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Nisarg Shah is an Associate Professor in the Department of Computer Science at the University of Toronto, and is a part of the Theory Group. He leads research focused on developing the theoretical foundations of artificial intelligence (AI) systems, utilizing insights from multiple disciplines including computer science, economics, political science, philosophy, and cognitive psychology. His work aims to design AI systems that can aggregate individual preferences to make collective decisions, as well as to ensure that self-interested agents behave appropriately within these systems. This includes exploring concepts from social choice theory and game theory, and designing robust AI systems in the presence of strategic agents through mechanism design. Recently, he has significantly concentrated on the issue of algorithmic fairness in AI systems, proposing robust fairness definitions that can be meaningfully and non-trivially applied across a broad range of decision-making settings such as voting, resource allocation, conference peer reviewing, and recommender systems. Additionally, he co-developed the non-profit website Spliddit.org, which has assisted over 250,000 people in making provably fair decisions in their daily lives.
Department of Sociology