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      Unlocking new doors to artificial intelligence

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      Artificial intelligence research is constantly developing new hypotheses that have the potential to benefit society and industry; however, sometimes these benefits are not fully realized due to a lack of engineering tools. To help bridge this gap, graduate students in the MIT Department of Electrical Engineering and Computer Science’s 6-A Master of Engineering (MEng) Thesis Program work with some of the most innovative companies in the world and collaborate on cutting-edge projects, while contributing to and completing their MEng thesis.

      During a portion of the last year, four 6-A MEng students teamed up and completed an internship with IBM Research’s advanced prototyping team through the MIT-IBM Watson AI Lab on AI projects, often developing web applications to solve a real-world issue or business use cases. Here, the students worked alongside AI engineers, user experience engineers, full-stack researchers, and generalists to accommodate project requests and receive thesis advice, says Lee Martie, IBM research staff member and 6-A manager. The students’ projects ranged from generating synthetic data to allow for privacy-sensitive data analysis to using computer vision to identify actions in video that allows for monitoring human safety and tracking build progress on a construction site.

      “I appreciated all of the expertise from the team and the feedback,” says 6-A graduate Violetta Jusiega ’21, who participated in the program. “I think that working in industry gives the lens of making sure that the project’s needs are satisfied and [provides the opportunity] to ground research and make sure that it is helpful for some use case in the future.”

      Jusiega’s research intersected the fields of computer vision and design to focus on data visualization and user interfaces for the medical field. Working with IBM, she built an application programming interface (API) that let clinicians interact with a medical treatment strategy AI model, which was deployed in the cloud. Her interface provided a medical decision tree, as well as some prescribed treatment plans. After receiving feedback on her design from physicians at a local hospital, Jusiega developed iterations of the API and how the results where displayed, visually, so that it would be user-friendly and understandable for clinicians, who don’t usually code. She says that, “these tools are often not acquired into the field because they lack some of these API principles which become more important in an industry where everything is already very fast paced, so there’s little time to incorporate a new technology.” But this project might eventually allow for industry deployment. “I think this application has a bunch of potential, whether it does get picked up by clinicians or whether it’s simply used in research. It’s very promising and very exciting to see how technology can help us modify, or I can improve, the health-care field to be even more custom-tailored towards patients and giving them the best care possible,” she says.

      Another 6-A graduate student, Spencer Compton, was also considering aiding professionals to make more informed decisions, for use in settings including health care, but he was tackling it from a causal perspective. When given a set of related variables, Compton was investigating if there was a way to determine not just correlation, but the cause-and-effect relationship between them (the direction of the interaction) from the data alone. For this, he and his collaborators from IBM Research and Purdue University turned to a field of math called information theory. With the goal of designing an algorithm to learn complex networks of causal relationships, Compton used ideas relating to entropy, the randomness in a system, to help determine if a causal relationship is present and how variables might be interacting. “When judging an explanation, people often default to Occam’s razor” says Compton. “We’re more inclined to believe a simpler explanation than a more complex one.” In many cases, he says, it seemed to perform well. For instance, they were able to consider variables such as lung cancer, pollution, and X-ray findings. He was pleased that his research allowed him to help create a framework of “entropic causal inference” that could aid in safe and smart decisions in the future, in a satisfying way. “The math is really surprisingly deep, interesting, and complex,” says Compton. “We’re basically asking, ‘when is the simplest explanation correct?’ but as a math question.”

      Determining relationships within data can sometimes require large volumes of it to suss out patterns, but for data that may contain sensitive information, this may not be available. For her master’s work, Ivy Huang worked with IBM Research to generate synthetic tabular data using a natural language processing tool called a transformer model, which can learn and predict future values from past values. Trained on real data, the model can produce new data with similar patterns, properties, and relationships without restrictions like privacy, availability, and access that might come with real data in financial transactions and electronic medical records. Further, she created an API and deployed the model in an IBM cluster, which allowed users increased access to the model and abilities to query it without compromising the original data.

      Working with the advanced prototyping team, MEng candidate Brandon Perez also considered how to gather and investigate data with restrictions, but in his case it was to use computer vision frameworks, centered on an action recognition model, to identify construction site happenings. The team based their work on the Moments in Time dataset, which contains over a million three-second video clips with about 300 attached classification labels, and has performed well during AI training. However, the group needed more construction-based video data. For this, they used YouTube-8M. Perez built a framework for testing and fine-tuning existing object detection models and action recognition models that could plug into an automatic spatial and temporal localization tool — how they would identify and label particular actions in a video timeline. “I was satisfied that I was able to explore what made me curious, and I was grateful for the autonomy that I was given with this project,” says Perez. “I felt like I was always supported, and my mentor was a great support to the project.”

      “The kind of collaborations that we have seen between our MEng students and IBM researchers are exactly what the 6-A MEng Thesis program at MIT is all about,” says Tomas Palacios, professor of electrical engineering and faculty director of the MIT 6-A MEng Thesis program. “For more than 100 years, 6-A has been connecting MIT students with industry to solve together some of the most important problems in the world.” More

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      Meet the 2021-22 Accenture Fellows

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      Launched in October of 2020, the MIT and Accenture Convergence Initiative for Industry and Technology underscores the ways in which industry and technology come together to spur innovation. The five-year initiative aims to achieve its mission through research, education, and fellowships. To that end, Accenture has once again awarded five annual fellowships to MIT graduate students working on research in industry and technology convergence who are underrepresented, including by race, ethnicity, and gender.

      This year’s Accenture Fellows work across disciplines including robotics, manufacturing, artificial intelligence, and biomedicine. Their research covers a wide array of subjects, including: advancing manufacturing through computational design, with the potential to benefit global vaccine production; designing low-energy robotics for both consumer electronics and the aerospace industry; developing robotics and machine learning systems that may aid the elderly in their homes; and creating ingestible biomedical devices that can help gather medical data from inside a patient’s body.

      Student nominations from each unit within the School of Engineering, as well as from the four other MIT schools and the MIT Schwarzman College of Computing, were invited as part of the application process. Five exceptional students were selected as fellows in the initiative’s second year.

      Xinming (Lily) Liu is a PhD student in operations research at MIT Sloan School of Management. Her work is focused on behavioral and data-driven operations for social good, incorporating human behaviors into traditional optimization models, designing incentives, and analyzing real-world data. Her current research looks at the convergence of social media, digital platforms, and agriculture, with particular attention to expanding technological equity and economic opportunity in developing countries. Liu earned her BS from Cornell University, with a double major in operations research and computer science.

      Caris Moses is a PhD student in electrical engineering and computer science specializing inartificial intelligence. Moses’ research focuses on using machine learning, optimization, and electromechanical engineering to build robotics systems that are robust, flexible, intelligent, and can learn on the job. The technology she is developing holds promise for industries including flexible, small-batch manufacturing; robots to assist the elderly in their households; and warehouse management and fulfillment. Moses earned her BS in mechanical engineering from Cornell University and her MS in computer science from Northeastern University.

      Sergio Rodriguez Aponte is a PhD student in biological engineering. He is working on the convergence of computational design and manufacturing practices, which have the potential to impact industries such as biopharmaceuticals, food, and wellness/nutrition. His current research aims to develop strategies for applying computational tools, such as multiscale modeling and machine learning, to the design and production of manufacturable and accessible vaccine candidates that could eventually be available globally. Rodriguez Aponte earned his BS in industrial biotechnology from the University of Puerto Rico at Mayaguez.

      Soumya Sudhakar SM ’20 is a PhD student in aeronautics and astronautics. Her work is focused on theco-design of new algorithms and integrated circuits for autonomous low-energy robotics that could have novel applications in aerospace and consumer electronics. Her contributions bring together the emerging robotics industry, integrated circuits industry, aerospace industry, and consumer electronics industry. Sudhakar earned her BSE in mechanical and aerospace engineering from Princeton University and her MS in aeronautics and astronautics from MIT.

      So-Yoon Yang is a PhD student in electrical engineering and computer science. Her work on the development of low-power, wireless, ingestible biomedical devices for health care is at the intersection of the medical device, integrated circuit, artificial intelligence, and pharmaceutical fields. Currently, the majority of wireless biomedical devices can only provide a limited range of medical data measured from outside the body. Ingestible devices hold promise for the next generation of personal health care because they do not require surgical implantation, can be useful for detecting physiological and pathophysiological signals, and can also function as therapeutic alternatives when treatment cannot be done externally. Yang earned her BS in electrical and computer engineering from Seoul National University in South Korea and her MS in electrical engineering from Caltech. More

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      Data flow’s decisive role on the global stage

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      In 2016, Meicen Sun came to a profound realization: “The control of digital information will lie at the heart of all the big questions and big contentions in politics.” A graduate student in her final year of study who is specializing in international security and the political economy of technology, Sun vividly recalls the emergence of the internet “as a democratizing force, an opener, an equalizer,” helping give rise to the Arab Spring. But she was also profoundly struck when nations in the Middle East and elsewhere curbed internet access to throttle citizens’ efforts to speak and mobilize freely.

      During her undergraduate and graduate studies, which came to focus on China and its expanding global role, Sun became convinced that digital constraints initially intended to prevent the free flow of ideas were also having enormous and growing economic impacts.

      “With an exceptionally high mobile internet adoption rate and the explosion of indigenous digital apps, China’s digital economy was surging, helping to drive the nation’s broader economic growth and international competitiveness,” Sun says. “Yet at the same time, the country maintained the most tightly controlled internet ecosystem in the world.”

      Sun set out to explore this apparent paradox in her dissertation. Her research to date has yielded both novel findings and troubling questions.  

      “Through its control of the internet, China has in effect provided protectionist benefits to its own data-intensive domestic sectors,” she says. “If there is a benefit to imposing internet control, given the absence of effective international regulations, does this give authoritarian states an advantage in trade and national competitiveness?” Following this thread, Sun asks, “What might this mean for the future of democracy as the world grows increasingly dependent on digital technology?”

      Protect or innovate

      Early in her graduate program, classes in capitalism and technology and public policy, says Sun, “cemented for me the idea of data as a factor of production, and the importance of cross-border information flow in making a country innovative.” This central premise serves as a springboard for Sun’s doctoral studies.

      In a series of interconnected research papers using China as her primary case, she is examining the double-edged nature of internet limits. “They accord protectionist benefits to domestic data-internet-intensive sectors, on the one hand, but on the other, act as a potential longer-term deterrent to the country’s capacity to innovate.”

      To pursue her doctoral project, advised by professor of political science Kenneth Oye, Sun is extracting data from a multitude of sources, including a website that has been routinely testing web domain accessibility from within China since 2011. This allows her to pin down when and to what degree internet control occurs. She can then compare this information to publicly available records on the expansion or contraction of data-intensive industrial sectors, enabling her to correlate internet control to a sector’s performance.

      Sun has also compiled datasets for firm-level revenue, scientific citations, and patents that permit her to measure aspects of China’s innovation culture. In analyzing her data she leverages both quantitative and qualitative methods, including one co-developed by her dissertation co-advisor, associate professor of political science In Song Kim. Her initial analysis suggests internet control prevents scholars from accessing knowledge available on foreign websites, and that if sustained, such control could take a toll on the Chinese economy over time.

      Of particular concern is the possibility that the economic success that flows from strict internet controls, as exemplified by the Chinese model, may encourage the rise of similar practices among emerging states or those in political flux.

      “The grim implication of my research is that without international regulation on information flow restrictions, democracies will be at a disadvantage against autocracies,” she says. “No matter how short-term or narrow these curbs are, they confer concrete benefits on certain economic sectors.”

      Data, politics, and economy

      Sun got a quick start as a student of China and its role in the world. She was born in Xiamen, a coastal Chinese city across from Taiwan, to academic parents who cultivated her interest in international politics. “My dad would constantly talk to me about global affairs, and he was passionate about foreign policy,” says Sun.

      Eager for education and a broader view of the world, Sun took a scholarship at 15 to attend school in Singapore. “While this experience exposed me to a variety of new ideas and social customs, I felt the itch to travel even farther away, and to meet people with different backgrounds and viewpoints from mine,” than she says.

      Sun attended Princeton University where, after two years sticking to her “comfort zone” — writing and directing plays and composing music for them — she underwent a process of intellectual transition. Political science classes opened a window onto a larger landscape to which she had long been connected: China’s behavior as a rising power and the shifting global landscape.

      She completed her undergraduate degree in politics, and followed up with a master’s degree in international relations at the University of Pennsylvania, where she focused on China-U.S. relations and China’s participation in international institutions. She was on the path to completing a PhD at Penn when, Sun says, “I became confident in my perception that digital technology, and especially information sharing, were becoming critically important factors in international politics, and I felt a strong desire to devote my graduate studies, and even my career, to studying these topics,”

      Certain that the questions she hoped to pursue could best be addressed through an interdisciplinary approach with those working on similar issues, Sun began her doctoral program anew at MIT.

      “Doer mindset”

      Sun is hopeful that her doctoral research will prove useful to governments, policymakers, and business leaders. “There are a lot of developing states actively shopping between data governance and development models for their own countries,” she says. “My findings around the pros and cons of information flow restrictions should be of interest to leaders in these places, and to trade negotiators and others dealing with the global governance of data and what a fair playing field for digital trade would be.”

      Sun has engaged directly with policy and industry experts through her fellowships with the World Economic Forum and the Pacific Forum. And she has embraced questions that touch on policy outside of her immediate research: Sun is collaborating with her dissertation co-advisor, MIT Sloan Professor Yasheng Huang, on a study of the political economy of artificial intelligence in China for the MIT Task Force on the Work of the Future.

      This year, as she writes her dissertation papers, Sun will be based at Georgetown University, where she has a Mortara Center Global Political Economy Project Predoctoral Fellowship. In Washington, she will continue her journey to becoming a “policy-minded scholar, a thinker with a doer mindset, whose findings have bearing on things that happen in the world.” More

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      3 Questions: Peko Hosoi on the data-driven reasoning behind MIT’s Covid-19 policies for the fall

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      As students, faculty, and staff prepare for a full return to the MIT campus in the weeks ahead, procedures for entering buildings, navigating classrooms and labs, and interacting with friends and colleagues will likely take some getting used to.

      The Institute recently reinforced its policies for indoor masking and has also continued to require regular testing for people who live, work, or study on campus — procedures that apply to both vaccinated and unvaccinated individuals. Vaccination is required for all students, faculty, and staff on campus unless a medical or religious exemption is granted.

      These and other policies adopted by MIT to control the spread of Covid-19 have been informed by modeling efforts from a volunteer group of MIT faculty, students, and postdocs. The collaboration, dubbed Isolat, was co-founded by Anette “Peko” Hosoi, the Neil and Jane Pappalardo Professor of Mechanical Engineering and associate dean in the School of Engineering.

      The group, which is organized through MIT’s Institute for Data, Systems, and Society (IDSS), has run numerous models to show how measures such as mask wearing, testing, ventilation, and quarantining could affect Covid-19’s spread. These models have helped to shape MIT’s Covid-19 policies throughout the pandemic, including its procedures for returning to campus this fall.

      Hosoi spoke with MIT News about the data-backed reasoning behind some of these procedures, including indoor masking and regular testing, and how a “generous community” will help MIT safely weather the virus and its variants.

      Q: Take us through how you have been modeling Covid-19 and its variants, in regard to helping MIT shape its Covid policies. What’s the approach you’ve taken, and why?

      A: The approach we’re taking uses a simple counting exercise developed in IDSS to estimate the balance of testing, masking, and vaccination that is required to keep the virus in check. The underlying objective is to find infected people faster, on average, than they can infect others, which is captured in a simple algebraic expression. Our objective can be accomplished either by speeding up the rate of finding infected people (i.e. increasing testing frequency) or slowing down the rate of infection (i.e. increasing masking and vaccination) or by a combination of both. To give you a sense of the numbers, balances for different levels of testing are shown in the chart below for a vaccine efficacy of 67 percent and a contagious period of 18 days (which are the CDC’s latest parameters for the Delta variant).

      The vertical axis shows the now-famous reproduction number R0, i.e. the average number of people that one infected person will infect throughout the course of their illness. These R0 are averages for the population, and in specific circumstances the spreading could be more than that.

      Each blue line represents a different testing frequency: Below the line, the virus is controlled; above the line, it spreads. For example, the dotted blue line shows the boundary if we rely solely on vaccination with no testing. In that case, even if everyone is vaccinated, we can only control up to an R0 of about 3.  Unfortunately, the CDC places R0 of the Delta variant somewhere between 5 and 9, so vaccination alone is insufficient to control the spread. (As an aside, this also means that given the efficacy estimates for the current vaccines, herd immunity is not possible.)

      Next consider the dashed blue line, which represents the stability boundary if we test everyone once per week. If our vaccination rate is greater than about 90 percent, testing one time per week can control even the CDC’s most pessimistic estimate for the Delta variant’s R0.

      Q: In returning to campus over the next few weeks, indoor masking and regular testing are required of every MIT community member, even those who are vaccinated. What in your modeling has shown that each of these policies is necessary?

      A: Given that the chart above shows that vaccination and weekly testing are sufficient to control the virus, one should certainly ask “Why have we reinstated indoor masking?” The answer is related to the fact that, as a university, our population turns over once a year; every September we bring in a few thousand new people. Those people are coming from all over the world, and some of them may not have had the opportunity to get vaccinated yet. The good news is that MIT Medical has vaccines and will be administering them to any unvaccinated students as soon as they arrive; the bad news is that, as we all know, it takes three to five weeks for resistance to build up, depending on the vaccine. This means that we should think of August and September as a transition period during which the vaccination rates may fluctuate as new people arrive. 

      The other revelation that has informed our policies for September is the recent report from the CDC that infected vaccinated people carry roughly the same viral load as unvaccinated infected people. This suggests that vaccinated people — although they are highly unlikely to get seriously ill — are a consequential part of the transmission chain and can pass the virus along to others. So, in order to avoid giving the virus to people who are not yet fully vaccinated during the transition period, we all need to exercise a little extra care to give the newly vaccinated time for their immune systems to ramp up. 

      Q: As the fall progresses, what signs are you looking for that might shift decisions on masking and testing on campus?

      A: Eventually we will have to shift responsibility toward individuals rather than institutions, and allow people to make decisions about masks and testing based on their own risk tolerance. The success of the vaccines in suppressing severe illness will enable us to shift to a position in which our objective is not necessarily to control the spread of the virus, but rather to reduce the risk of serious outcomes to an acceptable level. There are many people who believe we need to make this adjustment and wean ourselves off pandemic living. They are right; we cannot continue like this forever. However, we have not played all our cards yet, and, in my opinion, we need to carefully consider what’s left in our hand before we abdicate institutional responsibility.

      The final ace we have to play is vaccinating kids. It is important to remember that we have many people in our community with kids who are too young to be vaccinated and, understandably, those parents do not want to bring Covid home to their children. Furthermore, our campus is not just a workplace; it is also home to thousands of people, some of whom have children living in our residences or attending an MIT childcare center. Given that context, and the high probability that a vaccine will be approved for children in the near future, it is my belief that our community has the empathy and fortitude to try to keep the virus in check until parents have the option to protect their children with vaccines. 

      Bearing in mind that children constitute an unprotected portion of our population, let me return to the original question and speculate on the fate of masks and testing in the fall. Regarding testing, the analysis suggests that we cannot give that up entirely if we would like to control the spread of the virus. Second, control of the virus is not the only benefit we get from testing. It also gives us situational awareness, serves as an early warning beacon, and provides information that individual members of the community can use as they make decisions about their own risk budget. Personally, I’ve been testing for a year now and I find it easy and reassuring. Honestly, it’s nice to know that I’m Covid-free before I see friends (outside!) or go home to my family.

      Regarding masks, there is always uncertainty around whether a new variant will arise or whether vaccine efficacy will fade, but, given the current parameters and our analysis, my hope is that we will be in a position to provide some relief on the mask mandate once the incoming members of our population have been fully vaccinated. I also suspect that whenever the mask mandate is lifted, masks are not likely to go away. There are certainly situations in which I will continue to wear a mask regardless of the mandate, and many in our community will continue to feel safer wearing masks even when they are not required.

      I believe that we are a generous community and that we will be willing to take precautions to help keep each other healthy. The students who were on campus last year did an outstanding job, and they have given me a tremendous amount of faith that we can be considerate and good to one another even in extremely trying times.

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      “AI for Impact” lives up to its name

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      For entrepreneurial MIT students looking to put their skills to work for a greater good, the Media Arts and Sciences class MAS.664 (AI for Impact) has been a destination point. With the onset of the pandemic, that goal came into even sharper focus. Just weeks before the campus shut down in 2020, a team of students from the class launched a project that would make significant strides toward an open-source platform to identify coronavirus exposures without compromising personal privacy.

      Their work was at the heart of Safe Paths, one of the earliest contact tracing apps in the United States. The students joined with volunteers from other universities, medical centers, and companies to publish their code, alongside a well-received white paper describing the privacy-preserving, decentralized protocol, all while working with organizations wishing to launch the app within their communities. The app and related software eventually got spun out into the nonprofit PathCheck Foundation, which today engages with public health entities and is providing exposure notifications in Guam, Cyprus, Hawaii, Minnesota, Alabama, and Louisiana.

      The formation of Safe Paths demonstrates the special sense among MIT researchers that “we can launch something that can help people around the world,” notes Media Lab Associate Professor Ramesh Raskar, who teaches the class together with Media Lab Professor Alex “Sandy” Pentland and Media Lab Lecturer Joost Bonsen. “To have that kind of passion and ambition — but also the confidence that what you create here can actually be deployed globally — is kind of amazing.”

      AI for Impact, created by Pentland, began meeting two decades ago under the course name Development Ventures, and has nurtured multiple thriving businesses. Examples of class ventures that Pentland incubated or co-founded include Dimagi, Cogito, Ginger, Prosperia, and Sanergy.

      The aim-high challenge posed to each class is to come up with a business plan that touches a billion people, and it can’t all be in one country, Pentland explains. Not every class effort becomes a business, “but 20 percent to 30 percent of students start something, which is great for an entrepreneur class,” says Pentland.

      Opportunities for Impact

      The numbers behind Dimagi, for instance, are striking. Its core product CommCare has helped front-line health workers provide care for more than 400 million people in more than 130 countries around the world. When it comes to maternal and child care, Dimagi’s platform has registered one in every 110 pregnancies worldwide. This past year, several governments around the world deployed CommCare applications for Covid-19 response — from Sierra Leone and Somalia to New York and Colorado.

      Spinoffs like Cogito, Prosperia, and Ginger have likewise grown into highly successful companies. Cogito helps a million people a day gain access to the health care they need; Prosperia helps manage social support payments to 80 million people in Latin America; and Ginger handles mental health services for over 1 million people.

      The passion behind these and other class ventures points to a central idea of the class, Pentland notes: MIT students are often looking for ways to build entrepreneurial businesses that enable positive social change.

      During the spring 2021 class, for example, a number of promising student projects included tools to help residents of poor communities transition to owning their homes rather than renting, and to take better control of their community health.

      “It’s clear that the people who are graduating from here want to do something significant with their lives … they want to have an impact on their world,” Pentland says. “This class enables them to meet other people who are interested in doing the same thing, and offers them some help in starting a company to do it.”

      Many of the students who join the class come in with a broad set of interests. Guest lectures, case studies of other social entrepreneurship projects, and an introduction to a broad ecosystem of expertise and funding, then helps students to refine their general ideas into specific and viable projects.

      A path toward confronting a pandemic 

      Raskar began co-teaching the class in 2019, and brought a “Big AI” focus to the Development Ventures class, inspired by an AI for Impact team he had set up at his former employer, Facebook. “What I realized is that companies like Google or Facebook or Amazon actually have enough data about all of us that they can solve major problems in our society — climate, transportation, health, and so on,” he says. “This is something we should think about more seriously: how to use AI and data for positive social impact, while protecting privacy.”

      Early into the spring 2020 class, as students were beginning to consider their own projects, Raskar approached the class about the emerging coronavirus outbreak. Students like Kristen Vilcans recognized the urgency, and the opportunity. She and 10 other students joined forces to work on a project that would focus on Covid-19.

      “Students felt empowered to do something to help tackle the spread of this alarming new virus,” Raskar recalls. “They immediately began to develop data- and AI-based solutions to one of the most critical pieces of addressing a pandemic: halting the chain of infections. They created and launched one of the first digital contact tracing and exposure notification solutions in the U.S., developing an early alert system that engaged the public and protected privacy.” 

      Raskar looks back on the moment when a core group of students coalesced into a team. “It was very rare for a significant part of the class to just come together saying, ‘let’s do this, right away.’ It became as much a movement as a venture.”

      Group discussions soon began to center around an open-source, privacy-first digital set of tools for Covid-19 contact tracing. For the next two weeks, right up to the campus shutdown in March 2020, the team took over two adjacent conference rooms in the Media Lab, and started a Slack messaging channel devoted to the project. As the team members reached out to an ever-wider circle of friends, colleagues, and mentors, the number of participants grew to nearly 1,600 people, coming together virtually from all corners of the world.

      Kaushal Jain, a Harvard Business School student who had cross-registered for the spring 2020 class to get to know the MIT ecosystem, was also an early participant in Safe Paths. He wrote up an initial plan for the venture and began working with external organizations to figure out how to structure it into a nonprofit company. Jain eventually became the project’s lead for funding and partnerships.

      Vilcans, a graduate student in system design and management, served as Safe Paths’ communications lead through July 2020, while still working a part-time job at Draper Laboratory and taking classes.

      “There are these moments when you want to dive in, you want to contribute and you want to work nonstop,” she says, adding that the experience was also a wake-up call on how to manage burnout, and how to balance what you need as a person while contributing to a high-impact team. “That’s important to understand as a leader for the future.”

      MIT recognized Vilcan’s contributions later that year with the 2020 SDM Student Award for Leadership, Innovation, and Systems Thinking. 

      Jain, too, says the class gave him more than he could have expected.

      “I made strong friendships with like-minded people from very different backgrounds,” he says. “One key thing that I learned was to be flexible about the kind of work you want to do. Be open and see if there’s an opportunity, either through crisis or through something that you believe could really change a lot of things in the world. And then just go for it.” More

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      “To make even the smallest contribution to improving my country would be my dream”

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      Thailand has become an economic leader in Southeast Asia in recent decades, but while the country has rapidly industrialized, many Thai citizens have been left behind. As a child growing up in Bangkok, Pavarin Bhandtivej would watch the news and wonder why families in the nearby countryside had next to nothing. He aspired to become a policy researcher and create beneficial change.

      But Bhandtivej knew his goal wouldn’t be easy. He was born with a visual impairment, making it challenging for him to see, read, and navigate. This meant he had to work twice as hard in school to succeed. It took achieving the highest grades for Bhandtivej to break through stigmas and have his talents recognized. Still, he persevered, with a determination to uplift others. “I would return to that initial motivation I had as a kid. For me, to make even the smallest contribution to improving my country would be my dream,” he says.

      “When I would face these obstacles, I would tell myself that struggling people are waiting for someone to design policies for them to have better lives. And that person could be me. I cannot fall here in front of these obstacles. I must stay motivated and move on.”

      Bhandtivej completed his undergraduate degree in economics at Thailand’s top college, Chulalongkorn University. His classes introduced him to many debates about development policy, such as universal basic income. During one debate, after both sides made compelling arguments about how to alleviate poverty, Bhandtivej realized there was no clear winner. “A question came to my mind: Who’s right?” he says. “In terms of theory, both sides were correct. But how could we know what approach would work in the real world?”

      A new approach to higher education

      The search for those answers would lead Bhandtivej to become interested in data analysis. He began investigating online courses, eventually finding the MIT MicroMasters Program in Data, Economics, and Development Policy (DEDP), which was created by MIT’s Department of Economics and the Abdul Latif Jameel Poverty Action Lab (J-PAL). The program requires learners to complete five online courses that teach quantitative methods for evaluating social programs, leading to a MicroMasters credential. Students that pass the courses’ proctored exams are then also eligible to apply for a full-time, accelerated, on-campus master’s program at MIT, led by professors Esther Duflo, Abhijit Banerjee, and Benjamin Olken.

      The program’s mission to make higher education more accessible worked well for Bhandtivej. He studied tirelessly, listening and relistening to online lectures and pausing to scrutinize equations. By the end, his efforts paid off — Bhandtivej was the MicroMasters program’s top scorer. He was soon admitted into the second cohort of the highly selective DEDP master’s program.

      “You can imagine how time-consuming it was to use text-to-speech to get through a 30-page reading with numerous equations, tables, and graphs,” he explains. “Luckily, Disability and Access Services provided accommodations to timed exams and I was able to push through.”   

      In the gap year before the master’s program began, Bhandtivej returned to Chulalongkorn University as a research assistant with Professor Thanyaporn Chankrajang. He began applying his newfound quantitative skills to study the impacts of climate change in Thailand. His contributions helped uncover how rising temperatures and irregular rainfall are leading to reduced rice crop yields. “Thailand is the world’s second largest exporter of rice, and the vast majority of Thais rely heavily on rice for its nutritional and commercial value. We need more data to encourage leaders to act now,” says Bhandtivej. “As a Buddhist, it was meaningful to be part of generating this evidence, as I am always concerned about my impact on other humans and sentient beings.”

      Staying true to his mission

      Now pursuing his master’s on campus, Bhandtivej is taking courses like 14.320 (Econometric Data Science) and studying how to design, conduct, and analyze empirical studies. “The professors I’ve had have opened a whole new world for me,” says Bhandtivej. “They’ve inspired me to see how we can take rigorous scientific practices and apply them to make informed policy decisions. We can do more than rely on theories.”

      The final portion of the program requires a summer capstone experience, which Bhandtivej is using to work at Innovations for Poverty Action. He has recently begun to analyze how remote learning interventions in Bangladesh have performed since Covid-19. Many teachers are concerned, since disruptions in childhood education can lead to intergenerational poverty. “We have tried interventions that connect students with teachers, provide discounted data packages, and send information on where to access adaptive learning technologies and other remote learning resources,” he says. “It will be interesting to see the results. This is a truly urgent topic, as I don’t believe Covid-19 will be the last pandemic of our lifetime.”

      Enhancing education has always been one of Bhandtivej’s priority interests. He sees education as the gateway that brings a person’s innate talent to light. “There is a misconception in many developing countries that disabled people cannot learn, which is untrue,” says Bhandtivej. “Education provides a critical signal to future employers and overall society that we can work and perform just as well, as long as we have appropriate accommodations.”

      In the future, Bhandtivej plans on returning to Thailand to continue his journey as a policy researcher. While he has many issues he would like to tackle, his true purpose still lies in doing work that makes a positive impact on people’s lives. “My hope is that my story encourages people to think of not only what they are capable of achieving themselves, but also what they can do for others.”

      “You may think you are just a small creature on a large planet. That you have just a tiny role to play. But I think — even if we are just a small part — whatever we can do to make life better for our communities, for our country, for our planet … it’s worth it.” More