Ioannis Mitliagkas is an Assistant Professor in the department of Computer Science and Operations Research (DIRO) at the University of Montréal, as well as a member of MILA and a Canadian CIFAR AI chair holder. Before that, he was a Postdoctoral Scholar with the departments of Statistics and Computer Science at Stanford University. He obtained his PhD from the department of Electrical and Computer Engineering at The University of Texas at Austin. His research includes topics in optimization, dynamics and learning, with a focus on modern machine learning. His work currently focuses on the intersection of ML, game theory and applications in causal inference, domain adaptation and generative models. He has also done work on MCMC methods, efficient large-scale and distributed algorithms, and topics of generalization and domain adaptation. In the past he has worked on high-dimensional streaming problems and fast algorithms and computation for large graph problems.