Mikhail Belkin

Associate Professor; Computer Science & Engineering, College of Engineering, and Statistics, College of Arts and Sciences; Executive Committee Member, Center for Cognitive Science

Dr. Belkin’s research focuses on designing and analyzing practical algorithms for machine learning based on non-linear structure of high dimensional data, in particular manifold and spectral methods. He is also interested in a range of theoretical questions concerning the computational and statistical limits of learning and in the mathematical foundations of learning structure from data.

I specialize in

PhD, Mathematics, University of Chicago
MSc, Mathematics, University of Chicago
HonBSc with High Distinction, Mathematics, University of Toronto