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MD4SG

Mechanism Design for Social Good Research Group

Members



Organizers


Rediet Abebe, Cornell University


Rediet Abebe is a PhD student in the Department of Computer Science at Cornell University, advised by Jon Kleinberg. Her research focuses on algorithms, computational social science, and social networks. In particular, she is interested in using insights from theoretical computer science to better understand and implement interventions in socioeconomic inequality and opinion dynamics. She is the 2016 recipient of the Google Generation Scholarship. Prior to Cornell, she completed a B.A. in Mathematics from Harvard University, an M.A. in Mathematics from the University of Cambridge, and an M.S. in Applied Mathematics from Harvard University. She was born and raised in Addis Ababa, Ethiopia.



Kira Goldner, University of Washington


Kira Goldner is a fourth-year PhD student in Computer Science and Engineering at the University of Washington, advised by Anna Karlin. Her research focuses on problems in mechanism design, particularly in maximizing revenue in settings that are motivated by practice, such as those where buyer distributions are unknown or buyers are risk-averse. She is also beginning to work on mechanism design within health insurance. She is a 2017 recipient of the Microsoft Research PhD Fellowship and was a 2016 recipient of a Google Anita Borg Scholarship. Kira received her B.A. in Mathematics from Oberlin College and also studied at Budapest Semesters in Mathematics.



Participants


Ellora Derenoncourt, Harvard University


Ellora Derenoncourt is a graduate student in economics at Harvard University, specializing in public and labor economics, economic history, and microeconomic theory. Her research employs a range of methods to understand the determinants of current and historical inequality, including field experimental and theoretical work on firms and fairness and analyses of historical data on economic mobility and racial inequality.



Alon Eden, Tel Aviv University


Alon Eden is a PhD student in the Computer Science department at Tel Aviv University. He is advised by Amos Fiat and Michal Feldman. His research interests have focused on algorithmic game theory, and mainly pricing algorithms. In particular, he is interested in finding out whether resources can be allocated efficiently using prices when agents are selfish and arriving online.



Lily Hu, Harvard University


Lily Hu is a second-year PhD student in applied mathematics at Harvard University where she is advised by Yiling Chen and works on algorithmic fairness and ethics in artificial intelligence. Broadly, her academic interests include algorithmic game theory, statistical inference, and theories of justice. Her current time is divided between economics/computer science research, where she studies fairness in algorithmic settings, and philosophy/ethics work, where she considers algorithmic fairness as it relates to notions of procedural, substantive, and distributive justice. Lily graduated from Harvard College in 2015 with an A.B. in Mathematics.



Anna Karlin, University of Washington


Anna R. Karlin is the Microsoft Professor of Computer Science and Engineering at the University of Washington. Her research is primarily in theoretical computer science: algorithmic game theory, and the design and analysis of algorithms, particularly probabilistic and online algorithms. She is an ACM Fellow and a Fellow of the American Academy of Arts and Sciences.



Jon Kleinberg, Cornell University


Jon Kleinberg is the Tisch University Professor of Computer Science and Information Science at Cornell University. His research focuses on algorithmic issues at the interface of networks and information, with an emphasis on the social and information networks that underpin the Web and other on-line media. He is a member of the National Academy of Sciences and the National Academy of Engineering.



Irene Lo, Columbia University


Irene Lo is a fifth-year Ph.D. student in the IEOR Department at Columbia University. Her main research areas are in the intersection of operations research, computer science and economics. In particular, she is interested in how to optimally allocate scarce resources while incorporating the preferences of strategic agents, and in developing mathematical and algorithmic tools to answer this question. She currently works in matching market design, with a focus on school choice mechanisms. Irene graduated from Princeton University in 2013 with an A.B. in mathematics.



Manish Raghavan, Cornell University


Manish Raghavan is a second-year PhD student at Cornell advised by Jon Kleinberg. He studies human decision-making and behavioral biases using techniques from theoretical computer science. He also works on understanding the effects that algorithmic decision-making has on society, focusing on fairness in machine learning. He received his B.S. from UC Berkeley in Electrical Engineering and Computer Science in 2016, and he is a recipient of an NSF GRFP fellowship.



Sam Taggart, Northwestern University


Sam Taggart is a fifth-year doctoral student in theoretical computer science at Northwestern University, advised by Jason Hartline. His research interests in economic design are broad. Specific focuses include the analysis of auctions where bidders are incentivized to bid strategically rather than reporting according to their true preferences, and learning in economic settings - both understanding the consequences of information sources being strategic, developing tools to learn better mechanisms from data. Sam has bachelors degrees in mathematics and violin performance from Oberlin College. He will join the Oberlin computer science department as an assistant professor next year.



Dan Waldinger, MIT


Dan Waldinger is a graduate student in economics at MIT doing research in empirical market design. His work focuses the allocation of organs and public housing (fortunately they are allocated separately), and quantifies how waiting times provide incentives to economic agents in these dynamic mechanisms. Before graduate school, he lived in Cairo and worked at Microsoft Research after graduating from the University of Chicago. He grew up in Newton, MA.



Matt Weinberg, Princeton University


Matt Weinberg is an Assistant Professor of computer science at Princeton University. His research focuses on algorithmic mechanism design, including multidimensional auctions. His thesis on this topic was awarded the ACM SIGecom doctoral dissertation award. More recently, he's additionally working on mechanism design for cryptocurrencies and social good domains.