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    MIT Schwarzman College of Computing unveils Break Through Tech AI

    Aimed at driving diversity and inclusion in artificial intelligence, the MIT Stephen A. Schwarzman College of Computing is launching Break Through Tech AI, a new program to bridge the talent gap for women and underrepresented genders in AI positions in industry.

    Break Through Tech AI will provide skills-based training, industry-relevant portfolios, and mentoring to qualified undergraduate students in the Greater Boston area in order to position them more competitively for careers in data science, machine learning, and artificial intelligence. The free, 18-month program will also provide each student with a stipend for participation to lower the barrier for those typically unable to engage in an unpaid, extra-curricular educational opportunity.

    “Helping position students from diverse backgrounds to succeed in fields such as data science, machine learning, and artificial intelligence is critical for our society’s future,” says Daniel Huttenlocher, dean of the MIT Schwarzman College of Computing and Henry Ellis Warren Professor of Electrical Engineering and Computer Science. “We look forward to working with students from across the Greater Boston area to provide them with skills and mentorship to help them find careers in this competitive and growing industry.”

    The college is collaborating with Break Through Tech — a national initiative launched by Cornell Tech in 2016 to increase the number of women and underrepresented groups graduating with degrees in computing — to host and administer the program locally. In addition to Boston, the inaugural artificial intelligence and machine learning program will be offered in two other metropolitan areas — one based in New York hosted by Cornell Tech and another in Los Angeles hosted by the University of California at Los Angeles Samueli School of Engineering.

    “Break Through Tech’s success at diversifying who is pursuing computer science degrees and careers has transformed lives and the industry,” says Judith Spitz, executive director of Break Through Tech. “With our new collaborators, we can apply our impactful model to drive inclusion and diversity in artificial intelligence.”

    The new program will kick off this summer at MIT with an eight-week, skills-based online course and in-person lab experience that teaches industry-relevant tools to build real-world AI solutions. Students will learn how to analyze datasets and use several common machine learning libraries to build, train, and implement their own ML models in a business context.

    Following the summer course, students will be matched with machine-learning challenge projects for which they will convene monthly at MIT and work in teams to build solutions and collaborate with an industry advisor or mentor throughout the academic year, resulting in a portfolio of resume-quality work. The participants will also be paired with young professionals in the field to help build their network, prepare their portfolio, practice for interviews, and cultivate workplace skills.

    “Leveraging the college’s strong partnership with industry, Break Through AI will offer unique opportunities to students that will enhance their portfolio in machine learning and AI,” says Asu Ozdaglar, deputy dean of academics of the MIT Schwarzman College of Computing and head of the Department of Electrical Engineering and Computer Science. Ozdaglar, who will be the MIT faculty director of Break Through Tech AI, adds: “The college is committed to making computing inclusive and accessible for all. We’re thrilled to host this program at MIT for the Greater Boston area and to do what we can to help increase diversity in computing fields.”

    Break Through Tech AI is part of the MIT Schwarzman College of Computing’s focus to advance diversity, equity, and inclusion in computing. The college aims to improve and create programs and activities that broaden participation in computing classes and degree programs, increase the diversity of top faculty candidates in computing fields, and ensure that faculty search and graduate admissions processes have diverse slates of candidates and interviews.

    “By engaging in activities like Break Through Tech AI that work to improve the climate for underrepresented groups, we’re taking an important step toward creating more welcoming environments where all members can innovate and thrive,” says Alana Anderson, assistant dean for diversity, equity and inclusion for the Schwarzman College of Computing. More

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    Jonathan Schwarz appointed director of MIT Institutional Research

    Former Provost Martin A. Schmidt named Jonathan D. Schwarz as the new director of MIT Institutional Research — a group within the Office of the Provost that provides high-quality data and analysis to the Institute, government entities, news organizations, and the broader community. 

    Over its 35-year history, Institutional Research has provided consistent, verifiable, and high-quality data. The group was established in 1986 as part of the MIT Office of Campus Planning to support MIT’s academic budget process and space planning studies. The Institute established the group to provide a central source of dependable data for departments, units, research labs, and administrators. 

    Institutional Research conducts campus-wide surveys on topics that affect the community including commuting, wellness, and diversity and inclusion. Additionally, the group submits data on behalf of MIT to the U.S. Department of Education, the Commonwealth of Massachusetts, the National Science Foundation, and national and international higher education rankings such as U.S. News & World Report. Institutional Research also works with peer institutions, consortia, government agencies, and rankings groups to establish the criteria that define how students, faculty, and research dollars are counted.

    “At its core, Institutional Research is about counting people, money, and space,” says Schwarz. “Once Institutional Research established valid and reliable metrics in these areas, it was able to apply its deep understanding of data and the Institute to a broader range of topics using surveys, interviews, and focus groups. We collect, maintain, analyze, and report data so people can make data-informed decisions.”

    One of the group’s most data-rich surveys launched earlier this month, the 2022 MIT Quality of Life Survey. Administered every two years to the entire MIT community on campus and at Lincoln Laboratory, the Quality of Life Survey gathers information about the workload and well-being of MIT’s community members as well as the general atmosphere and climate at MIT. Findings from previous Institutional Research surveys helped to inspire several campus-wide initiatives, including expanded childcare benefits, protocols for flexible work arrangements, upgrades to commuting services, and measures to address student hunger.

    “Surveys give us an idea of where to shine a flashlight, but they are blunt instruments that don’t tell the whole story,” says Schwarz, who most recently served as associate director of Institutional Research, where he has worked since 2017. “We also need to sit down and talk to people and take a deeper dive to get nuance, rich detail, and context to better understand the data we’re collecting.”

    As associate director, Schwarz led an initiative to integrate qualitative data collection and analysis, and played an active role in work around issues of diversity, equity and inclusion. Schwarz joined MIT as an intern and later served as a researcher in MIT’s Office of Minority Education and Admissions Office. He earned a bachelor’s degree in political science from Wabash College and served as the college’s mascot, Wally Wabash. He also earned a master’s degree in education from the Harvard Graduate School of Education, and a PhD in sociology from the University of Notre Dame.

    Schwarz takes over the post from his mentor and Institutional Research’s founding director Lydia Snover, who is retiring after serving MIT in various roles for more than 50 years. 

    “We are blessed at MIT to have a community with an engineering culture — measuring is what we do,” says Snover. “You can’t fix something if you don’t know what’s wrong.”

    Snover will serve as the senior advisor to the director through 2022. A dedicated and valuable member of the MIT community, she started her career at MIT working in administrative positions in the departments of Psychology (now Brain and Cognitive Sciences) and Nutrition and Food Science/Applied Biological Sciences and served as a cook at MIT’s Kappa Sigma fraternity before she officially joined MIT. Snover has a bachelor of arts in philosophy and an MBA from Boston University.

    In her capacity as director of Institutional Research, Snover was awarded the 2019 John Stecklein Distinguished Member Award by the Association for Institutional Research, and the 2007 Lifetime Achievement Award from the Association of American Universities Data Exchange.

    Schwarz began his new role on Jan. 3. More

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    How artificial intelligence can help combat systemic racism

    In 2020, Detroit police arrested a Black man for shoplifting almost $4,000 worth of watches from an upscale boutique. He was handcuffed in front of his family and spent a night in lockup. After some questioning, however, it became clear that they had the wrong man. So why did they arrest him in the first place?

    The reason: a facial recognition algorithm had matched the photo on his driver’s license to grainy security camera footage.

    Facial recognition algorithms — which have repeatedly been demonstrated to be less accurate for people with darker skin — are just one example of how racial bias gets replicated within and perpetuated by emerging technologies.

    “There’s an urgency as AI is used to make really high-stakes decisions,” says MLK Visiting Professor S. Craig Watkins, whose academic home for his time at MIT is the Institute for Data, Systems, and Society (IDSS). “The stakes are higher because new systems can replicate historical biases at scale.”

    Watkins, a professor at the University of Texas at Austin and the founding director of the Institute for Media Innovation​, researches the impacts of media and data-based systems on human behavior, with a specific concentration on issues related to systemic racism. “One of the fundamental questions of the work is: how do we build AI models that deal with systemic inequality more effectively?”

    Play video

    Artificial Intelligence and the Future of Racial Justice | S. Craig Watkins | TEDxMIT

    Ethical AI

    Inequality is perpetuated by technology in many ways across many sectors. One broad domain is health care, where Watkins says inequity shows up in both quality of and access to care. The demand for mental health care, for example, far outstrips the capacity for services in the United States. That demand has been exacerbated by the pandemic, and access to care is harder for communities of color.

    For Watkins, taking the bias out of the algorithm is just one component of building more ethical AI. He works also to develop tools and platforms that can address inequality outside of tech head-on. In the case of mental health access, this entails developing a tool to help mental health providers deliver care more efficiently.

    “We are building a real-time data collection platform that looks at activities and behaviors and tries to identify patterns and contexts in which certain mental states emerge,” says Watkins. “The goal is to provide data-informed insights to care providers in order to deliver higher-impact services.”

    Watkins is no stranger to the privacy concerns such an app would raise. He takes a user-centered approach to the development that is grounded in data ethics. “Data rights are a significant component,” he argues. “You have to give the user complete control over how their data is shared and used and what data a care provider sees. No one else has access.”

    Combating systemic racism

    Here at MIT, Watkins has joined the newly launched Initiative on Combatting Systemic Racism (ICSR), an IDSS research collaboration that brings together faculty and researchers from the MIT Stephen A. Schwarzman College of Computing and beyond. The aim of the ICSR is to develop and harness computational tools that can help effect structural and normative change toward racial equity.

    The ICSR collaboration has separate project teams researching systemic racism in different sectors of society, including health care. Each of these “verticals” addresses different but interconnected issues, from sustainability to employment to gaming. Watkins is a part of two ICSR groups, policing and housing, that aim to better understand the processes that lead to discriminatory practices in both sectors. “Discrimination in housing contributes significantly to the racial wealth gap in the U.S.,” says Watkins.

    The policing team examines patterns in how different populations get policed. “There is obviously a significant and charged history to policing and race in America,” says Watkins. “This is an attempt to understand, to identify patterns, and note regional differences.”

    Watkins and the policing team are building models using data that details police interventions, responses, and race, among other variables. The ICSR is a good fit for this kind of research, says Watkins, who notes the interdisciplinary focus of both IDSS and the SCC. 

    “Systemic change requires a collaborative model and different expertise,” says Watkins. “We are trying to maximize influence and potential on the computational side, but we won’t get there with computation alone.”

    Opportunities for change

    Models can also predict outcomes, but Watkins is careful to point out that no algorithm alone will solve racial challenges.

    “Models in my view can inform policy and strategy that we as humans have to create. Computational models can inform and generate knowledge, but that doesn’t equate with change.” It takes additional work — and additional expertise in policy and advocacy — to use knowledge and insights to strive toward progress.

    One important lever of change, he argues, will be building a more AI-literate society through access to information and opportunities to understand AI and its impact in a more dynamic way. He hopes to see greater data rights and greater understanding of how societal systems impact our lives.

    “I was inspired by the response of younger people to the murders of George Floyd and Breonna Taylor,” he says. “Their tragic deaths shine a bright light on the real-world implications of structural racism and has forced the broader society to pay more attention to this issue, which creates more opportunities for change.” More

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    3 Questions: Fotini Christia on racial equity and data science

    Fotini Christia is the Ford International Professor in the Social Sciences in the Department of Political Science, associate director of the Institute for Data, Systems, and Society (IDSS), and director of the Sociotechnical Systems Research Center (SSRC). Her research interests include issues of conflict and cooperation in the Muslim world, and she has conducted fieldwork in Afghanistan, Bosnia, Iran, the Palestinian Territories, Syria, and Yemen. She has co-organized the IDSS Research Initiative on Combatting Systemic Racism (ICSR), which works to bridge the social sciences, data science, and computation by bringing researchers from these disciplines together to address systemic racism across housing, health care, policing, education, employment, and other sectors of society.

    Q: What is the IDSS/ICSR approach to systemic racism research?

    A: The Research Initiative on Combatting Systemic Racism (ICSR) aims to seed and coordinate cross-disciplinary research to identify and overcome racially discriminatory processes and outcomes across a range of U.S. institutions and policy domains.

    Building off the extensive social science literature on systemic racism, the focus of this research initiative is to use big data to develop and harness computational tools that can help effect structural and normative change toward racial equity.

    The initiative aims to create a visible presence at MIT for cutting-edge computational research with a racial equity lens, across societal domains that will attract and train students and scholars.

    The steering committee for this research initiative is composed of underrepresented minority faculty members from across MIT’s five schools and the MIT Schwarzman College of Computing. Members will serve as close advisors to the initiative as well as share the findings of our work beyond MIT’s campus. MIT Chancellor Melissa Nobles heads this committee.

    Q: What role can data science play in helping to effect change toward racial equity?

    A: Existing work has shown racial discrimination in the job market, in the criminal justice system, as well as in education, health care, and access to housing, among other places. It has also underlined how algorithms could further entrench such bias — be it in training data or in the people who build them. Data science tools can not only help identify, but also contribute to, proposing fixes on racially inequitable outcomes that result from implicit or explicit biases in governing institutional practices in the public and private sector, and more recently from the use of AI and algorithmic methods in decision-making.

    To that effect, this initiative will produce research that explores and collects the relevant big data across domains, while paying attention to the ways such data are collected, and focus on improving and developing data-driven computational tools to address racial disparities in structures and institutions that have reproduced racially discriminatory outcomes in American society.

    The strong correlation between race, class, educational attainment, and various attitudes and behaviors in the American context can make it extremely difficult to rule out the influence of confounding factors. Thus, a key motivation for our research initiative is to highlight the importance of causal analysis using computational methods, and focus on understanding the opportunities of big data and algorithmic decision-making to address racial inequities and promote racial justice — beyond de-biasing algorithms. The intent is to also codify methodologies on equity-informed research practices and produce tools that are clear on the quantifiable expected social costs and benefits, as well as on the downstream effects on systemic racism more broadly.

    Q: What are some ways that the ICSR might conduct or follow-up on research seeking real-world impact or policy change?

    A: This type of research has ethical and societal considerations at its core, especially as they pertain to historically disadvantaged groups in the U.S., and will be coordinated with and communicated to local stakeholders to drive relevant policy decisions. This initiative intends to establish connections to URM [underrepresented minority] researchers and students at underrepresented universities and to directly collaborate with them on these research efforts. To that effect, we are leveraging existing programs such as the MIT Summer Research Program (MSRP).

    To ensure that our research targets the right problems bringing a racial equity lens with an interest to effect policy change, we will also connect with community organizations in minority neighborhoods who often bear the brunt of the direct and indirect effects of systemic racism, as well as with local government offices that work to address inequity in service provision in these communities. Our intent is to directly engage IDSS students with these organizations to help develop and test algorithmic tools for racial equity. More

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    The promise and pitfalls of artificial intelligence explored at TEDxMIT event

    Scientists, students, and community members came together last month to discuss the promise and pitfalls of artificial intelligence at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) for the fourth TEDxMIT event held at MIT. 

    Attendees were entertained and challenged as they explored “the good and bad of computing,” explained CSAIL Director Professor Daniela Rus, who organized the event with John Werner, an MIT fellow and managing director of Link Ventures; MIT sophomore Lucy Zhao; and grad student Jessica Karaguesian. “As you listen to the talks today,” Rus told the audience, “consider how our world is made better by AI, and also our intrinsic responsibilities for ensuring that the technology is deployed for the greater good.”

    Rus mentioned some new capabilities that could be enabled by AI: an automated personal assistant that could monitor your sleep phases and wake you at the optimal time, as well as on-body sensors that monitor everything from your posture to your digestive system. “Intelligent assistance can help empower and augment our lives. But these intriguing possibilities should only be pursued if we can simultaneously resolve the challenges that these technologies bring,” said Rus. 

    The next speaker, CSAIL principal investigator and professor of electrical engineering and computer science Manolis Kellis, started off by suggesting what sounded like an unattainable goal — using AI to “put an end to evolution as we know it.” Looking at it from a computer science perspective, he said, what we call evolution is basically a brute force search. “You’re just exploring all of the search space, creating billions of copies of every one of your programs, and just letting them fight against each other. This is just brutal. And it’s also completely slow. It took us billions of years to get here.” Might it be possible, he asked, to speed up evolution and make it less messy?

    The answer, Kellis said, is that we can do better, and that we’re already doing better: “We’re not killing people like Sparta used to, throwing the weaklings off the mountain. We are truly saving diversity.”

    Knowledge, moreover, is now being widely shared, passed on “horizontally” through accessible information sources, he noted, rather than “vertically,” from parent to offspring. “I would like to argue that competition in the human species has been replaced by collaboration. Despite having a fixed cognitive hardware, we have software upgrades that are enabled by culture, by the 20 years that our children spend in school to fill their brains with everything that humanity has learned, regardless of which family came up with it. This is the secret of our great acceleration” — the fact that human advancement in recent centuries has vastly out-clipped evolution’s sluggish pace.

    The next step, Kellis said, is to harness insights about evolution in order to combat an individual’s genetic susceptibility to disease. “Our current approach is simply insufficient,” he added. “We’re treating manifestations of disease, not the causes of disease.” A key element in his lab’s ambitious strategy to transform medicine is to identify “the causal pathways through which genetic predisposition manifests. It’s only by understanding these pathways that we can truly manipulate disease causation and reverse the disease circuitry.” 

    Kellis was followed by Aleksander Madry, MIT professor of electrical engineering and computer science and CSAIL principal investigator, who told the crowd, “progress in AI is happening, and it’s happening fast.” Computer programs can routinely beat humans in games like chess, poker, and Go. So should we be worried about AI surpassing humans? 

    Madry, for one, is not afraid — or at least not yet. And some of that reassurance stems from research that has led him to the following conclusion: Despite its considerable success, AI, especially in the form of machine learning, is lazy. “Think about being lazy as this kind of smart student who doesn’t really want to study for an exam. Instead, what he does is just study all the past years’ exams and just look for patterns. Instead of trying to actually learn, he just tries to pass the test. And this is exactly the same way in which current AI is lazy.”

    A machine-learning model might recognize grazing sheep, for instance, simply by picking out pictures that have green grass in them. If a model is trained to identify fish from photos of anglers proudly displaying their catches, Madry explained, “the model figures out that if there’s a human holding something in the picture, I will just classify it as a fish.” The consequences can be more serious for an AI model intended to pick out malignant tumors. If the model is trained on images containing rulers that indicate the size of tumors, the model may end up selecting only those photos that have rulers in them.

    This leads to Madry’s biggest concerns about AI in its present form. “AI is beating us now,” he noted. “But the way it does it [involves] a little bit of cheating.” He fears that we will apply AI “in some way in which this mismatch between what the model actually does versus what we think it does will have some catastrophic consequences.” People relying on AI, especially in potentially life-or-death situations, need to be much more mindful of its current limitations, Madry cautioned.

    There were 10 speakers altogether, and the last to take the stage was MIT associate professor of electrical engineering and computer science and CSAIL principal investigator Marzyeh Ghassemi, who laid out her vision for how AI could best contribute to general health and well-being. But in order for that to happen, its models must be trained on accurate, diverse, and unbiased medical data.

    It’s important to focus on the data, Ghassemi stressed, because these models are learning from us. “Since our data is human-generated … a neural network is learning how to practice from a doctor. But doctors are human, and humans make mistakes. And if a human makes a mistake, and we train an AI from that, the AI will, too. Garbage in, garbage out. But it’s not like the garbage is distributed equally.”

    She pointed out that many subgroups receive worse care from medical practitioners, and members of these subgroups die from certain conditions at disproportionately high rates. This is an area, Ghassemi said, “where AI can actually help. This is something we can fix.” Her group is developing machine-learning models that are robust, private, and fair. What’s holding them back is neither algorithms nor GPUs. It’s data. Once we collect reliable data from diverse sources, Ghassemi added, we might start reaping the benefits that AI can bring to the realm of health care.

    In addition to CSAIL speakers, there were talks from members across MIT’s Institute for Data, Systems, and Society; the MIT Mobility Initiative; the MIT Media Lab; and the SENSEable City Lab.

    The proceedings concluded on that hopeful note. Rus and Werner then thanked everyone for coming. “Please continue to reflect about the good and bad of computing,” Rus urged. “And we look forward to seeing you back here in May for the next TEDxMIT event.”

    The exact theme of the spring 2022 gathering will have something to do with “superpowers.” But — if December’s mind-bending presentations were any indication — the May offering is almost certain to give its attendees plenty to think about. And maybe provide the inspiration for a startup or two. More

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    Meet the 2021-22 Accenture Fellows

    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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    Exploring the human stories behind the data

    Shaking in the back of a police cruiser, handcuffs digging into his wrists, Brian Williams was overwhelmed with fear. He had been pulled over, but before he was asked for his name, license, or registration, a police officer ordered him out of his car and into back of the police cruiser, saying into his radio, “Black male detained.” The officer’s explanation for these actions was: “for your safety and mine.”

    Williams walked away from the experience with two tickets, a pair of bruised wrists, and a desire to do everything in his power to prevent others from experiencing the utter powerlessness he had felt.

    Now an MIT senior majoring in biological engineering and minoring in Black studies, Williams has continued working to empower his community. Through experiences in and out of the classroom, he has leveraged his background in bioengineering to explore interests in public health and social justice, specifically looking at how the medical sector can uplift and support communities of color.

    Williams grew up in a close-knit family and community in Broward County, Florida, where he found comfort in the routine of Sunday church services, playing outside with friends, and cookouts on the weekends. Broward County was home to him — a home he felt deeply invested in and indebted to.

    “It takes a village. The Black community has invested a lot in me, and I have a lot to invest back in it,” he says.

    Williams initially focused on STEM subjects at MIT, but in his sophomore year, his interests in exploring data science and humanities research led him to an Undergraduate Research Opportunities Program (UROP) project in the Department of Political Science. Working with Professor Ariel White, he analyzed information on incarceration and voting rights, studied the behavior patterns of police officers, and screened 911 calls to identify correlations between how people described events to how the police responded to them.

    In the summer before his junior year, Williams also joined MIT’s Civic Data Design Lab, where he worked as a researcher for the Missing Data Project, which uses both journalism and data science to visualize statistics and humanize the people behind the numbers. As the project’s name suggests, there is often much to be learned from seeking out data that aren’t easily available. Using datasets and interviews describing how the pandemic affected Black communities, Williams and a team of researchers created a series called the Color of Covid, which told the stories behind the grim statistics on race and the pandemic.

    The following year, Williams undertook a research-and-development internship with the biopharmaceutical company Amgen in San Francisco, working on protein engineering to combat autoimmune diseases. Because this work was primarily in the lab, focusing on science-based applications, he saw it as an opportunity to ask himself: “Do I want to dedicate my life to this area of bioengineering?” He found the issue of social justice to be more compelling.

    At the same time, Williams was drawn toward tackling problems the local Black community was experiencing related to the pandemic. He found himself thinking deeply about how to educate the public, address disparities in case rates, and, above all, help people.

    Working through Amgen’s Black Employee Resource Group and its Diversity, Inclusion, and Belonging Team, Williams crafted a proposal, which the company adopted, for addressing Covid-19 vaccination misinformation in Black and Brown communities in San Mateo and San Francisco County. He paid special attention to how to frame vaccine hesitancy among members of these communities, understanding that a longstanding history of racism in scientific discovery and medicine led many Black and Brown people to distrust the entire medical industry.

    “Trying to meet people where they are is important,” Williams says.

    This experience reinforced the idea for Williams that he wanted to do everything in his power to uplift the Black community.

    “I think it’s only right that I go out and I shine bright because it’s not easy being Black. You know, you have to work twice as hard to get half as much,” he says.

    As the current political action co-chair of the MIT Black Students’ Union (BSU), Williams also works to inspire change on campus, promoting and participating in events that uplift the BSU. During his Amgen internship, he also organized the MIT Black History Month Takeover Series, which involved organizing eight events from February through the beginning of spring semester. These included promotions through social media and virtual meetings for students and faculty. For his leadership, he received the “We Are Family” award from the BSU executive board.

    Williams prioritizes community in everything he does, whether in the classroom, at a campus event, or spending time outside in local communities of color around Boston.

    “The things that really keep me going are the stories of other people,” says Williams, who is currently applying to a variety of postgraduate programs. After receiving MIT endorsement, he applied to the Rhodes and Marshall Fellowships; he also plans to apply to law school with a joint master’s degree in public health and policy.

    Ultimately, Williams hopes to bring his fight for racial justice to the policy level, looking at how a long, ongoing history of medical racism has led marginalized communities to mistrust current scientific endeavors. He wants to help bring about new legislation to fix old systems which disproportionately harm communities of color. He says he aims to be “an engineer of social solutions, one who reaches deep into their toolbox of social justice, pulling the levers of activism, advocacy, democracy, and legislation to radically change our world — to improve our social institutions at the root and liberate our communities.” While he understands this is a big feat, he sees his ambition as an asset.

    “I’m just another person with huge aspirations, and an understanding that you have to go get it if you want it,” he says. “You feel me? At the end of the day, this is just the beginning of my story. And I’m grateful to everyone in my life that’s helping me write it. Tap in.” More

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    MIT welcomes nine MLK Visiting Professors and Scholars for 2021-22

    In its 31st year, the Martin Luther King Jr. (MLK) Visiting Professors and Scholars Program will host nine outstanding scholars from across the Americas. The flagship program honors the life and legacy of Martin Luther King Jr. by increasing the presence and recognizing the contributions of underrepresented minority scholars at MIT. Throughout the year, the cohort will enhance their scholarship through intellectual engagement with the MIT community and enrich the cultural, academic, and professional experience of students.

    The 2021-22 scholars

    Sanford Biggers is an interdisciplinary artist hosted by the Department of Architecture. His work is an interplay of narrative, perspective, and history that speaks to current social, political, and economic happenings while examining their contexts. His diverse practice positions him as a collaborator with the past through explorations of often-overlooked cultural and political narratives from American history. Through collaboration with his faculty host, Brandon Clifford, he will spend the year contributing to projects with Architecture; Art, Culture and Technology; the Transmedia Storytelling initiatives; and community workshops and engagement with local K-12 education.

    Kristen Dorsey is an assistant professor of engineering at Smith College. She will be hosted by the Program in Media Arts and Sciences at the MIT Media Lab. Her research focuses on the fabrication and characterization of microscale sensors and microelectromechanical systems. Dorsey tries to understand “why things go wrong” by investigating device reliability and stability. At MIT, Dorsey is interested in forging collaborations to consider issues of access and equity as they apply to wearable health care devices.

    Omolola “Lola” Eniola-Adefeso is the associate dean for graduate and professional education and associate professor of chemical engineering at the University of Michigan. She will join MIT’s Department of Chemical Engineering (ChemE). Eniola-Adefeso will work with Professor Paula Hammond on developing electrostatically assembled nanoparticle coatings that enable targeting of specific immune cell types. A co-founder and chief scientific officer of Asalyxa Bio, she is interested in the interactions between blood leukocytes and endothelial cells in vessel lumen lining, and how they change during inflammation response. Eniola-Adefeso will also work with the Diversity in Chemical Engineering (DICE) graduate student group in ChemE and the National Organization of Black Chemists and Chemical Engineers.

    Robert Gilliard Jr. is an assistant professor of chemistry at the University of Virginia and will join the MIT chemistry department, working closely with faculty host Christopher Cummins. His research focuses on various aspects of group 15 element chemistry. He was a founding member of the National Organization of Black Chemists and Chemical Engineers UGA section, and he has served as an American Chemical Society (ACS) Bridge Program mentor as well as an ACS Project Seed mentor. Gilliard has also collaborated with the Cleveland Public Library to expose diverse young scholars to STEM fields.

    Valencia Joyner Koomson ’98, MNG ’99 will return for the second semester of her appointment this fall in MIT’s Department of Electrical Engineering and Computer Science. Based at Tufts University, where she is an associate professor in the Department of Electrical and Computer Engineering, Koomson has focused her research on microelectronic systems for cell analysis and biomedical applications. In the past semester, she has served as a judge for the Black Alumni/ae of MIT Research Slam and worked closely with faculty host Professor Akintunde Akinwande.

    Luis Gilberto Murillo-Urrutia will continue his appointment in MIT’s Environmental Solutions Initiative. He has 30 years of experience in public policy design, implementation, and advocacy, most notably in the areas of sustainable regional development, environmental protection and management of natural resources, social inclusion, and peace building. At MIT, he has continued his research on environmental justice, with a focus on carbon policy and its impacts on Afro-descendant communities in Colombia.

    Sonya T. Smith was the first female professor of mechanical engineering at Howard University. She will join the Department of Aeronautics and Astronautics at MIT. Her research involves computational fluid dynamics and thermal management of electronics for air and space vehicles. She is looking forward to serving as a mentor to underrepresented students across MIT and fostering new research collaborations with her home lab at Howard.

    Lawrence Udeigwe is an associate professor of mathematics at Manhattan College and will join MIT’s Department of Brain and Cognitive Sciences. He plans to co-teach a graduate seminar course with Professor James DiCarlo to explore practical and philosophical questions regarding the use of simulations to build theories in neuroscience. Udeigwe also leads the Lorens Chuno group; as a singer-songwriter, his work tackles intersectionality issues faced by contemporary Africans.

    S. Craig Watkins is an internationally recognized expert in media and a professor at the University of Texas at Austin. He will join MIT’s Institute for Data, Systems, and Society to assist in researching the role of big data in enabling deep structural changes with regard to systemic racism. He will continue to expand on his work as founding director of the Institute for Media Innovation at the University of Texas at Austin, exploring the intersections of critical AI studies, critical race studies, and design. He will also work with MIT’s Center for Advanced Virtuality to develop computational systems that support social perspective-taking.

    Community engagement

    Throughout the 2021-22 academic year, MLK professors and scholars will be presenting their research at a monthly speaker series. Events will be held in an in-person/Zoom hybrid environment. All members of the MIT community are encouraged to attend and hear directly from this year’s cohort of outstanding scholars. To hear more about upcoming events, subscribe to their mailing list.

    On Sept. 15, all are invited to join the Institute Community and Equity Office in welcoming the scholars to campus by attending a welcome luncheon. More