Portrait of Ioannis Mitliagkas

Ioannis Mitliagkas

Core Academic Member
Canada CIFAR AI Chair
Associate Professor, Université de Montréal, Department of Computer Science and Operations Research
Research Scientist, Google DeepMind
Research Topics
Deep Learning
Distributed Systems
Dynamical Systems
Generative Models
Machine Learning Theory
Optimization
Representation Learning

Biography

Ioannis Mitliagkas (Γιάννης Μητλιάγκας) is an associate professor in the Department of Computer Science and Operations Research (DIRO) at Université de Montréal, as well as a Core Academic member of Mila – Quebec Artificial Intelligence Institute and a Canada CIFAR AI Chair. He holds a part-time position as a staff research scientist at Google DeepMind Montréal.

Previously, he was a postdoctoral scholar in 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 machine learning, with emphasis on optimization, deep learning theory, statistical learning. His recent work includes methods for efficient and adaptive optimization, studying the interaction between optimization and the dynamics of large-scale learning systems and the dynamics of games.

Current Students

Research Intern - Université de Montréal
Collaborating Alumni - Université de Montréal
Co-supervisor :
PhD - Université de Montréal
Principal supervisor :
Professional Master's - Université de Montréal
PhD - Université de Montréal
PhD - Université de Montréal
Principal supervisor :
Collaborating researcher - Université de Montréal
Principal supervisor :
Master's Research - Université de Montréal

Publications

Deep Learning @15 Petaflops/second: Semi-supervised pattern detection for 15 Terabytes of climate data
W. Collins
M. Wehner
M. Prabhat
Thorsten Kurth
Nadathur Satish
Jie Zhang
Evan Racah
Md. Mostofa Ali Patwary
Narayanan Sundaram
Pradeep Dubey