Hello, I am a Postdoctoral Scholar at Stanford Artificial Intelligence Laboratory where I work with Emma Brunskill. I am particularly interested in Offline Reinforcement Learning and Deep RL.
I did my PhD at Inria where I worked on sample-efficient Deep RL for control, exploration and safety. I graduated from DTU (machine learning, deep learning, HPC) and École Centrale (advanced probabilities, software engineering, project management). I also worked as a ML Engineer at iAdvize and in three different startups when I was in Denmark.
Whenever possible, I like to go out running (at times marathons), cross-country skiing and windsurfing.
PhD in Computer Science, 2021
Inria (funded by Univ. Lille), Lille, FR
MSc in Computer Science, 2017
Technical University of Denmark, Copenhagen, DK
MSc in General Engineering, 2017
École Centrale, Nantes, FR
Degree in Digital Business and IT, 2015
Audencia School of Management, Nantes, FR
BSc in General Engineering, 2014
École Centrale, Nantes, FR
A Reinforcement Learning Library for Research and Education (PyTorch)
AGAC: Adversarially Guided Actor-Critic (TensorFlow)
AVEC: Actor with Variance Estimated Critic (TensorFlow)
Materials for the Reinforcement Learning Summer School 2019: Bandits, RL & Deep RL (PyTorch)
Teaching Assistant
Instructors: Alessandro Lazaric, Matteo Pirotta
Teaching Assistant
Instructors: Felix Berkenkamp, Tristan Cazenave, Ludovic Denoyer, Gabriel Dulac-Arnold, Audrey Durand, Vincent François-Lavet, Matteo Hessel, Emilie Kaufmann, Marc Lanctot, Max Lapan, Alessandro Lazaric, Odalric-Ambrym Maillard, Jérémie Mary, Gerhard Neumann, Guillaume Obozinski, Olivier Pietquin, Bilal Piot, Matteo Pirotta, Bruno Scherrer, Florian Strub, Eleni Vasilaki, Oriol Vinyals
Projects, Summer Schools, etc.
2019 - London, UK
Code for RLSS | 2019 - Lille, France
Exhibition pictures | 2019 - Lille, France