Nisarg Shah

Nisarg Shah is an Associate Professor in the Department of Computer Science at the University of Toronto, part of the Theory Group. He also serves as a Research Lead at the Schwartz Reisman Institute for Technology and Society and a Faculty Affiliate at the Vector Institute for Artificial Intelligence. His research focuses on developing theoretical foundations for AI systems, particularly in algorithmic fairness, social choice theory, game theory, and mechanism design. He co-developed Spliddit.org, a not-for-profit platform aiding fair decision-making for over 250,000 users.

Shah's work bridges computer science with economics, political science, and cognitive psychology. Recent research emphasizes fairness in AI across domains like voting, resource allocation, and recommendation systems. His 2025 AAAI paper on distortion minimization received an Outstanding Paper Award, and his 2016 work on maximum Nash welfare won the 2024 Kalai Prize. He has supervised numerous collaborative projects in fair division, public policy, and multi-agent systems.

Key affiliations include Vector Institute (AI), Schwartz Reisman Institute (Society-Impact Technology), and the Theory Group (Computer Science). His research portfolio spans over 80 publications in top venues like AAAI, NeurIPS, EC, and IJCAI, addressing both foundational theory and practical applications of fair and strategic AI systems.