Matus Telgarsky obtained his PhD in Computer Science from UCSD in 2013, under Sanjoy Dasgupta. While there, his research focused primarily upon optimization and statistical aspects of unconstrained and unregularized algorithms (e.g., boosting), and to a lesser extent, clustering. He then served as a postdoctoral researcher at Rutgers University and the University of Michigan, as well as a consulting researcher at Microsoft Research in New York City. Since fall 2016, he has been an assistant professor at the University of Illinois, Urbana-Champaign. His most recent interests are representation and nonconvex optimization.