Dr. Michael Kearns

Biography

Michael Kearns is a Professor in the Department of Computer Science at the University of Pennsylvania. His research interests lie primarily in the areas of Machine Learning, Algorithmic Game Theory, Network Science, Computational Social Science, and Algorithmic Trading. He has published extensively in these fields, with influential works on the theoretical aspects of learning algorithms and their real-world applications. Kearns has contributed to the development of methods for ensuring fairness in machine learning and the auditing of algorithms in judicial contexts. He is also recognized for his work on reinforcement learning and the application of these techniques to economic and social issues. Kearns has a notable academic lineage, having published articles in prestigious journals and international conferences. His scholarly contributions have significantly impacted various domains, harnessing computational depth and social implications to inform algorithm design and analysis. As a leading figure in his field, Kearns continues to engage in research that combines theoretical advancements with practical applications of machine learning and game theory, aiming to address contemporary challenges in technology and society.

Research Interests