2016 Victor Lesser Distinguished Dissertation Award
Center for Research on Computation and Society (CRCS), Harvard University (Postdoc fellow)
Thesis developed at Carnegie Mellon University (Advisor: Ariel Procaccia)
Title: Optimal Social Decision Making
ABSTRACT: How can computers help ordinary people make collective decisions about real-life dilemmas, like which restaurant to go to with friends, or even how to divide an inheritance? In this talk, I will present an optimization-driven approach that draws on ideas from AI, theoretical computer science, and economic theory, and illustrate it through my research in computational social choice and computational fair division. In both areas, I will make a special effort to demonstrate how fundamental theoretical questions underlie the design and implementation of deployed services — Spliddit.org and RoboVote.org — that are already used by more than a hundred thousand people.
SHORT BIO: Nisarg Shah is currently a postdoctoral fellow at the Center for Research on Computation and Society (CRCS) at Harvard University. He received his Ph.D. from Carnegie Mellon University, where he was advised by Ariel Procaccia. He will join the University of Toronto as an Assistant Professor in August 2017. He is broadly interested in algorithmic economics - theory and applications. His research has focused on topics such as computational social choice, fair division, game theory, peer prediction, and prediction markets. Nisarg is the winner of the 2013-2014 Hima and Jive Graduate Fellowship, the 2014-2015 Facebook Fellowship, and the 2016 Victor Lesser Distinguished Dissertation Award.