Marc Gendron-Bellemare

Core Industry Member

Canada CIFAR AI Chair

Adjunct professor, McGill University, School of Computer Science

Adjunct Professor, Université de Montréal, Department of Computer Science and Operations Research

Chief Scientific Officer, Reliant AI

Research Topics

Large Language Models (LLM)

Reinforcement Learning

Representation Learning

Biography

I am Chief Scientific Officer at Reliant AI and an adjunct professor at McGill University and Université de Montréal. My journey in AI has taken me from leading the reinforcement learning team at Google Brain in Montréal to being part of the pioneering research group at DeepMind in the U.K. I earned my PhD at the University of Alberta, where I was fortunate to work under the guidance of Michael Bowling and Joel Veness.

My research is driven by a fascination with how machines can learn and adapt. I’ve worked on projects like the Arcade Learning Environment, which helped shape the field of deep reinforcement learning, and developed approaches like distributional RL and curiosity-driven agents. These ideas have even found their way into real-world applications, like steering Loon’s stratospheric balloons.

At the heart of my work is a passion for building AI that is not only scientifically rigorous but also genuinely useful. I feel incredibly lucky to collaborate with brilliant minds who share this vision, and I’m excited to keep exploring what’s possible in AI.