Siamak Ravanbakhsh
Core Academic Member
Canada CIFAR AI Chair
Assistant Professor, McGill University, School of Computer Science
Research Topics
Causality
Deep Learning
Dynamical Systems
Generative Models
Graph Neural Networks
Information Theory
Learning on Graphs
Machine Learning Theory
Molecular Modeling
Probabilistic Models
Reasoning
Reinforcement Learning
Representation Learning
Biography
Siamak Ravanbakhsh is an assistant professor at McGill University’s School of Computer Science and a core academic member of Mila – Quebec Artificial Intelligence Institute.
Before joining McGill and Mila, he held a similar position at the University of British Columbia. Prior to that, he was a postdoctoral fellow at the Machine Learning Department and Robotics Institute of Carnegie Mellon University. He completed his PhD at the University of Alberta.
Ravanbakhsh’s research is centred around problems of representation learning, in particular the principled use of geometry, probabilistic inference and symmetry.