Organizers
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Executive Chairs
Prajna is an S.M. student in the Technology and Policy Program and EECS. Her research interests are broadly in the evaluation of algorithmic systems, both from a technical and regulatory perspective, algorithmic fairness and tools which facilitate the development of safer and more trustworthy AI. Prior to MIT, Prajna graduated from NYU Abu Dhabi in 2020 and was awarded the Post-graduate Research Fellow at NYU Abu Dhabi where she investigated bias propagation in recommender systems.
Marilena Velonia Bellonia is a Graduate student at the MIT Technology and Policy Program. She is interested in Artificial Intelligence, Data, Internet and Industrial policy. Before MIT, she studied Management Science and Technology at the Athens University of Economics and Business and was working in the Technology sector in Greece.
Deepika is a graduate student in MIT’s Technology and Policy Program. Her research focuses on the responsible and equitable design of emerging technologies and public digital goods. Previously, Deepika worked with NITI Aayog and the Ministry of Electronics and IT, Government of India as a project lead with the University of Chicago's International Innovation Corps. Her work has ranged from creating enabling pathways for women's entrepreneurship to data governance, digital transformation, and AI policy. She is an engineer from Anna University and a Young India Fellow from Ashoka University, India.
Aurora is a PhD student in IDSS. Her current research focus is on algorithmic fairness and equity in loan approval algorithms, and she is broadly interested in ethical decision making, mechanism design, and dynamic models of structural inequality applied to urban studies and housing. Before MIT, she graduated from Pomona College and worked for a year in economic consulting.
Taylor Lynn is an S.M. candidate in technology and policy. Prior to her current degree, she obtained a bachelor of software engineering with a minor in political science from McGill University in Montréal, Canada. Her research interests include the effectiveness of governance surrounding large, generative models, quantifying the societal impact of AI, and more generally the regulatory frameworks that function in the technology space.
### Past Organizers
Andy Haupt is an interdisciplinary Ph.D. Candidate with the Schwarzman College of Computing. He uses tools from Microeconomic Theory to understand multi-agent systems, recommendation engines, and automatic pricing tools in deployment and propose ways to mitigate undesirable consequences of seemingly innocuous algorithmic choices.
Annie Snyder is an undergraduate studying Computer Science and Economics at MIT. She's currently exploring equitable design in tech and how to effectively implement these practices in industry, as well as working on engaging undergrads in careers for social good. Annie has previously worked on Internet Policy with the Knesset, Responsible AI at Facebook, and on unions and employment research at MIT.
Sarah Cen is a PhD student in Computer Science at MIT. She studies machine learning theory through the lens of social good. Her current projects include works on social media regulation, matching markets with learning, fairness in recommendation systems, and feedback loops in data-driven algorithms. Sarah has previously worked on autonomous vehicles, communication networks, reinforcement learning, and robotics.
Rui-Jie Yew is an S.M. student studying the legal and human-centered aspects of computation in the Technology and Policy Program. She has worked on research projects involving the design and analysis of regulation for emerging technologies, as well as the operationalization of legal values for technical systems.
Marla Evelyn is an undergraduate studying computer science, economics, and math at MIT. She is a researcher at the MIT Computer Science and Artificial Intelligence Laboratory studying interpretable and explainable machine learning algorithms. Previously, she has done research at the Brookings Institution and the MIT Media Lab. Outside of class and research, Marla enjoys rowing, baking, and playing board games.
Riana Shah is a concurrent degree student at MIT and Harvard studying business and public policy. With her background in tech and sociology, she built an Ed tech startup that has done work in over 19 cities across 11 countries. She is now building Ethix.AI that combats algorithmic bias to fight systematic racism in tech.
Harini Suresh is PhD student in computer science at MIT. She is particularly interested in studying how complications arise when machine learning is used with imperfect real-world data, and building tools that surface possible concerns to end users. She did her undergrad and M.Eng. at MIT as well, and worked on developing interpretable methods for predicting onset and weaning of invasive interventions for patients in Intensive Care Units. She has spent summers working at Google Brain, Jawbone, and Zephyr Health. Outside of research, she loves doing aerial arts, baking all kinds of things, and reading.
Irene Chen is a PhD student in computer science at MIT, advised by David Sontag in the Clinical Machine Learning group. She works on machine learning methods to advance understanding of health and reduce inequality. Prior to MIT, she completed a joint AB/SM degree at Harvard. She also worked at Dropbox as a data scientist, machine learning engineer, and chief of staff.
Leilani H. Gilpin is a PhD student in Electrical Engineering and Computer Science at MIT. Her area of focus is explanatory artificial intelligence, which enables autonomous vehicles, and other autonomous machines to explain themselves. She is currently working on a Toyota Research Initiative Project, “The Car Can Explain!” in the Computer Science and Artificial Intelligence Lab under the supervision of Professor Gerald Jay Sussman. Before returning to academia, Leilani worked at Palo Alto Research Center (PARC) and earned a M.S. from Stanford University and a B.S. in Mathematics (with honors), B.S. in Computer Science (with highest honors), and a music minor from UC San Diego in 2011.
Milo Phillips-Brown is a Postdoctoral Associate in the Ethics of Technology at MIT Philosophy and a Research Fellow in Digital Ethics at the Jain Family Institute. He studies the ethical and social justice implications of technology and teaches ethical engineering practices to computer scientists.