Welcome!
I'm interested in many things related to Machine Learning, AI for Science, and Open-Endedness.
My research has focused on developing open-ended AI agents that unsupervisedly learn to represent and set their own goals in complex dynamical systems, with the aim to accelerate scientific discovery by assisting humans' exploration of the structures that can self-organize in these systems.
I recently defended my Ph.D. in Machine Learning under the supervision of Pierre-Yves Oudeyer and Clément Moulin-Frier at the FLOWERS team at Inria, Bordeaux; and in collaboration with the Poietis biotech company. Last year, I also went on a 4-month visit to Dr. Michael Levin and his team at the Levin Lab at Tufts University.
Previously, I have been at University College of London where I completed my Master of Science (MSc) in computer vision and at Télécom Paristech where I did my Master of Engineering (MEng). I also spent a year as an AI research intern at Siemens Healthineers, Princeton N.J., working on deep learning and reinforcement learning algorithms for healthcare. My extended CV can be found here.
News:
- 03/2024: Released the sketch-transformer tutorial to train transformers to generate human-like sketches
- 02/2024: Our paper about AI-driven discovery of GRN behaviors got accepted into the eLife journal
- 12/2023: Co-organized the Agent Learning in Open-Endedness Workshop held at NeurIPS 2023 🌱
- 11/2023: Defended my thesis "Curiosity-driven AI for Science: Automated Discovery of Self-Organized Structures". Thank you to my amazing jury Alan Aspuru-Guzik, Sebastian Risi, Melanie Mitchell, Jeff Clune, and Nicolas Brodu; and supervisors Pierre-Yves Oudeyer, Clément Moulin-Frier and Marc Nicodème 🙏
- 07/2023: Our Flow Lenia paper won the best paper at ALife 2023 conference
- 07/2023: Released the SBMLtoODEjax package, check out the documentation and tutorials for more info
Thesis:
Publications:
SBMLtoODEjax: Efficient Simulation and Optimization of Biological Network Models in JAX
AI for Science Workshop at NeurIPS 2023 (Poster)
| abstract | webpage | pdf | publication | code | documentation | tutorials |Flow-Lenia: Towards open-ended evolution in cellular automata through mass conservation and parameter localization
ALIFE 2023 (Best Paper Award)
| abstract | webpage | pdf | publication | oral talk | code |Hierarchically Organized Latent Modules for Exploratory Search in Morphogenetic Systems
NeurIPS 2020 (Oral presentation, top 1%)
| abstract | webpage | pdf | publication | poster | oral talk | code |Progressive Growing of Self-Organized Hierarchical Representations for Exploration
Be-TR RL Workshop at ICLR 2020 (Poster)
| abstract | pdf | publication | oral talk |Intrinsically Motivated Exploration for Automated Discovery of Patterns in Morphogenetic Systems
ICLR 2020 (Oral presentation, top 2%)
| abstract | webpage | pdf | publication | oral talk | blog | code |Nonlinear Adaptively Learned Optimization for Object Localization in 3D Medical Images
DLMIA workshop at MICCAI 2018, also abstract at MED-NEURIPS 2018 (Poster)
US Patent: https://patents.google.com/patent/US20190378291A1/en
| abstract | pdf | publication | poster |