Michal Derezinski

Michał Dereziński is an Assistant Professor of Computer Science and Engineering at the University of Michigan. Previously, he was a postdoctoral fellow in the Department of Statistics at the University of California, Berkeley, and a research fellow at the Simons Institute for the Theory of Computing. Michał obtained his Ph.D. in Computer Science at the University of California, Santa Cruz, where he received the Best Dissertation Award for his work on sampling methods in statistical learning. Michał's current research is focused on theoretical foundations of randomized algorithms for machine learning, optimization, and applied mathematics. In particular, his work in the area of Randomized Numerical Linear Algebra was funded by an NSF CAREER Award, and received the Best Paper Award at the 34th Conference on Neural Information Processing Systems (NeurIPS).