Experts join J-PAL North America in advancing conversation on the work of the future

On Jan. 14, J-PAL North America’s Work of the Future Initiative hosted an afternoon of conversation on how to address the changing nature of work while advancing equity and opportunity. The event, entitled Building A Future That Works For All, was attended by 35 leaders from nonprofits, academia, government, philanthropy, and advocacy organizations. 

“The assumption that we can solve these problems without workers in the conversation is one that we need to leave behind,” said Ai-jen Poo, co-founder and executive director of the National Domestic Workers Alliance, as she kicked off the first panel of the day. This theme was echoed throughout the day’s conversations, which were hosted by the Gerri and Rich Wong family at the Accel office in Palo Alto, California. Rich Wong is an alumnus of MIT engineering and the MIT Sloan School of Management. 

The event sought to continue J-PAL North America and the Work of the Future Initiative’s efforts to shift the conversations surrounding the future of work to focus on working people and collaborative research partnerships. As J-PAL North America Executive Director Mary Ann Bates stated in her introductory remarks: “We’re here to talk about the work of the future, which is about many big ideas — automation, artificial intelligence, and more — but we care about this work because of the people.” 

J-PAL North America launched the Work of the Future Initiative in April 2019 to identify effective, evidence-based strategies to increase opportunities, reduce disparities, and help all workers navigate and thrive in the labor markets of the future. 

Research partnerships are vital to generating the rigorous evidence necessary to identify these effective strategies. The recent event’s conversations sought to provide attendees with a chance to forge new partnerships and discuss innovative ideas for new programs and evaluations. 

The first panel discussed the role of rigorous research to inform worker-centered policies. Ai-jen Poo focused her discussion on the care sector — a workforce that will grow at five times the rate of any other sector in the coming years. Specifically, Poo noted the creative and innovative measures that the National Domestic Workers Alliance is taking to ensure that care work is dignified and that domestic workers are protected, including turning to technology: “What we’re trying to do is deploy technology to solve for dignity and equity.” 

Harvard professor and J-PAL North America Co-Scientific Director Lawrence Katz followed Poo’s remarks by discussing the growing divergence between real wages and worker productivity. Katz cited rising inequality as a primary driver of the decline in upward mobility and the stagnation of wages; more so than slow economic growth. 

Lastly, Aneesh Raman, senior advisor to California Governor Gavin Newsom, closed the conversation with a discussion on why collaboration across sectors and a willingness to innovate is crucial to progress: “We live in a world where politicians have very little opportunity to fail, which makes it very hard to innovate. We need to create a shared ownership of risk. Philanthropy, government, the private sector, and the nonprofit community need to come together to innovate and make a difference.” 

Other highlights of the day included a discussion of an ongoing research partnership between MIT Professor and Work of the Future Initiative Co-Chair David Autor, Rutgers University professor and J-PAL-affiliated researcher Amanda Agan, and Irene Liu and Jen Yeh of Checkr. 

Checkr is a selected partner through the Work of the Future Initiative’s inaugural innovation competition. The company partnered with Autor and Agan to evaluate whether their Positive Adjudication Matrix (PAM) can reduce bias in the background-check and hiring process. PAM allows employers to deem certain types of offenses irrelevant to the roles for which they’re hiring. Companies can then choose to either filter out or de-emphasize these criminal records. 

The candid conversation addressed the challenging aspects of partnering to design an evaluation and discussed what conditions must hold for more productive research partnerships to form in the future. Autor discussed the need for a champion within a partner organization, stating, “Data is threatening in the sense that it can produce results that you’re not looking for. You need a champion within your organization to move this forward.” 

The Checkr team expressed their hope that the evaluation of their product can inform policy decisions in the future: “There are states that have laws dictating who can and cannot apply to these companies. If we have evidence there, that can be really helpful.”

Other panelists, such as Katy Hamilton of the Center for Work Education and Employment and Jukay Hsu of Pursuit, run organizations that provide direct support to workers seeking quality jobs. Hamilton and Hsu discussed the programs that they hope to evaluate and turned to the audience for advice and constructive questions to inform their evaluation design processes. 

To wrap up the day, representatives from academia, philanthropy, the private sector, and government offered a call to action to other leaders within their sectors. Themes included centering workers’ voices and collaborating across sectors.  

Katy Knight of the Siegel Family Endowment discussed the steps that philanthropic organizations should take to promote people-centered practices: “We need to bring other people into the conversation and listen to their personal expertise to make sure we really understand the work we’re doing.” Mark Gorenberg of Zetta Venture Partners echoed these statements, stressing the private sector’s obligation to invest responsibly in programs that promote dignity. 

José Cisneros, elected treasurer for the City and County of San Francisco, discussed how collaboration is crucial for innovation: “The government is ready to be creative and work in partnership with philanthropy and the private sector to see if we can do things differently.” Columbia University professor and J-PAL-affiliated researcher Peter Bergman advocated for a similar type of collaboration within the academic community, calling for larger and more diverse research teams to conduct both quantitative and qualitative analyses of programs. 

The Work of the Future Initiative will continue to shape the dialogue surrounding the future of work by bringing together leaders and innovators across sectors to engage in conversations and research partnerships that center worker voices and concerns. By generating research on strategies to help workers thrive in today’s labor market, the initiative seeks to shape a more equitable future of work.

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A new facet for germanium

Although silicon is the workhorse of the semiconductor industry, forming the basis for computer chips, camera sensors, and other everyday electronic devices, researchers and manufacturers add other materials, such as germanium, to boost silicon chip processing speed, cut power consumption, and create new functions, such as photonic connections that use light instead of electrical current to transfer data.

Researchers have known for about a decade that dome-shaped empty spaces form in germanium when it is grown on top of silicon patterned with a dielectric material, such as silicon oxide or silicon nitride, that masks part of the silicon base. Now, MIT researchers have discovered a method to predict and control the length of tunnels in solid germanium by growing it on silicon oxide strips on top of silicon. These tunnels have potential to be used as light channels for silicon photonics or liquid channels for microfluidic devices.

“We found a tunnel or cavity on top of the silicon dioxide which is between the germanium and the silicon dioxide, and we can vary the length of the tunnel depending on the length of the oxide,” says Rui-Tao Wen, a former MIT postdoc and first author of a recent paper in Nano Letters. Wen is now an assistant professor of materials science and engineering at the Southern University of Science and Technology in Shenzhen, China.

The researchers used a two-step growth process, which first puts down a layer of germanium at a relatively lower temperature, then adds another germanium layer at a relatively higher temperature. The germanium layers have difficulty bonding directly to the silicon oxide strips. “The major discovery was that you form these cavities or tunnels, and they’re actually reconfiguring during growth or annealing,” says Jurgen Michel, Materials Research Laboratory senior research scientist and senior lecturer in the Department of Materials Science and Engineering. “The reconfiguration internally is a basic scientific phenomenon that I don’t think anybody would have expected.”

Evolving over time

During their experiments, which took a year to carry out, first author Wen analyzed cross-sections of the germanium-silicon oxide material with a transmission electron microscope (TEM), capturing images at multiple points in time during its formation. Before actually analyzing their results, the researchers expected that once tunnels formed they would stay the same shape throughout the process. Instead, they found a large amount of material is reconfigured within that space as the material evolves over time. “This is something that nobody has observed yet, that you can actually get this, what we call internal reconfiguration of material,” Michel says.

“So for instance, the tunnel gets larger, some of the connected material completely disappears, and the tunnel surfaces are perfect in terms that they are atomically flat,” Michel says. “They form actually what are called facets, which are certain crystallographic germanium orientations.”

The fine resolution that Wen obtained with TEM images unexpectedly showed these internal surfaces appear to have perfect surfaces. “Normally, if we do epitaxial growth of germanium on silicon, we will find very many dislocations,” Wen says. “There are none of those defects on top of the tunnels. It’s not like materials we used to have, which have a lot of dislocations in germanium layers. This one is a perfect single crystal.” Co-author Baoming Wang prepared the TEM samples. Wang is a postdoc in Professor Carl V. Thompson’s Materials for Micro and Nano Systems research group.

During the growth process, which is called selective epitaxy growth, a gas containing a compound of germanium and hydrogen (germane) flows into an ultra-high vacuum chemical vapor deposition chamber. At first, the germanium deposits on the silicon, then it slowly overgrows the silicon oxide strips, forming an archway-shaped tunnel centered directly over the oxide strips.

Wen patterned silicon oxide strips up to 2 centimeters in length (about three-quarters of an inch) on a 6-inch (about 15 cm) silicon wafer with tunnels covering the entire length of the strip. The strips themselves ranged in size from a width of 350 to 750 nanometers and lengths of 2 microns to 2 cm. The only limit to tunnel length appears to be the size of the silicon base layer, Michel suggests. “We see that the ends of that strip are partially covered with germanium, but then the tunnel length increases with strip length. And that’s a linear process,” he says.

Growth conditions

In these experiments, the pressure in the tunnels was about 10 millibars, which is about 100 times weaker than sea-level atmospheric pressure. Suggesting a mechanism for how the tunnels form, Michel explains that the germanium cannot form a stable germanium oxide directly on top of the silicon oxide in the high temperature, ultra-high vacuum environment, so the process slowly consumes the oxide. “You lose some of the oxide thickness during growth, but the area will stay clear,” he says. Rather than being empty, the tunnels are likely occupied by hydrogen gas, which is present because the germane gas separates into its germanium and hydrogen components.

Another surprising finding was that as the germanium spreads over the silicon oxide strips, it does so unevenly at first, covering the far ends of the strip and then moving toward the centers of the strips. But as this process continues, the uncovered area of the silicon oxide shrinks from an oval shape to a circle, after which the germanium evenly spreads over the remaining uncovered area.

“The effect of the length of the oxide stripe on tunnel formation is surprising and deserves further explanation, both for theoretical understanding and for possible applications,” says Ted Kamins, an adjunct professor of electrical engineering at Stanford University, who was not involved in this research. “The end effects might be useful for introducing liquids or gases into the tunnels. Overgrowth only from the ends of the oxide stripe is also unexpected for four-fold symmetric materials, such as Si (silicon) and Ge (germanium).”

“If controllable and reproducible, the technique might be applied to photonics, where an abrupt change of refractive index can help guide light, and to microfluidics integrated onto a silicon chip,” Kamins says.

“The results are absolutely fascinating and shocking — my jaw drops when going through the electron microscopy photos,” says Jifeng Liu, an associate professor of engineering at Dartmouth College, who was not involved in this research. “Imagine all the pillars in the middle of the Longfellow Bridge gradually and spontaneously migrate to the banks, and one day you find the entire bridge completely suspended in the middle! This would be analogous to what has been reported in this paper on microscopic scale.”

As a postdoc at MIT from 2007 to 2010, Liu worked on the first germanium laser and the first germanium-silicon electroabsorption modulator with Jurgen Michel and Lionel C. Kimerling, the Thomas Lord Professor of Materials Science and Engineering. At Dartmouth, Liu continues research on germanium and other materials such as germanium-tin compounds for photonic integration on silicon platforms.

“I hope these beautiful and shocking results also remind all of us about the central importance of hands-on experimental research and training, even in an emerging age of artificial intelligence and machine learning — you simply cannot calculate and predict everything, not even in a material growth process that has been studied for three decades,” Liu says.

Kamins notes that “This experimental study produced a significant amount of data that should be used to gain an understanding of the mechanisms. Then, the technique can be assessed for its practicality for applications.”

Michel notes that the although the findings about tunnel formation were demonstrated in a specific growth system of germanium on silicon using silicon oxide to pattern growth, these results also should apply to similar growth systems based on combinations of elements such as aluminum, gallium, and arsenic or indium and phosphorus that are called III-V semiconductor materials. “Any kind of growth system where you have this selective growth, you should be able to generate tunnels and voids,” Michel says.

Additional experiments will need to be carried out to see if this process can produce devices for microfluidics, photonics, or possibly passing light and liquid through together. “It’s a very first step toward applications,” Michel says.

This research was supported by the National Science Foundation.

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Maurice Fox, professor emeritus of biology, dies at 95

Maurice Sanford Fox, professor emeritus of biology and former head of the Department of Biology, passed away on Jan. 26 at the age of 95.

Fox was instrumental in creating and revising several courses within the biology major, and served as department head from 1985 to 1989. His research focused on bacterial genetics, and he pioneered investigations into bacterial transformation.

“Maury was a force in the department for many years,” says current department head Alan Grossman, the Praecis Professor of Biology. “He was very involved in the graduate program, and served as a mentor and friend to many of us. He cared deeply about the department, the scientific enterprise, and bioethics.”

Fox was born in the Bronx, New York, in 1924 to a family of poor Jewish immigrants; his father had fled Russia to avoid being conscripted into the tsar’s army. Growing up, Fox had little interest in science, and considered himself small for his age and “not very noticeable.” However, one teacher took an interest in him, and encouraged him to apply to Stuyvesant High School, which specialized in math and science. It took him an hour to make the commute each day, but he relished his biology and chemistry courses, where he got to study flies and flatworms and learn how to blow glass.

Fox graduated from high school at age 16 and enrolled in Queens College with the intent of majoring in chemistry. After a year and a half, he left to enlist in the U.S. Army Air Force and attend their meteorology program, eventually becoming a full-time meteorologist and traveling all over the American South to forecast weather for the military. At the time, he aspired to become a doctor, but didn’t have enough money for medical school. Instead, at age 22, he returned to Queens College to continue taking chemistry courses.

He went on to receive his PhD in chemistry from the University of Chicago, where he studied under Willard Libby and specialized in nuclear chemistry. Realizing he had no interest in nuclear weapons, Fox began scanning the bulletin boards at the University of Chicago for other opportunities post-graduation, and came across Leo Szilard’s lab. Szilard had discovered a chemical reaction, known as the “Szilard-Chalmers reaction,” which Fox had just used to complete his thesis in physical chemistry. Fox joined the lab and became fascinated with Szilard’s continuous-flow device, called a chemostat, used for growing hundreds of generations of bacteria under constant conditions. To Fox, the device was a new way to think about kinetics, which “treated living things like chemicals.”

Fox considered Szilard to be his most influential mentor, inspiring him both scientifically and personally. Szilard encouraged Fox to take biology classes, and Fox became increasingly enthralled by bacterial genetics — a subject he later taught in classes of his own.

Several years later, the two joined forces to establish the Council for a Livable World. Their plan was to create an organization that would raise money for senatorial candidates who would be “sensible” about nuclear weapons and avoid nuclear catastrophe. Fox felt this conviction to uphold the social and political responsibilities of being a researcher throughout his entire life. He fought to reduce the risks of radiation, biological warfare, and gene editing, and later went on to chair MIT’s Radiation Protection Committee, in addition to joining UNESCO’s International Bioethics Committee and the American Veterans Committee.

At the time that Fox and Szilard were building the Council for a Livable World, Fox was completing his postdoc with biochemist Rollin Hotchkiss at Rockefeller Institute for Medical Research — the country’s first biomedical institute — which later became Rockefeller University. After his postdoc, he rose through the ranks to become an associate professor before being recruited to MIT in 1962.

As a bacterial geneticist, Fox used bacterial transformation as an experimental model for genetic analysis to gain insights into mechanisms of genetic modification. He later extended his investigations to transduction and conjugation. Fox helped lay the foundation of our modern understanding of DNA mutation, recombination, and mismatch repair — efforts which directly and indirectly influenced key advancements like the search for RNA viruses and the discovery of the SOS response. He also had a keen interest in evaluating the effectiveness of medical procedures, including diagnosis and treatment of breast cancer. He was a member of the American Academy of Arts and Sciences, the National Academy of Sciences, and the National Academy of Medicine, among other prominent professional organizations.

Fox remained active in the Department of Biology for 34 years, retiring in 1996. During that time, he taught several Course 7 subjects and mentored graduate and undergraduate students, as well as postdocs.

Fox was among the founding generation of molecular biologists who migrated from the physical sciences, says David Botstein, one of Fox’s earliest trainees at MIT. He remembers Fox as both an intellectual mentor and a life coach. Fox befriended many and his house was always full of visitors, with whom he shared his love for science, culture, art, and politics. “Maury introduced me to the quantitative study of microorganisms and the importance of DNA mutation and recombination — which I had expected — but also to the rigorous and persistent skepticism that led me to constantly search for alternatives to the current thinking,” Botstein says. “In this way, Maury introduced me to an approach to science and learning that shaped my entire career.”

Michael Lichten PhD ’82 also credits Fox with teaching him how to think about science. “Maury taught as much by example as by direction, and he transmitted a deep and profound commitment to teaching that guides many of his students to this day,” he says.

"Maury was a colleague, a mentor, and, most importantly, a friend,” recalls H. Robert Horvitz, Nobel laureate and one of Fox’s former undergraduate students. “Maury truly helped shaped my life, from my undergraduate days as a student in his genetics class to many more recent days, when he always offered both warmth and wisdom.”

“This is a man who made an astonishing difference in an astonishing number of lives,” adds Evelyn Fox Keller, Fox’s sister and professor emerita of history and philosophy of science at MIT. “He made a difference to the world. His life was devoted to making the world a better place for people — and he did.”

Fox is survived by his three sons, Jonathan, Gregory, and Michael, and his sisters Evelyn and Frances, who is a professor emerita of political science at the Graduate Center, City University of New York. Fox was predeceased by his wife of more than 50 years, Sally. The Department of Biology will hold a memorial celebration of Fox’s life in the spring. 

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MIT helps first-time entrepreneur build food hospitality company

Christine Marcus MBA ’12 was an unlikely entrepreneur in 2011. That year, after spending her entire, 17-year career in government, most recently as the deputy chief financial officer for the U.S. Department of Energy, she entered the MIT Sloan School of Management Fellows MBA Program.

Moreover, Marcus didn’t think of herself as an entrepreneur.

“That was the furthest thing from my mind,” she says. “I knew it was time to think about the private sector, but my plan was to leave Sloan and get a job in finance. The thought of entrepreneurship was nowhere in my mind. I wasn’t one of those people who came with a business idea.”

By the end of Sloan’s intensive, 12-month program, however, Marcus was running a startup helping local organizations and companies serve food from some of Boston’s best restaurants to hundreds of people. Upon graduation, in addition to her degree, Marcus had 40 recurring customers and had sold about $50,000 worth of food from her classmates’ Italian restaurant.

What happened to spark such a dramatic change?

“MIT happened,” Marcus says. “Being in that ecosystem and listening to all the people share their stories of starting companies, listening to CEOs talk about their successes and failures, the mistakes they’ve made along the way, that was super-inspiring. What I realized at MIT was that I’ve always been an entrepreneur.”

In the years since graduation, Marcus has used her new perspective to build Alchemista, a “high-touch” hospitality company that helps businesses, commercial real estate developers, and property owners provide meals to employees and tenants. Today, Alchemista has clients in Boston, New York City, and Washington, and serves more than 60,000 meals each month.

The company’s services go beyond simply curating restaraunts on a website: Each one of Alchemista’s clients has its own representative that customizes menus each month, and Alchemista employees are on the scene setting up every meal to ensure everything goes smoothly.

“We work with companies that focus on employee culture and invest in their employees, and we incorporate ourselves into that culture,” Marcus says.

Finding inspiration, then confidence

At first, all Marcus wanted from MIT were some bright new employees for the Department of Energy. During a recruiting trip for that agency in 2011, she met Bill Aulet, the managing director of the Martin Trust Center for MIT Entrepreneurship and professor of the practice at Sloan.

“I mentioned to Bill that I was thinking of doing an MBA,” Marcus remembers. “He said, ‘You need to come to MIT. It will transform your life.’ Those were his exact words. Then basically, ‘And you need to do it now.’”

Soon after that conversation, Marcus applied for the Sloan Fellows Program, which crams an MBA into one year of full-time, hands on work. A few weeks after being accepted, she left her lifelong career in government for good.

But Marcus still had no plans to become an entrepreneur. That came more gradually at Sloan, as she listened to experts describe entrepreneurship as a learnable craft, received encouragement and advice from professors, and heard from dozens of successful first-time entrepreneurs about their own early doubts and failures.

“A lot of these founders had backgrounds in things that had nothing to do with their industry,” Marcus says. “My question was always, ‘How do you become successful in an industry you don’t know anything about?’ Their answer was always the same: ‘It’s all about learning and being curious.’”

During one typically long day in the MBA program, a classmate brought in food from his Italian restaurant. Marcus was blown away and wondered why MIT didn’t cater from nice restaurants like that all the time.

The thought set in motion a process that has never really stopped for Marcus. She began speaking with office secretaries, club presidents, and other event organizers at MIT. She learned it was a nightmare ordering food for hundreds of people, and that many of Boston’s best restaurants had no means of connecting with such organizers.

“I made myself known on campus just hustling,” Marcus remembers. “First I had to spend time figuring out who orders food. … I made it my mission to talk to all of them, understand their pain points, and understand what would get them to change their processes at that point. It was a lot of legwork.”

Marcus moved into the entrepreneurial track at Sloan, and says one of her most helpful classes was tech sales, taught by Lou Shipley, who’s now an advisor for Alchemista. She also says it was helpful that professors focused on real-world problems, at some points even using Alchemista as a case study, allowing Marcus’s entire class to weigh in on problems she was grappling with.

“That was super-helpful, to have all these smart MIT students working on my company,” she says.

As she neared gradation, Marcus spent a lot of time in the Trust Center, and leaned heavily on MIT’s support system.

“That’s the best thing about MIT: the ecosystem,” Marcus says. “Everybody genuinely wants to help however they can.”

Leaving that ecosystem, which Marcus described as a “challenging yet safe environment,” presented Marcus with her biggest test yet.

Taking the plunge

At some point, every entrepreneur must decide if they’re passionate and confident enough in their business to fully commit to it. Over the course of a whirlwind year, MIT gave Marcus a crash course in entrepreneurship, but it couldn’t make that decision for her.

Marcus responded unequivocally. She started by selling her house in Washington and renting a one-bedroom apartment in Boston. She also says she used up her retirement savings as she worked to expand Alchemista’s customer base in the early days.

“I’m not sure I would recommend it to anyone without a strong stomach, but I jumped in with both feet,” Marcus says.

And MIT never stopped lending support. At the time, Sloan was planning to renovate a building on campus, so in the interim, Aulet started a coworking space called the MIT Beehive. Marcus worked out of there for more than a year, collaborating with other MIT startup founders and establishing a supportive network of peers.

Her commitment paid off. By 2014, Marcus had a growing customer base and a strong business model based on recurring revenue from large customer accounts. Alchemista soon expanded to Washington and New York City.

Last year, the company brought on a culinary team and opened its own kitchens. It also expanded its services to commercial property owners and managers who don’t want to give up leasing space for a traditional cafeteria or don’t have restaurants nearby.

Marcus has also incorporated her passion for sustainability into Alchemista’s operations. After using palm leaf plates for years, the company recently switched over to reusable plates and utensils, saving over 100,000 tons of waste annually, she says.

Ultimately, Marcus thinks Alchemista’s success is a result of its human-centered approach to helping customers.

“It’s not this massive website where you place an order and have no contact,” Marcus says. “We’re the opposite of that. We’re high-touch because everyone else is a website or app. Simply put, we take all the headaches away from ordering for hundreds of people. Food is very personal; breaking bread is one of the most fundamental ways to connect with others. We provide that experience in a premium, elevated way.”

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Hospital rankings hold up

Given the complexities of health care, do basic statistics used to rank hospitals really work well? A study co-authored by MIT economists indicates that some fundamental metrics do, in fact, provide real insight about hospital quality.

“The results suggest a substantial improvement in health if you go to a hospital where the quality scores are higher,” says Joseph Doyle, an MIT economist and co-author of a new paper detailing the study’s results.

The study was designed to work around a difficult problem in evaluating hospital quality: Some high-performing hospitals may receive an above-average number of very sick patients. Accepting those difficult cases could, on the surface, worsen the aggregate outcomes of a given hospital’s patients and make such hospitals seem less effective than they are.

However, the scholars found a way to study equivalent pools of patients, thus allowing them to judge the hospitals in level terms. Overall, the study shows, when patient sickness levels are accounted for, hospitals that score well on quality measures have 30-day readmission rates that are 15 percent lower than a set of lesser-rated hospitals, and 30-day mortality rates that are 17 percent lower.

“It wasn’t clear going in whether these quality measures do a good job of sorting hospitals out,” Doyle adds. “These results suggest that they have predictive power.”

The paper, “Evaluating Measures of Hospital Quality: Evidence from Hospital Referral Patterns,” was written by Doyle, the Erwin H. Schell Professor of Management and Applied Economics at the MIT Sloan School of Management; John Graves, an assistant professor in the Department of Health Policy at Vanderbilt University; and Jonathan Gruber, the Ford Professor of Economics and associate department head of MIT’s Department of Economics. It appears in the latest issue of the Review of Economics and Statistics.

Randomized evaluations

To conduct the study, the researchers used a method that eliminates the issue of studying a skewed sample of admissions. They studied areas across the country where dispatchers’ calls are assigned randomly to different ambulance companies. Those ambulance companies tend to deliver patients to particular hospitals. Thus, otherwise similar groups of patients are admitted to different hospitals in what is essentially a random pattern; this allows outcomes to be compared among hospitals.

The patient data came primarily from Medicare claims made across the country during the period 2008-2012, and covered over 170,000 hospital admissions for patients who had just suffered a health event requiring “nondiscretionary” hospital admission. The patients also fit some basic criteria, such as not having previously been admitted recently for the same condition.

In addition to analyzing 30-day readmission and mortality rates, the researchers looked at patient satisfaction levels. All these criteria, and more, are commonly used in hospital assessments.

The researchers also found a 37 percent difference in one-year mortality, among highly-rated and lower-rated hospitals.

“I thought our results were reasonable,” says Doyle . “They’re not too big to be believed, but they suggest a substantial improvement in health if you go to a hospital where the quality scores are much higher.”

As the authors note in the paper, the subject is topical in the health policy world. Some lawmakers and experts want the hospital payment system to evolve in the direction of reimbursement for quality and oucomes, rather than treatment. As such, it is important to be able to tell if those quality measures are sturdy. 

“There’s been a lot of interest in whether these quality measures are informative or not, because there is a shift away from paying for the quantity of care provided to the quality of care provided,” Doyle says. “Most of the policymakers I’ve talked to want to use these quality measures.”

Management matters

Further research will be needed to help illuminate issues surrounding hospital quality in further depth. For instance, the current study is more focused on emergency care and not on care for chronic conditions; Doyle says that analysis of chronic care is “a fascinating question” that merits further investigation.

Doyle also acknowledges the need for further study to explain why certain hospitals fare better than others on basic quality measures. He notes that some were historically quicker than others to adopt what are now almost universal practices — the allotment of blood-thinning drugs to heart patients, for instance — and suggests the rate of adoption of new practices is an important factor in this area.

“Coming from a management school, we see that a lot of the variation in outcomes stems in large part from differences in management,” Doyle says. “Do you have the right procedures in places so that it’s easy for providers to do what the guidelines suggest? Improving management could yield big improvements in patient health.”

The research was supported by the National Institutes of Health.

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Giving cryptocurrency users more bang for their buck

A new cryptocurrency-routing scheme co-invented by MIT researchers can boost the efficiency — and, ultimately, profits — of certain networks designed to speed up notoriously slow blockchain transactions.  

Cryptocurrencies hold promise for peer-to-peer financial transactions, potentially making banks and credit cards obsolete. But there’s a scalability issue: Bitcoin, for instance, processes only a handful of transactions per second, while major credit cards process hundreds or thousands. That’s because the blockchain — the digital ledger cryptocurrencies are built on — takes a really long time to process transactions. 

A new solution is “payment channel networks” (PCNs), where transactions are completed with minimal involvement from the blockchain. Pairs of PCN users form off-blockchain escrow accounts with a dedicated amount of money, forming a large, interconnected network of joint accounts. Users route payments through these  accounts, only pinging the blockchain to establish and close the accounts, which speeds things up dramatically. Accounts can also collect a tiny fee when transactions get routed through them.

Inefficient routing schemes, however, slow down even these fast solutions. They deplete users’ balances in these accounts frequently, forcing them to invest a lot of money in each account or frequently rebalance their accounts on the blockchain. In a paper being presented next month at the USENIX Symposium on Networked Systems Design and Implementation, the researchers introduce “Spider,” a more efficient routing scheme that lets users invest only a fraction of funds in each account and process roughly four times more transactions before rebalancing on the blockchain.

“It’s important to have balanced, high-throughput routing in PCNs to ensure the money that users put into joint accounts is used efficiently,” says first author Vibhaalakshmi Sivaraman, a graduate student in the Computer Science and Artificial Intelligence Laboratory (CSAIL). “This should be efficient and a lucrative business. That means routing as many transactions as possible, with as little funds as possible, to give PCNs the best bang for their buck.”

Joining Sivaraman on the paper are former postdoc Shaileshh Bojja Venkatakrishnan, CSAIL graduate students Parimarjan Negi and Lei Yang, and Mohammad Alizadeh, an associate professor of electrical engineering and computer science and a CSAIL researcher; Radhika Mittal of the University of Illinois at Urbana-Champaign; and Kathleen Ruan and Giulia Fanti of Carnegie Mellon University.

Packet payments

PCNs rely heavily on bidirectional joint accounts — where both parties can receive and send money — so money can be routed between any users. User B can have a joint account with user A, while also linking separately to user C. Users A and C are not directly connected, but user A can send money to user C via the A-B and B-C joint accounts.

To exchange funds, each party must approve and update the balances in their joint accounts. Payments can only be routed on channels with sufficient funds to handle the transactions, causing major issues.

Traditional schemes send transactions along the shortest path possible, without being aware of any given user’s balance or the rate of sending on that account. This can cause one of the users in the joint account to handle too many transactions and drop to a zero balance, making it unable to route further transactions. What’s more, users can only send a payment in full. If a user wants to send, say, 10 bitcoins, current schemes try to push the full amount on the shortest path possible. If that path can’t support all 10 bitcoins at once, they’ll search for the next shortest path, and so on — which can slow down or completely fail the transaction.

Inspired by a technique for internet communications called packet switching, Spider splits each full transaction into smaller “packets” that are sent across different channels at different rates. This lets the scheme route chunks of these large payments through potentially low-funded accounts. Each packet is then far more likely to reach its destination without slowing down the network or being rejected in any given account for its size.

“Shortest-path routing can cause imbalances between accounts that deplete key payment channels and paralyze the system,” Sivaraman says. “Routing money in a way that the funds of both users in each joint account are balanced allows us to reuse the same initial funds to support as many transactions as possible.”

All queued up

Another innovation was creating queues at congested accounts. If an account can’t handle incoming transactions that require it to send money, instead of rejecting them, it queues them up. Then, it waits for any transactions that will replenish its funds — within a reasonable time frame — to be able to process those transactions.

“If you’re waiting on a queue, but I send you funds within the next second, you can then use any of those funds to send your waiting transactions,” Sivaraman says.

The researchers also adopted an algorithm — built by Alizadeh and other researchers — that monitors data center congestion to identify queueing delays at congested accounts. This helps control the rate of transactions. Say user A sends funds to user C through user B, which has a long queue. The receiver C sends the sender A, along with the payment confirmation, one bit of information representing the transaction’s wait time at user B. If it’s too long, user A routes fewer transactions through user B. As the queueing time decreases, account A routes more transactions through B. In this manner, by monitoring the queues alone, Spider is able to ensure that the rate of transactions is both balanced and as high as possible.

Ultimately, the more balanced the routing of PCNs, the smaller the capacity required — meaning, overall funds across all joint accounts — for high transaction throughput. In PCN simulations, Spider processed 95 percent of all transactions using only 25 percent of the capacity needed in traditional schemes.

The researchers also ran tests on tricky transactions called “DAGs,” which are one-directional payments where one user inevitably runs out of funds and needs to rebalance on the blockchain. A key metric for the performance of PCNs on DAG transactions is the number of off-chain transactions enabled for each transaction on the blockchain. In this regard, Spider is able to process eight times as many off-chain transactions for each transaction on-chain. In contrast, traditional schemes only support twice as many off-chain transactions.

“Even with extremely frequent rebalancing, traditional schemes can’t process all DAG transactions. But with very low-frequency rebalancing, Spider can complete them all,” Sivaraman says.

Next, the researchers are making Spider more robust to DAG transactions, which can cause bottlenecks. They’re also exploring data privacy issues and ways to incentivize users to use Spider.

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Genetic screen offers new drug targets for Huntington’s disease

Using a type of genetic screen that had previously been impossible in the mammalian brain, MIT neuroscientists have identified hundreds of genes that are necessary for neuron survival. They also used the same approach to identify genes that protect against the toxic effects of a mutant protein that causes Huntington’s disease.

These efforts yielded at least one promising drug target for Huntington’s: a family of genes that may normally help cells to break down the mutated huntingtin protein before it can aggregate and form the clumps seen in the brains of Huntington’s patients.

“These genes had never been linked to Huntington’s disease processes before. When we saw them, that was very exciting because we found not only one gene, but actually several of the same family, and also we saw them have an effect across two models of Huntington’s disease,” says Myriam Heiman, an associate professor of neuroscience in the Department of Brain and Cognitive Sciences and the senior author of the study.

The researchers’ new screening technique, which allowed them to assess all of the roughly 22,000 genes found in the mouse brain, could also be applied to other neurological disorders, including Alzheimer’s and Parkinson’s diseases, says Heiman, who is also a member of MIT’s Picower Institute for Learning and Memory and the Broad Institute of MIT and Harvard.

Broad Institute postdoc Mary Wertz is the lead author of the paper, which appears today in Neuron.

Genome-wide screen

For many decades, biologists have been performing screens in which they systematically knock out individual genes in model organisms such as mice, fruit flies, and the worm C. elegans, then observe the effects on cell survival. However, such screens have never been done in the mouse brain. One major reason for this is that delivering the molecular machinery required for these genetic manipulations is more difficult in the brain than elsewhere in the body.

“These unbiased genetic screens are very powerful, but the technical difficulty of doing it in the central nervous system at a genome-wide scale has never been overcome,” Heiman says.

In recent years, researchers at the Broad Institute have developed libraries of genetic material that can be used to turn off the expression of every gene found in the mouse genome. One of these libraries is based on short hairpin RNA (shRNA), which interferes with the messenger RNA that carries a particular gene’s information. Another makes use of CRISPR, a technique that can disrupt or delete specific genes in a cell. These libraries are delivered by viruses, each of which carry one element that targets a single gene.

The libraries were designed so that each of the approximately 22,000 mouse genes is targeted by four or five shRNAs or CRISPR components, so 80,000 to 100,000 viruses need to make it into the brain to ensure that all genes are hit at least once. The MIT team came up with a way to make their solution of viruses highly concentrated, and to inject them directly into the striatum of the brain. Using this approach, they were able to deliver one of the shRNA or CRISPR elements to about 25 percent of all of the cells in the striatum.

The researchers focused on the striatum, which is involved in regulating motor control, cognition, and emotion, because it is the brain region most affected by Huntington’s disease. It is also involved in Parkinson’s disease, as well as autism and drug addiction.

About seven months after the injection, the researchers sequenced all of the genomic DNA in the targeted striatal neurons. Their approach is based on the idea that if particular genes are necessary for neurons’ survival, any cell with those genes knocked out will die. Then, those shRNAs or CRISPR elements will be found at lower rates in the total population of cells.

The study turned up many genes that are necessary for any cell to survive, such as enzymes involved in cell metabolism or copying DNA into RNA. The findings also revealed genes that had been identified in previous studies of fruit flies and worms as being important for neuron function, such as genes involved the function of synapses (structures that allow neurons to communicate with each other).

However, a novel finding of this study was the identification of genes that hadn’t been linked to neuron survival before, Heiman says. Many of those were genes that code for metabolic proteins that are essential in cells that burn a lot of energy.

“What we interpret this to mean is that neurons in the mammalian brain are much more metabolically active and have a much higher dependency on these processes than for example, a neuron in C. elegans,” Heiman says.

William Yang, a professor of psychiatry and biobehavioral sciences at the University of California at Los Angeles, calls the new screening technique “a giant leap forward” for the field of brain research.

“Prior to this, people really could study the molecular function of genes gene-by-gene, or maybe a few genes at a time. This is a groundbreaking study because it demonstrates that you can perform genome-wide genetic screening in the mammalian central nervous system,” says Yang, who was not involved in the study.

Promising targets

The researchers then performed the same type of screen on two different mouse models of Huntington’s disease. These mouse models express the mutated form of the huntingtin protein, which forms clumps in the brains of Huntington’s patients. In this case, the researchers compared the results from the screen of the Huntington’s mice to normal mice. If any of the shRNA or CRISPR elements were found less frequently in the Huntington’s mice, that would suggest that those elements targeted genes that are helping to make cells more resistant to the toxic effects of the huntingtin protein, Heiman says.

One promising drug target that emerged from this screen is the Nme gene family, which has previously been linked to cancer metastasis, but not Huntington’s disease. The MIT team found that one of these genes, Nme1, regulates the expression of other genes that are involved in the proper disposal of proteins. The researchers hypothesize that without Nme1, these genes don’t get turned on as highly, allowing huntingtin to accumulate in the brain. They also showed that when Nme1 is overexpressed in the mouse models of Huntington’s, the Huntington’s symptoms appear to improve.

Although this gene hasn’t been linked to Huntington’s before, there have already been some efforts to develop compounds that target it, for use in treating cancer, Heiman says.

“This is very exciting to us because it’s theoretically a druggable compound,” she says. “If we can increase its activity with a small molecule, perhaps we can replicate the effect of genetic overexpression.”

The research was funded by the National Institutes of Health/National Institute of Neurological Disorders and Stroke, the JPB Foundation, the Bev Hartig Huntington’s Disease Foundation, a Fay/Frank Seed Award from the Brain Research Foundation, the Jeptha H. and Emily V. Wade Award, and the Hereditary Disease Foundation.

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Mehtaab Sawhney named 2020 Churchill Scholar

Mehtaab Sawhney, a senior from Commack, New York, has been named a 2020 Churchill Scholar and will pursue a year of graduate studies at Cambridge University in the U.K. Sawhney will graduate this February with a BS in mathematics and a minor in computer science. At Cambridge, he will undertake Part III of the Mathematics Tripos master’s degree before returning to the U.S. to enroll in a mathematics PhD program. He aspires to become a professor of mathematics specializing in combinatorics.

Sawhney completed his first year of undergraduate studies at the University of Pennsylvania and then transferred to MIT. At MIT, he has contributed to more than a dozen published or submitted academic papers, a rare feat for an undergraduate student. The majority of his research has been done in combinatorics under the tutelage of Professor Yufei Zhao in the MIT Department of Mathematics.

“Mehtaab is an incredibly talented and energetic mathematician,” states Zhao. “I constantly learn so much from talking to him. Working with Mehtaab on research has been one of the most fun and rewarding activities that I have done since joining MIT as a faculty member.”

Sawhney began his impressive rise in mathematics in high school, where he was a participant in the United States Mathematical Olympiad. He found the activity of solving problems fascinating. In high school, he got his first real taste of research through the MIT Primes-USA Program, which pairs high school students with graduate students to solve problems collectively but remotely. Here he first encountered combinatorics, an area of mathematics that focuses on counting.

Sawhney continued to work on math problems in the Math Olympiad, International Science and Engineering Fair, and then eventually the Putnam Mathematical Competition (where he was an honorable mention in both 2016 and 2018). He volunteers his time with the U.S. Mathematical Olympiad and the U.S. Team Selection Test as a grader and reviewer.

The Churchill Scholarship provides funding to American students for a year of master’s study at Cambridge University, based at Churchill College. The program was set up at the request of former British Prime Minister Winston Churchill to honor his vision of U.S.-U.K. scientific exchange. The Churchill Foundation annually awards scholarships to 15 American students for study in science, mathematics, or engineering. MIT nominates two candidates each year. MIT students interested in learning more about applying for the Churchill Scholarship, and other distinguished fellowships, should contact Kimberly Benard, assistant dean of Career Advising and Professional Development.

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Researchers discover a new way to control infrared light

In the 1950s, the field of electronics began to change when the transistor replaced vacuum tubes in computers. The change, which entailed replacing large and slow components with small and fast ones, was a catalyst for the enduring trend of miniaturization in computer design. No such revolution has yet hit the field of infrared optics, which remains reliant on bulky moving parts that preclude building small systems.

However, a team of researchers at MIT Lincoln Laboratory, together with Professor Juejun Hu and graduate students from MIT's Department of Materials Science and Engineering, is devising a way to control infrared light by using phase-change materials instead of moving parts. These materials have the ability to change their optical properties when energy is added to them.

“There are multiple possible ways where this material can enable new photonic devices that impact people’s lives,” says Hu. “For example, it can be useful for energy-efficient optical switches, which can improve network speed and reduce power consumption of internet data centers. It can enable reconfigurable meta-optical devices, such as compact, flat infrared zoom lenses without mechanical moving parts. It can also lead to new computing systems, which can make machine learning faster and more power-efficient compared to current solutions.”

A fundamental property of phase-change materials is that they can change how fast light travels through them (the refractive index). “There are already ways to modulate light using a refractive index change, but phase-change materials can change almost 1,000 times better,” says Jeffrey Chou, a team member formerly in the laboratory's Advanced Materials and Microsystems Group.

The team successfully controlled infrared light in multiple systems by using a new class of phase-change material containing the elements germanium, antimony, selenium, and tellurium, collectively known as GSST. This work is discussed in a paper published in Nature Communications.

A phase-change material's magic occurs in the chemical bonds that tie its atoms together. In one phase state, the material is crystalline, with its atoms arranged in an organized pattern. This state can be changed by applying a short, high-temperature spike of thermal energy to the material, causing the bonds in the crystal to break down and then reform in a more random, or amorphous, pattern. To change the material back to the crystalline state, a long- and medium-temperature pulse of thermal energy is applied.

“This changing of the chemical bonds allows for different optical properties to emerge, similar to the differences between coal (amorphous) and diamond (crystalline),” says Christopher Roberts, another Lincoln Laboratory member of the research team. “While both materials are mostly carbon, they have vastly different optical properties.”

Currently, phase-change materials are used for industry applications, such as Blu-ray technology and rewritable DVDs, because their properties are useful for storing and erasing a large amount of information. But so far, no one has used them in infrared optics because they tend to be transparent in one state and opaque in the other. (Think of the diamond, which light can pass through, and coal, which light cannot penetrate.) If light cannot pass through one of the states, then that light cannot be adequately controlled for a range of uses; instead, a system would only be able to work like an on/off switch, allowing light to either pass through the material or not pass through at all.

However, the research team found that that by adding the element selenium to the original material (called GST), the material's absorption of infrared light in the crystalline phase decreased dramatically — in essence, changing it from an opaque coal-like material to a more transparent diamond-like one. What's more, the large difference in the refractive index of the two states affects the propagation of light through them.

“This change in refractive index, without introducing optical loss, allows for the design of devices that control infrared light without the need for mechanical parts,” Roberts says.

As an example, imagine a laser beam that is pointing in one direction and needs to be changed to another. In current systems, a large mechanical gimbal would physically move a lens to steer the beam to another position. A thin-film lens made of GSST would be able change positions by electrically reprogramming the phase-change materials, enabling beam steering with no moving parts.

The team has already tested the material successfully in a moving lens. They have also demonstrated its use in infrared hyperspectral imaging, which is used to analyze images for hidden objects or information, and in a fast optical shutter that was able to close in nanoseconds.

The potential uses for GSST are vast, and an ultimate goal for the team is to design reconfigurable optical chips, lenses, and filters, which currently must be rebuilt from scratch each time a change is required. Once the team is ready to move the material beyond the research phase, it should be fairly easy to transition it into the commercial space. Because it's already compatible with standard microelectronic fabrication processes, GSST components could be made at a low cost and in large numbers.

Recently, the laboratory obtained a combinatorial sputtering chamber — a state-of-the-art machine that allows researchers to create custom materials out of individual elements. The team will use this chamber to further optimize the materials for improved reliability and switching speeds, as well as for low-power applications. They also plan to experiment with other materials that may prove useful in controlling visible light.

The next steps for the team are to look closely into real-world applications of GSST and understand what those systems need in terms of power, size, switching speed, and optical contrast.

“The impact [of this research] is twofold,” Hu says. "Phase-change materials offer a dramatically enhanced refractive index change compared to other physical effects — induced by electric field or temperature change, for instance — thereby enabling extremely compact reprogrammable optical devices and circuits. Our demonstration of bistate optical transparency in these materials is also significant in that we can now create high-performance infrared components with minimal optical loss.” The new material, Hu continues, is expected to open up an entirely new design space in the field of infrared optics.

This research was supported with funding from the laboratory's Technology Office and the U.S. Defense Advanced Research Projects Agency.

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At halfway point, SuperUROP scholars share their research results

MIT undergraduates are rolling up their sleeves to address major problems in the world, conducting research on topics ranging from nursing care to money laundering to the spread of misinformation about climate change — work highlighted at the most recent SuperUROP Showcase.

The event, which took place on the Charles M. Vest Student Street in the Stata Center in December 2019, marked the halfway point in the Advanced Undergraduate Research Opportunities Program (better known as “SuperUROP”). The yearlong program gives MIT students firsthand experience in conducting research with close faculty mentorship. Many participants receive scholar titles recognizing the program’s industry sponsors, individual donors, and other contributors.

This year, 102 students participated in SuperUROP, with many of their projects focused on applying computer science technologies, such as machine learning, to challenges in fields ranging from robotics to health care. Almost all presented posters of their work at the December showcase, explaining research to fellow students, faculty members, alumni, sponsors, and other guests.

“Every year, this program gets more and more impressive,” says Anantha P. Chandrakasan, dean of the School of Engineering and Vannevar Bush Professor of Electrical Engineering and Computer Science. “What’s especially noteworthy is the incredible breadth of projects and how articulate students are in talking about their work. Their presentation skills seem pretty remarkable.”

SuperUROP, administered by the Department of Electrical Engineering and Computer Science (EECS), includes a two-term course, 6.UAR (Undergraduate Advanced Research), designed to teach students research skills, including how to design an experiment and communicate results.

“What’s different about SuperUROP [compared to other research opportunities offered to undergraduates] is the companion class that guides you through the necessary writing and speaking,” says Anis Ehsani, a senior majoring in EECS and mathematics, whose project centered on the geometry of drawing political districts. “If I want to pursue a research career, it’s nice to have those skills,” adds Ehsani, an MIT EECS/Nutanix SuperUROP scholar.

Beyond the lab and classroom

Participants present their work at showcases in the fall and spring, and they are expected to produce prototypes or publication-worthy results by the end of the year.

“All these presentations help keep us on track with our projects,” says Weitung Chen, an EECS junior whose project focuses on automating excavation for mining applications. He explains that the inspiration for his SuperUROP work was a real-world problem he faced when trying to build a startup in automated food preparation. Scooping tofu, it turns out, is surprisingly difficult to automate. At the showcase, Chen — an MIT EECS/Angle SuperUROP scholar — explained that he is trying to create a simulation than can be used to train machines to scoop materials autonomously. “I feel really accomplished having this poster and presentation,” he said.

Launched by EECS in 2012, SuperUROP has expanded across the Institute over the past several years.

Adam Berinsky, the Mitsui Professor of Political Science, is working with SuperUROP students for the first time this year, an experience he’s enjoying. “What’s really cool is being able to give undergraduates firsthand experience in real research,” he says. He’s been able to tap students for the computer science skills he needs for his work, while providing them with a deep dive into the social sciences.

Madeline Abrahams, an MIT/Tang Family FinTech SuperUROP scholar, says she especially appreciates the program’s flexibility: “I could explore my interdisciplinary interests,” she says. A computer science and engineering major who is also passionate about political science, Abrahams is working with Berinsky to investigate the spread of misinformation related to climate change via algorithmic aggregation platforms.

Nicholas Bonaker also enjoyed the freedom of pursuing his SuperUROP project. “I’ve been able to take the research in the direction I want,” says Bonaker, a junior in EECS, who has developed a new algorithm he hopes will improve an assistive technology developed by his advisor, EECS Associate Professor Tamara Broderick.

Exploring new directions in health care

Bonaker said he particularly values the health-care focus of his project, which centers on creating better communications software for people living with severe motor impairments. “It feels like I’m doing something that can help people — using things I learned in class,” says Bonaker. He is among this year’s MIT EECS/CS+HASS SuperUROP scholars, whose projects combine computer science with the humanities, arts, or social sciences.  

Many of this year’s SuperUROP students are working on health-care applications. For example, Fatima Gunter-Rahman, a junior in EECS and biology, is examining Alzheimer’s data, and Sabrina Liu, an EECS junior and MIT EECS/Takeda SUperUROP scholar, is investigating noninvasive ways to monitor the heartrates of dental patients. Justin Lim, a senior math major, is using data analytics to try to determine the optimal treatment for chronic diseases like diabetes. “I like the feeling that my work would have real-world impact,” says Lim, an MIT EECS/Hewlett Foundation SuperUROP scholar. “It’s been very satisfying.”

Dhamanpreet Kaur, a junior majoring in math and computer science and molecular biology, is using machine learning to determine the characteristics of patients who are readmitted to hospitals following their discharge to skilled nursing facilities. The work aims to predict who might benefit most from expensive telehealth systems that enable clinicians to monitor patients remotely. The project has given Kaur the chance to work with a multidisciplinary team of professors and doctors. “I find that aspect fascinating,” says Kaur, also an MIT EECS/Takeda SuperUROP scholar.

As attendees bustled through the two-hour December showcase, some of the most enthusiastic visitors were industry sponsors, including Larry Bair ’84, SM ’86, a director at Advanced Micro Devices. “I’m always amazed at what undergraduates are doing,” he says, noting that his company has been sponsoring SuperUROPs for the last few years.

“It’s always interesting to see what’s going on at MIT,” says Tom O’Dwyer, an MIT research affiliate and the former director of technology at Analog Devices, another industry sponsor. O’Dwyer notes that supporting SuperUROP can help companies with recruitment. “The whole high-tech business runs on smart people,” he says. “SuperUROPs can lead to internships and employment.”

SuperUROP also exposes students to the work of academia, which can underscore a key difference between classwork and research: Research results are unpredictable.

Junior math major Lior Hirschfeld, for example, compared the effectiveness of different machine learning methods used to test molecules for potential in drug development. “None of them performed exceptionally well,” he says.

That might appear to be a poor result, but Hirschfeld notes that it’s important information for those who are using and trusting those tests today. “It shows you may not always know where you are going when you start a project,” says Hirschfeld, also an MIT EECS/Takeda SuperUROP scholar.

EECS senior Kenneth Acquah had a similar experience with his SuperUROP project, which focuses on finding a technological way to combat money laundering with Bitcoin. “We’ve tried a bunch of things but mostly found out what doesn’t work,” he says.

Still, Acquah says, he values the SuperUROP experience, including the chance to work in MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL). "I get a lot more supervision, more one-on-one time with my mentor," the MIT/EECS Tang Family FinTech SuperUROP scholar says. "And working in CSAIL has given me access to state-of-the-art materials."

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Engineers design bionic “heart” for testing prosthetic valves, other cardiac devices

As the geriatric population is expected to balloon in the coming decade, so too will rates of heart disease in the United States. The demand for prosthetic heart valves and other cardiac devices — a market that is valued at more than $5 billion dollars today — is predicted to rise by almost 13 percent in the next six years.

Prosthetic valves are designed to mimic a real, healthy heart valve in helping to circulate blood through the body. However, many of them have issues such as leakage around the valve, and engineers working to improve these designs must test them repeatedly, first in simple benchtop simulators, then in animal subjects, before reaching human trials — an arduous and expensive process.

Now engineers at MIT and elsewhere have developed a bionic “heart” that offers a more realistic model for testing out artificial valves and other cardiac devices.

The device is a real biological heart whose tough muscle tissue has been replaced with a soft robotic matrix of artificial heart muscles, resembling bubble wrap. The orientation of the artificial muscles mimics the pattern of the heart’s natural muscle fibers, in such a way that when the researchers remotely inflate the bubbles, they act together to squeeze and twist the inner heart, similar to the way a real, whole heart beats and pumps blood.

With this new design, which they call a “biorobotic hybrid heart,” the researchers envision that device designers and engineers could iterate and fine-tune designs more quickly by testing on the biohybrid heart, significantly reducing the cost of cardiac device development.

“Regulatory testing of cardiac devices requires many fatigue tests and animal tests,” says Ellen Roche, assistant professor of mechanical engineering at MIT. “[The new device] could realistically represent what happens in a real heart, to reduce the amount of animal testing or iterate the design more quickly.”

Roche and her colleagues have published their results today in the journal Science Robotics. Her co-authors are lead author and MIT graduate student Clara Park, along with Yiling Fan, Gregor Hager, Hyunwoo Yuk, Manisha Singh, Allison Rojas, and Xuanhe Zhao at MIT, along with collaborators from Nanyang Technology University, the Royal College of Surgeons in Dublin, Boston’s Children’s Hospital, Harvard Medical School, and Massachusetts General Hospital.

The structure of the biorobotic hybrid heart under magnetic resonance imaging. Credit: Christopher T. Nguyen

“Mechanics of the heart”

Before coming to MIT, Roche worked briefly in the biomedical industry, helping to test cardiac devices on artificial heart models in the lab.

“At the time I didn’t feel any of these benchtop setups were representative of both the anatomy and the physiological biomechanics of the heart,” Roche recalls. “There was an unmet need in terms of device testing.”

In separate research as part of her doctoral work at Harvard University, she developed a soft, robotic, implantable sleeve, designed to wrap around a whole, live heart, to help it pump blood in patients suffering from heart failure.

At MIT, she and Park wondered if they could combine the two research avenues, to develop a hybrid heart: a heart that is made partly of chemically preserved, explanted heart tissue and partly of soft artificial actuators that help the heart pump blood. Such a model, they proposed, should be a more realistic and durable environment in which to test cardiac devices, compared with models that are either entirely artificial but do not capture the heart’s complex anatomy, or are made from a real explanted heart, requiring highly controlled conditions to keep the tissue alive.

The team briefly considered wrapping a whole, explanted heart in a soft robotic sleeve, similar to Roche’s previous work, but realized the heart’s outer muscle tissue, the myocardium, quickly stiffened when removed from the body. Any robotic contraction by the sleeve would fail to translate sufficiently to the heart within.

Instead, the team looked for ways to design a soft robotic matrix to replace the heart’s natural muscle tissue, in both material and function. They decided to try out their idea first on the heart’s left ventricle, one of four chambers in the heart, which pumps blood to the rest of the body, while the right ventricle uses less force to pump blood to the lungs.

“The left ventricle is the harder one to recreate given its higher operating pressures, and we like to start with the hard challenges,” Roche says.

The heart, unfurled

The heart normally pumps blood by squeezing and twisting, a complex combination of motions that is a result of the alignment of muscle fibers along the outer myocardium that covers each of the heart’s ventricles. The team planned to fabricate a matrix of artificial muscles resembling inflatable bubbles, aligned in the orientations of the natural cardiac muscle. But copying these patterns by studying a ventricle’s three-dimensional geometry proved extremely challenging.

They eventually came across the helical ventricular myocardial band theory, the idea that cardiac muscle is essentially a large helical band that wraps around each of the heart’s ventricles. This theory is still a subject of debate by some researchers, but Roche and her colleagues took it as inspiration for their design. Instead of trying to copy the left ventricle’s muscle fiber orientation from a 3D perspective, the team decided to remove the ventricle’s outer muscle tissue and unwrap it to form a long, flat band — a geometry that should be far easier to recreate. In this case, they used the cardiac tissue from an explanted pig heart.

In collaboration with co-lead author Chris Nguyen at MGH, the researchers used diffusion tensor imaging, an advanced technique that typically tracks how water flows through white matter in the brain, to map the microscopic fiber orientations of a left ventricle’s unfurled, two-dimensional muscle band. They then fabricated a matrix of artificial muscle fibers made from thin air tubes, each connected to a series of inflatable pockets, or bubbles, the orientation of which they patterned after the imaged muscle fibers.

Motion of the biorobotic hybrid heart mimics the pumping motion of the heart under echocardiography. Credit: Mossab Saeed

The soft matrix consists of two layers of silicone, with a water-soluble layer between them to prevent the layers from sticking, as well as two layers of laser-cut paper, which ensures that the bubbles inflate in a specific orientation.

The researchers also developed a new type of bioadhesive to glue the bubble wrap to the ventricle’s real, intracardiac tissue. While adhesives exist for bonding biological tissues to each other, and and for materials like silicone to each other, the team  realized few soft adhesives do an adequate job of gluing together biological tissue with synthetic materials, silicone in particular.

So Roche collaborated with Zhao, associate professor of mechanical engineering at MIT, who specializes in developing hydrogel-based adhesives. The new adhesive, named TissueSil, was made by functionalizing silicone in a chemical cross-linking process, to bond with components in heart tissue. The result was a viscous liquid that the researchers brushed onto the soft robotic matrix. They also brushed the glue onto a new explanted pig heart that had its left ventricle removed but its endocardial structures preserved. When they wrapped the artificial muscle matrix around this tissue, the two bonded tightly.

Finally, the researchers placed the entire hybrid heart in a mold that they had previously cast of the original, whole heart, and filled the mold with silicone to encase the hybrid heart in a uniform covering — a step that produced a form similar to a real heart and ensured that the robotic bubble wrap fit snugly around the real ventricle.

“That way, you don’t lose transmission of motion from the synthetic muscle to the biological tissue,” Roche says.

When the researchers pumped air into the bubble wrap at frequencies resembling a naturally beating heart, and imaged the bionic heart’s response, it contracted in a manner similar to the way a real heart moves to pump blood through the body.

Ultimately, the researchers hope to use the bionic heart as a realistic environment to help designers test cardiac devices such as prosthetic heart valves.

“Imagine that a patient before cardiac device implantation could have their heart scanned, and then clinicians could tune the device to perform optimally in the patient well before the surgery,” says Nyugen. “Also, with further tissue engineering, we could potentially see the biorobotic hybrid heart be used as an artificial heart — a very needed potential solution given the global heart failure epidemic where millions of people are at the mercy of a competitive heart transplant list.”

This research was supported in part by the National Science Foundation.

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Demystifying artificial intelligence

Natalie Lao was set on becoming an electrical engineer, like her parents, until she stumbled on course 6.S192 (Making Mobile Apps), taught by Professor Hal Abelson. Here was a blueprint for turning a smartphone into a tool for finding clean drinking water, or sorting pictures of faces, or doing just about anything. “I thought, I wish people knew building tech could be like this,” she said on a recent afternoon, taking a break from writing her dissertation.

After shifting her focus as an MIT undergraduate to computer science, Lao joined Abelson’s lab, which was busy spreading its App Inventor platform and do-it-yourself philosophy to high school students around the world. App Inventor set Lao on her path to making it easy for anyone, from farmers to factory workers, to understand AI, and use it to improve their lives. Now in the third and final year of her PhD at MIT, Lao is also the co-founder of an AI startup to fight fake news, and the co-producer of a series of machine learning tutorials. It’s all part of her mission to help people find the creator and free thinker within. 

“She just radiates optimism and enthusiasm,” says Abelson, the Class of 1922 Professor in the Department of Electrical Engineering and Computer Science (EECS). “She’s a natural leader who knows how to get people excited and organized.” 

Lao was immersed in App Inventor, building modules to teach students to build face recognition models and store data in the cloud. Then, in 2016, the surprise election of Donald Trump to U.S. president forced her to think more critically about technology. She was less upset by Trump the politician as by revelations that social media-fueled propaganda and misinformation had tilted the race in Trump’s favor.

When a friend, Elan Pavlov, a then-EECS postdoc, approached Lao about an idea he had for building a platform to combat fake news she was ready to dive in. Having grown up in rural, urban, and suburban parts of Tennessee and Ohio, Lao was used to hearing a range of political views. But now, social platforms were filtering those voices, and amplifying polarizing, often inaccurate, content. Pavlov’s idea stood out for its focus on identifying the people (and bots) spreading misinformation and disinformation, rather than the content itself. 

Lao recruited two friends, Andrew Tsai and Keertan Kini, to help build out the platform. They would later name it HINTS, or Human Interaction News Trustworthiness System, after an early page-ranking algorithm called HITS. 

In a demo last fall, Lao and Tsai highlighted a network of Twitter accounts that had shared conspiracy theories tied to the murder of Saudi journalist Jamal Khashoggi under the hashtag #khashoggi. When they looked at what else those accounts had shared, they found streams of other false and misleading news. Topping the list was the incorrect claim that then-U.S. Congressman Beto O’Rourke had funded a caravan of migrants headed for the U.S. border.

The HINTS team hopes that by flagging the networks that spread fake news, social platforms will move faster to remove fake accounts and contain the propagation of misinformation.

“Fake news doesn’t have any impact in a vacuum — real people have to read it and share it,” says Lao. “No matter what your political views, we’re concerned about facts and democracy. There’s fake news being pushed on both sides and it’s making the political divide even worse.”

The HINTS team is now working with its first client, a media analytics firm based in Virginia. As CEO, Lao has called on her experience as a project manager from internships at GE, Google, and Apple, where, most recently, she led the rollout of the iPhone XR display screen. “I’ve never met anyone as good at managing people and tech,” says Tsai, an EECS master’s student who met Lao as a lab assistant for Abelson’s course 6.S198 (Deep Learning Practicum), and is now CTO of HINTS.

As HINTS was getting off the ground, Lao co-founded a second startup, ML Tidbits, with EECS graduate student Harini Suresh. While learning to build AI models, both women grew frustrated by the tutorials on YouTube. “They were full of formulas, with very few pictures,” she says. “Even if the material isn’t that hard, it looks hard!” 

Convinced they could do better, Lao and Suresh reimagined a menu of intimidating topics like unsupervised learning and model-fitting as a set of inviting side dishes. Sitting cross-legged on a table, as if by a cozy fire, Lao and Suresh put viewers at ease with real-world anecdotes, playful drawings, and an engaging tone. Six more videos, funded by MIT Sandbox and the MIT-IBM Watson AI Lab, are planned for release this spring. 

If her audience learns one thing from ML Tidbits, Lao says, she hopes it’s that anyone can learn the basic underpinnings of AI. “I want them to think, ‘Oh, this technology isn't just something that professional computer scientists or mathematicians can touch. I can learn it too. I can form educated opinions and join discussions about how it should be used and regulated.’ ”

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Nathan Howard wins Nuclear Fusion Award

Nathan Howard, research scientist at MIT’s Plasma Science and Fusion Center (PSFC), has won the 2019 Nuclear Fusion Award from the International Atomic Energy Agency (IAEA) for a paper that explains heat losses due to turbulence in the core of magnetically confined fusion plasmas.

Understanding and predicting plasma turbulence has been a key challenge for fusion researchers. Simulations of turbulent plasma conditions have not always been able to match experimental observations of heat loss in magnetically confined plasmas, making it impossible for researchers to be confident predicting the performance of future tokamaks, like ITER, the next-step fusion reactor being built in France. In collaboration with colleagues from MIT, the University of California at San Diego, and General Atomics, Howard discovered that only by performing multiscale simulations, which simultaneously capture both short wavelength (electron scale) and long wavelength (ion scale) plasma turbulence, could he match the experimental observations.

Before this, many researchers had assumed that the turbulence caused by electrons would be negligible in relation to the greater turbulence caused by ions, which is 60 times larger. In fact, this work found that the smaller-scale electron-scale turbulence interacts with the ion-scale turbulence in a way that contributes significantly to the experimental results and would need to be considered in any simulation.

The multiscale simulations took approximately 120 million CPU hours and roughly a year to run on the Edison supercomputer at the National Energy Research Scientific Computing Center (NERSC), requiring Howard to get increases from the U.S. Department of Energy to his already-large allocation. Additionally, while the NERSC system only allows jobs to run without interruption for 36 hours, Howard's simulations took months to complete, necessitating frequent restarts.

“I’d wake up in the middle of the night and basically switch jobs around so I could keep the simulation running as frequently as possible because I wanted the answer faster. They still took months and months to do.”

What most excites Howard about the research is that the multiscale results of his paper have been incorporated into a reduced transport model called Trapped Gyro-Landau Fluid (TGLF), a model that provides results in a fraction of the time of a supercomputer.

“This allows you to predict the electron temperature, electron density, ion temperature profiles that you see in the experiment, but do it in a matter of minutes, not years,” says Howard. “That’s really what was cool about this work: Not only did it show that you can match these experiments with these large-scale simulations, but the results were fed back into TGLF and created a slightly different TGLF model that is now used to predict performance and interpret results on a number of fusion devices.”

Noting that the reduced model is now being used to predict performance of the PSFC’s proposed path to fusion, SPARC, Howard says, “It’s come full circle.”

Howard continues to explore similar simulations, but is looking at higher performance discharges than before, to see if the observed multiscale interactions still exist and to gain greater insight into how and when turbulence occurs.

Inaugurated in 2006, The Nuclear Fusion Award is given annually to recognize work published in the journal Nuclear Fusion that has made the largest scientific impact. Past recipients have included other members of the PSFC community: Senior Research Scientist John Rice (2010) and Director Dennis Whyte (2013).

Howard authored the winning paper as a postdoc supported by the Oak Ridge Institute for Science and Education (ORISE), using data from the PSFC’s Alcator C-Mod tokamak. He credits co-authors Chris Holland (University of California at San Diego), and Jeff Candy (General Atomics), as well as MIT colleagues Anne White, head of the Department of Nuclear Science and Engineering, and Martin Greenwald, PSFC deputy director. He is also grateful for significant support and encouragement from program managers at the Department of Energy.

“There is support for good science wherever it goes. And I think that is one thing that is great about the PSFC. It allows you to pursue what you feel is interesting research, and let it take you in a direction that you think might be most interesting and impactful. Working here, combined with the ORISE, really allowed me to do that.”

Howard will receive the award at the IAEA Fusion Energy Conference to be held in France in 2020.

The research was supported by the U.S. Department of Energy.

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Gift will allow MIT researchers to use artificial intelligence in a biomedical device

Researchers in the MIT Department of Civil and Environmental Engineering (CEE) have received a gift to advance their work on a device designed to position living cells for growing human organs using acoustic waves. The Acoustofluidic Device Design with Deep Learning is being supported by Natick, Massachusetts-based MathWorks, a leading developer of mathematical computing software.

“One of the fundamental problems in growing cells is how to move and position them without damage,” says John R. Williams, a professor in CEE. “The devices we’ve designed are like acoustic tweezers.”

Inspired by the complex and beautiful patterns in the sand made by waves, the researchers' approach is to use sound waves controlled by machine learning to design complex cell patterns. The pressure waves generated by acoustics in a fluid gently move and position the cells without damaging them.

The engineers developed a computer simulator to create a variety of device designs, which were then fed to an AI platform to understand the relationship between device design and cell positions.

“Our hope is that, in time, this AI platform will create devices that we couldn’t have imagined with traditional approaches,” says Sam Raymond, who recently completed his doctorate working with Williams on this project. Raymond’s thesis title, "Combining Numerical Simulation and Machine Learning," explored the application of machine learning in computational engineering.

“MathWorks and MIT have a 30-year long relationship that centers on advancing innovations in engineering and science,” says P.J. Boardman, director of MathWorks. “We are pleased to support Dr. Williams and his team as they use new methodologies in simulation and deep learning to realize significant scientific breakthroughs.”

Williams and Raymond collaborated with researchers at the University of Melbourne and the Singapore University of Technology and Design on this project.

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Powering the planet

Before Fikile Brushett wanted to be an engineer, he wanted to be a soccer player. Today, however, Brushett is the Cecil and Ida Green Career Development Chair, and associate professor of chemical engineering. Building 66 might not look much like a soccer field, but Brushett says the sport taught him a fundamental lesson that has proved invaluable in his scientific endeavors.

“The teams that are successful are the teams that work together,” Brushett says.

That philosophy inspires the Brushett Research Group, which draws on disciplines as diverse as organic chemistry and economics to create new electrochemical processes and devices.

As the world moves toward cleaner and sustainable sources of energy, one of the major challenges is converting efficiently between electrical and chemical energy. This is the challenge undertaken by Brushett and his colleagues, who are trying to push the frontiers of electrochemical technology.

Brushett’s research focuses on ways to improve redox flow batteries, which are potentially low-cost alternatives to conventional batteries and a viable way of storing energy from renewable sources like wind and the sun. His group also explores means to recycle carbon dioxide — a greenhouse gas — into fuels and useful chemicals, and to extract energy from biomass.

In his work, Brushett is helping to transform every stage of the energy pipeline: from unlocking the potential of solar and wind energy to replacing combustion engines with fuel cells, and even enabling greener industrial processes.

“A lot of times, electrochemical technologies work in some areas, but we'd like them to work much more broadly than we've asked them to do beforehand,” Brushett says. “A lot of that is now driving the need for new innovation in the area, and that's where we come in.”

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Accelerating the pace of engineering

Founded in 1984 by Jack Little ’78 and Cleve Moler, MathWorks was built on the premise of providing engineers and scientists with more powerful and productive computation environments. In 1985, the company sold its very first order — 10 copies of its first product, MATLAB — to MIT.

Decades later, engineers across MIT and around the world consistently rely on MathWorks products to accelerate the pace of discovery, innovation, and development in automotive, aerospace, electronics, biotech-pharmaceutical, and other industries. MathWorks’ products and support have had a significant impact on MITx, OpenCourseWare, and MIT’s digital learning efforts across campus, including the Department of Mathematics, one of the School of Engineering’s closest collaborators in the use of digital learning tools and educational technologies.

“We have a strong belief in the importance of engineers and scientists,” says Little. “They act to increase human knowledge and profoundly improve our standard of living. We create products like MATLAB and Simulink to help them do their best work.”

As the language of technical computing, MATLAB is a programming environment for algorithm development, data analysis, visualization, and numeric computation. It is used extensively by faculty, students, and researchers across MIT and by over 4 million users in industry, government, and academia in 185 countries.

Simulink is a block diagram environment for simulation and model-based design of multidomain and embedded engineering systems, including automatic code generation, verification, and validation. It is used heavily in automotive, aerospace, and other applications that design complex real-time systems.

This past summer, MathWorks celebrated 35 years of accelerating the pace of engineering and science. Shortly following this milestone, MathWorks awarded 11 engineering fellowships to graduate students within the School of Engineering who are active users of MATLAB or Simulink. The fellows are using the programs to advance discovery and innovation across disciplines.

“PhD fellowships are an investment in the world’s long-term future, and there are few investments more valuable than that,” says Little.

The 2019-20 MathWorks fellows are:

Pasquale Antonante is a PhD student in the Department of Aeronautics and Astronautics. He uses MATLAB and Simulink to build tools that make robots more accurate.

Alireza Fallah is a PhD student in the Department of Electrical Engineering and Computer Science. He uses Matlab and Symbolic Math Toolbox to develop better machine-learning algorithms.

James Gabbard is a SM/PhD student in the Department of Mechanical Engineering. He uses MATLAB to model fluids and materials.

Nicolas Meirhaeghe is a PhD student in medical engineering and medical physics in the Bioastronautics Training Program at Harvard-MIT Division of Health Sciences and Technology. He uses MATLAB to visualize activity in the brain and understand how it is related to an individual’s behavior.

Caroline Nielsen is a PhD student in the Department of Chemical Engineering. She uses MATLAB to implement and test new applications of non-smooth analysis. She also intends to use MATLAB to in the next phase of her research, developing methods to simultaneously optimize for minimal resource use and operating costs.

Bauyrzhan Primkulov is a PhD student in the Department of Civil and Environmental Engineering. He uses MATLAB to build computational models and explore how fluids interact in porous materials.

Kate Reidy is a PhD student in the Department of Materials Science and Engineering. She studies how 2D materials — only a single atom thick — can be combined with 3D materials, and uses MATLAB to analyze the properties of different materials.

Isabelle Su is a PhD student in civil and environmental engineering. She builds computational models with MATLAB to understand the mechanical properties of spider webs.

Joy Zeng is a PhD student in chemical engineering. Her research is focused on the electrochemical transformation of carbon dioxide to fuels and commodity chemicals. She uses MATLAB to model chemical reactions.

Benjamin "Jiahong" Zhang is a PhD student in computational science and engineering. He uses MATLAB to prototype new methods for rare event simulation, finding new methods by leveraging mathematical principles used in proofs and re-purposing them for computation.

Paul Zhang is a PhD student in electrical engineering and computer science. He uses MATLAB to develop algorithms with applications in meshing — the use of simple shapes to study complex ones.

For MathWorks, fostering engineering education is a priority, so when deciding where to focus philanthropic support, MIT — its very first customer — was an obvious choice.

“We are so humbled by MathWorks' generosity, and their continued support of our engineering students through these fellowships,” says Anantha Chandrakasan, dean of the School of Engineering. “Our relationship with MathWorks is one that we revere — they have developed products that foster research and advancement across many disciplines, and through their support our students launch discoveries and innovation that align with MathWorks’ mission.”

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