Ioannis Mitliagkas
Local 3359, Pav. Andre-Aisenstadt

Ioannis Mitliagkas is an assistant professor in the Department of Computer Science and Operations Research (DIRO) at the University of Montreal. Before that, he was a Postdoctoral Scholar with the Department of Statistics and Computer Science at Stanford University. He obtained his Ph.D. from the Department of Electrical and Computer Engineering at the University of Texas at Austin. His research focuses on broad-scale statistical learning and inference problems, focusing on efficient broad-scale and distributed algorithms, and the tight theoretical and data-dependent guarantees and tuning complex systems.His recent work includes understanding and optimizing the scanning used in Gibbs sampling for inference, as well as understanding the interaction between optimization and the dynamics of large-scale learning systems.