Michael Kearns

Michael Kearns is a Professor and National Center Chair in the Department of Computer and Information Science at the University of Pennsylvania. He serves as the Founding Director of the Warren Center for Network and Data Sciences and founded the Networked and Social Systems Engineering (NETS) program. He holds secondary appointments in Economics, Statistics and Data Science (Wharton), and Operations, Information and Decisions (Wharton). Since 2020, he has been an Amazon Scholar at Amazon Web Services, focusing on responsible AI.

He received his undergraduate degree in mathematics and computer science from the University of California, Berkeley (1985) and a Ph.D. in computer science from Harvard University (1989).

Kearns' research integrates theoretical computer science with empirical applications in:

• Machine Learning & AI: Algorithmic fairness, privacy, and reinforcement learning.
• Algorithmic Game Theory: Microeconomic modeling and strategic behavior in networks.
• Computational Social Science: Social network dynamics and information aggregation.
• Quantitative Finance: Algorithmic trading and market microstructure.

His work bridges mathematical rigor with real-world impact, including human-subject experiments and financial applications.

His recent publications emphasize algorithmic ethics, with themes like fairness in machine learning, privacy attacks (e.g., reconstruction and membership inference), and model disgorgement. Trends show a focus on reinforcement learning scalability, ensemble methods, and mitigating biases in generative AI.

Awards & Honors:

• National Academy of Sciences (2020)
• ACM Fellow (2014)
• Best Paper Awards (Journal of Trading, UAI, COLT)
• George H. Heilmeier Faculty Award (2005)
• Elected to American Academy of Arts and Sciences, AAAI, and Economic Theory Society

Advising & Grants: He mentors doctoral and master's students, often collaborating with Aaron Roth. His group investigates fairness, privacy, and game theory, supported by institutional and industry partnerships (e.g., Amazon, NSF).

Labs & Teams: He directs the Warren Center for Network and Data Sciences, fostering interdisciplinary research. His lab includes doctoral students and postdocs working on algorithmic accountability, network science, and AI ethics.