April 2021 : Our workshop proposal "Theory of Continual Learning" for ICML 2021 has been accepted !
January 2021 : Paper accepted at AISTATS 2021 A Theoretical Analysis of Catastrophic Forgetting through the NTK Overlap Matrix
January 2021 : Paper accepted at ICLR 2021 Regularized Inverse Reinforcement Learning
December 2020 : Our workshop proposal "Self-Supervised learning for Reinforcement Learning" for ICLR 2021 has been accepted !
November 2020 : Prepint Generalisation guarantees for continual learning with orthogonal gradient descent
October 2020 : Paper accepted at Neurips 2020 Deep RL workshop Domain Adversarial Reinforcement Learning
September 2020 : Paper accepted at Neurips 2020 Deep Reinforcement and InfoMax Learning [Poster]
I am a postdoctoral researcher @ McGill University and Mila (Quebec AI Institute) under supervision of Professor Joelle Pineau. My interests span representation and reinforcement learning, generative models and continual learning. I dedicated a part of my research investigating robust representation methods for better generalization in reinforcement learning. My other stream of focus seeks better understanding of Catastrophic Forgetting and Inference.
I earned my PhD in Operations Management from McGill University, focusing my research in exploration problems for Deep Reinforcement Learning and Generative models (GANs). Prior to this, I completed a French mechanical engineering degree from Arts et Metiers ParisTech with a master degree (MSc) in Mathematical Modeling at University College London.
PhD in Operation Management, 2019
McGill University, Canada
MSc in Mathematical Modeling, 2013
University College London, UK
Mechanical Engineering Degree, 2013
Arts et Metiers ParisTech, France