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About the speaker: Nisheeth K. Vishnoi is the A. Bartlett Giamatti Professor of Computer Science at Yale University, where his work spans Theoretical Computer Science, Optimization, and Artificial Intelligence. He aims to tackle some of the most pressing and complex problems at the intersection of computation and society.His research addresses foundational questions in algorithmic fairness, privacy, and decision-making, particularly in settings where algorithms interact with human judgment, institutional processes, and social norms. This includes mathematical models of bias and strategic behavior in selection and evaluation systems, as well as the design of equitable, accountable, and privacy-preserving mechanisms. He has also developed theoretical tools for efficient learning and inference in foundation models, especially in geometrically structured spaces.

More recently, his work has focused on developing theoretical frameworks to understand how modern AI systems—such as large language models—reshape work, learning, science, and societal systems. This line of research studies how AI alters skill formation, decision structures, and human-AI collaboration, and explores principles for building computational systems that preserve human agency, accountability, and interpretability.At Yale, he co-founded the Computation and Society Initiative and is affiliated with the Cowles Foundation for Research in Economics, the Institution for Social and Policy Studies, and the Thurman Arnold Project at the Yale School of Management. He is a co-PI of the NSF-funded AI Institute for Learning-enabled Optimization at Scale and has served on the Yale AI Task Force.

He is a Fellow of the ACM, IEEE, and the American Mathematical Society, and the recipient of multiple best paper awards for his research. He also writes the Substack The Intelligence Loop (https://nisheethvishnoi.substack.com/), where he explores the nature of intelligence, the limits of optimization-driven AI, and the cultural and philosophical implications of computation.