Building a roller coaster

Every year during residence exploration week at MIT, or REX week, our undergraduate residence halls host activities to encourage new students to visit, get to know the vibe of the community, and hopefully choose to join.

So, how do you get the attention of first-year MIT students? At East Campus, you invite them to help you build a working roller coaster.

The roller coaster team undergoes training and works with the City of Cambridge to ensure proper safety measures are followed. Once building begins, interested first-year students are invited to help with construction, and when it’s finished, to take ride. When the coaster comes down after REX week, the materials are recycled and reused – with some going to students who use them to customize their rooms.

Video by: Melanie Gonick/MIT News | 3 min 21 sec

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MIT engineers build a battery-free, wireless underwater camera

Scientists estimate that more than 95 percent of Earth’s oceans have never been observed, which means we have seen less of our planet’s ocean than we have the far side of the moon or the surface of Mars.

The high cost of powering an underwater camera for a long time, by tethering it to a research vessel or sending a ship to recharge its batteries, is a steep challenge preventing widespread undersea exploration.

MIT researchers have taken a major step to overcome this problem by developing a battery-free, wireless underwater camera that is about 100,000 times more energy-efficient than other undersea cameras. The device takes color photos, even in dark underwater environments, and transmits image data wirelessly through the water.

The autonomous camera is powered by sound. It converts mechanical energy from sound waves traveling through water into electrical energy that powers its imaging and communications equipment. After capturing and encoding image data, the camera also uses sound waves to transmit data to a receiver that reconstructs the image. 

Because it doesn’t need a power source, the camera could run for weeks on end before retrieval, enabling scientists to search remote parts of the ocean for new species. It could also be used to capture images of ocean pollution or monitor the health and growth of fish raised in aquaculture farms.

“One of the most exciting applications of this camera for me personally is in the context of climate monitoring. We are building climate models, but we are missing data from over 95 percent of the ocean. This technology could help us build more accurate climate models and better understand how climate change impacts the underwater world,” says Fadel Adib, associate professor in the Department of Electrical Engineering and Computer Science and director of the Signal Kinetics group in the MIT Media Lab, and senior author of a new paper on the system.

Joining Adib on the paper are co-lead authors and Signal Kinetics group research assistants Sayed Saad Afzal, Waleed Akbar, and Osvy Rodriguez, as well as research scientist Unsoo Ha, and former group researchers Mario Doumet and Reza Ghaffarivardavagh. The paper is published today in Nature Communications.

Going battery-free

To build a camera that could operate autonomously for long periods, the researchers needed a device that could harvest energy underwater on its own while consuming very little power.

The camera acquires energy using transducers made from piezoelectric materials that are placed around its exterior. Piezoelectric materials produce an electric signal when a mechanical force is applied to them. When a sound wave traveling through the water hits the transducers, they vibrate and convert that mechanical energy into electrical energy.

Those sound waves could come from any source, like a passing ship or marine life. The camera stores harvested energy until it has built up enough to power the electronics that take photos and communicate data.

To keep power consumption as a low as possible, the researchers used off-the-shelf, ultra-low-power imaging sensors. But these sensors only capture grayscale images. And since most underwater environments lack a light source, they needed to develop a low-power flash, too.

“We were trying to minimize the hardware as much as possible, and that creates new constraints on how to build the system, send information, and perform image reconstruction. It took a fair amount of creativity to figure out how to do this,” Adib says.

They solved both problems simultaneously using red, green, and blue LEDs. When the camera captures an image, it shines a red LED and then uses image sensors to take the photo. It repeats the same process with green and blue LEDs.

Even though the image looks black and white, the red, green, and blue colored light is reflected in the white part of each photo, Akbar explains. When the image data are combined in post-processing, the color image can be reconstructed.

“When we were kids in art class, we were taught that we could make all colors using three basic colors. The same rules follow for color images we see on our computers. We just need red, green, and blue — these three channels — to construct color images,” he says.

Sending data with sound

Once image data are captured, they are encoded as bits (1s and 0s) and sent to a receiver one bit at a time using a process called underwater backscatter. The receiver transmits sound waves through the water to the camera, which acts as a mirror to reflect those waves. The camera either reflects a wave back to the receiver or changes its mirror to an absorber so that it does not reflect back.

A hydrophone next to the transmitter senses if a signal is reflected back from the camera. If it receives a signal, that is a bit-1, and if there is no signal, that is a bit-0. The system uses this binary information to reconstruct and post-process the image.

“This whole process, since it just requires a single switch to convert the device from a nonreflective state to a reflective state, consumes five orders of magnitude less power than typical underwater communications systems,” Afzal says.

The researchers tested the camera in several underwater environments. In one, they captured color images of plastic bottles floating in a New Hampshire pond. They were also able to take such high-quality photos of an African starfish that tiny tubercles along its arms were clearly visible. The device was also effective at repeatedly imaging the underwater plant Aponogeton ulvaceus in a dark environment over the course of a week to monitor its growth.

Now that they have demonstrated a working prototype, the researchers plan to enhance the device so it is practical for deployment in real-world settings. They want to increase the camera’s memory so it could capture photos in real-time, stream images, or even shoot underwater video.

They also want to extend the camera’s range. They successfully transmitted data 40 meters from the receiver, but pushing that range wider would enable the camera to be used in more underwater settings.

“This will open up great opportunities for research both in low-power IoT devices as well as underwater monitoring and research,” says Haitham Al-Hassanieh, an assistant professor of electrical and computer engineering at the University of Illinois Urbana-Champaign, who was not involved with this research.

This research is supported, in part, by the Office of Naval Research, the Sloan Research Fellowship, the National Science Foundation, the MIT Media Lab, and the Doherty Chair in Ocean Utilization.

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Understanding reality through algorithms

Although Fernanda De La Torre still has several years left in her graduate studies, she’s already dreaming big when it comes to what the future has in store for her.

“I dream of opening up a school one day where I could bring this world of understanding of cognition and perception into places that would never have contact with this,” she says.

It’s that kind of ambitious thinking that’s gotten De La Torre, a doctoral student in MIT's Department of Brain and Cognitive Sciences, to this point. A recent recipient of the prestigious Paul and Daisy Soros Fellowship for New Americans, De La Torre has found at MIT a supportive, creative research environment that’s allowed her to delve into the cutting-edge science of artificial intelligence. But she’s still driven by an innate curiosity about human imagination and a desire to bring that knowledge to the communities in which she grew up.

An unconventional path to neuroscience

De La Torre’s first exposure to neuroscience wasn’t in the classroom, but in her daily life. As a child, she watched her younger sister struggle with epilepsy. At 12, she crossed into the United States from Mexico illegally to reunite with her mother, exposing her to a whole new language and culture. Once in the States, she had to grapple with her mother’s shifting personality in the midst of an abusive relationship. “All of these different things I was seeing around me drove me to want to better understand how psychology works,” De La Torre says, “to understand how the mind works, and how it is that we can all be in the same environment and feel very different things.”

But finding an outlet for that intellectual curiosity was challenging. As an undocumented immigrant, her access to financial aid was limited. Her high school was also underfunded and lacked elective options. Mentors along the way, though, encouraged the aspiring scientist, and through a program at her school, she was able to take community college courses to fulfill basic educational requirements.

It took an inspiring amount of dedication to her education, but De La Torre made it to Kansas State University for her undergraduate studies, where she majored in computer science and math. At Kansas State, she was able to get her first real taste of research. “I was just fascinated by the questions they were asking and this entire space I hadn’t encountered,” says De La Torre of her experience working in a visual cognition lab and discovering the field of computational neuroscience.

Although Kansas State didn’t have a dedicated neuroscience program, her research experience in cognition led her to a machine learning lab led by William Hsu, a computer science professor. There, De La Torre became enamored by the possibilities of using computation to model the human brain. Hsu’s support also convinced her that a scientific career was a possibility. “He always made me feel like I was capable of tackling big questions,” she says fondly.

With the confidence imparted in her at Kansas State, De La Torre came to MIT in 2019 as a post-baccalaureate student in the lab of Tomaso Poggio, the Eugene McDermott Professor of Brain and Cognitive Sciences and an investigator at the McGovern Institute for Brain Research. With Poggio, also the director of the Center for Brains, Minds and Machines, De La Torre began working on deep-learning theory, an area of machine learning focused on how artificial neural networks modeled on the brain can learn to recognize patterns and learn.

“It’s a very interesting question because we’re starting to use them everywhere,” says De La Torre of neural networks, listing off examples from self-driving cars to medicine. “But, at the same time, we don’t fully understand how these networks can go from knowing nothing and just being a bunch of numbers to outputting things that make sense.”

Her experience as a post-bac was De La Torre’s first real opportunity to apply the technical computer skills she developed as an undergraduate to neuroscience. It was also the first time she could fully focus on research. “That was the first time that I had access to health insurance and a stable salary. That was, in itself, sort of life-changing,” she says. “But on the research side, it was very intimidating at first. I was anxious, and I wasn’t sure that I belonged here.”

Fortunately, De La Torre says she was able to overcome those insecurities, both through a growing unabashed enthusiasm for the field and through the support of Poggio and her other colleagues in MIT’s Department of Brain and Cognitive Sciences. When the opportunity came to apply to the department’s PhD program, she jumped on it. “It was just knowing these kinds of mentors are here and that they cared about their students,” says De La Torre of her decision to stay on at MIT for graduate studies. “That was really meaningful.”

Expanding notions of reality and imagination

In her two years so far in the graduate program, De La Torre’s work has expanded the understanding of neural networks and their applications to the study of the human brain. Working with Guangyu Robert Yang, an associate investigator at the McGovern Institute and an assistant professor in the departments of Brain and Cognitive Sciences and Electrical Engineering and Computer Sciences, she’s engaged in what she describes as more philosophical questions about how one develops a sense of self as an independent being. She’s interested in how that self-consciousness develops and why it might be useful.

De La Torre’s primary advisor, though, is Professor Josh McDermott, who leads the Laboratory for Computational Audition. With McDermott, De La Torre is attempting to understand how the brain integrates vision and sound. While combining sensory inputs may seem like a basic process, there are many unanswered questions about how our brains combine multiple signals into a coherent impression, or percept, of the world. Many of the questions are raised by audiovisual illusions in which what we hear changes what we see. For example, if one sees a video of two discs passing each other, but the clip contains the sound of a collision, the brain will perceive that the discs are bouncing off, rather than passing through each other. Given an ambiguous image, that simple auditory cue is all it takes to create a different perception of reality.

“There’s something interesting happening where our brains are receiving two signals telling us different things and, yet, we have to combine them somehow to make sense of the world,” she says.

De La Torre is using behavioral experiments to probe how the human brain makes sense of multisensory cues to construct a particular perception. To do so, she’s created various scenes of objects interacting in 3D space over different sounds, asking research participants to describe characteristics of the scene. For example, in one experiment, she combines visuals of a block moving across a surface at different speeds with various scraping sounds, asking participants to estimate how rough the surface is. Eventually she hopes to take the experiment into virtual reality, where participants will physically push blocks in response to how rough they perceive the surface to be, rather than just reporting on what they experience.

Once she’s collected data, she’ll move into the modeling phase of the research, evaluating whether multisensory neural networks perceive illusions the way humans do. “What we want to do is model exactly what’s happening,” says De La Torre. “How is it that we’re receiving these two signals, integrating them and, at the same time, using all of our prior knowledge and inferences of physics to really make sense of the world?”

Although her two strands of research with Yang and McDermott may seem distinct, she sees clear connections between the two. Both projects are about grasping what artificial neural networks are capable of and what they tell us about the brain. At a more fundamental level, she says that how the brain perceives the world from different sensory cues might be part of what gives people a sense of self. Sensory perception is about constructing a cohesive, unitary sense of the world from multiple sources of sensory data. Similarly, she argues, “the sense of self is really a combination of actions, plans, goals, emotions, all of these different things that are components of their own, but somehow create a unitary being.”

It's a fitting sentiment for De La Torre, who has been working to make sense of and integrate different aspects of her own life. Working in the Computational Audition lab, for example, she’s started experimenting with combining electronic music with folk music from her native Mexico, connecting her “two worlds,” as she says. Having the space to undertake those kinds of intellectual explorations, and colleagues who encourage it, is one of De La Torre’s favorite parts of MIT.

“Beyond professors, there’s also a lot of students whose way of thinking just amazes me,” she says. “I see a lot of goodness and excitement for science and a little bit of — it’s not nerdiness, but a love for very niche things — and I just kind of love that.”

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MIT welcomes the 2022 incoming graduate students

This year’s incoming cohort of new MIT graduate students enjoyed a warm welcome from the Graduate Student Council (GSC), with a number of in-person orientation activities from Aug. 21 through Sept. 6. The GSC has traditionally offered a broad range of in-person orientation activities to the entire incoming graduate cohort. Katie Chen, a graduate student in integrated design and management, served as orientation chair.

Graduate Orientation kicked off with a picnic on Sunday, Aug. 21. New students mingled, enjoying food and conversation in Killian Court, and even meeting a fellow grad’s corgi. 

On Sunday, Aug. 28, MIT President L. Rafael Reif hosted a welcome lunch for all of the incoming students, giving remarks and answering questions from graduate student moderators Chen and A.J. Miller, the GSC president. Chancellor Melissa Nobles was pleased to attend, along with Vice Chancellor and Dean for Student Life Suzy Nelson; Senior Associate Dean for Residential Education Judy Robinson; Senior Associate Dean and Director of the Office of Graduate Education Blanche Staton; Institute Community and Equity Officer John Dozier; and MIT mascot Tim the Beaver.

For the GSC Scavenger Hunt on Wednesday, Aug. 31, teams of graduate students ventured all over MIT’s campus in search of clues during a timed competition. Prizes were awarded for first, second, and third places, and for “Most Creative Photos.”

Numerous offices and groups presented information and swag to the incoming grad students at the Sept. 6 Graduate Resource and Activity Fair. Each graduate student received a lively red T-shirt sponsored by the MIT Coop.

In addition to these central offerings, departments and various offices hosted local programming across campus.

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