Hello ! I am currently a PhD candidate in Statistics and Machine Learning. I am working at CMAP in Ecole polytechnique supervised by Stéphanie Allassonnière and Erwan Le Pennec. I am also part of the INRIA Paris team HeKA focused on Health data and model-driven Knowledge Acquisition. Before this, I was a Master student in Mathematics and Machine Learning at MVA in ENS Paris-Saclay.
I am interested in systems at the intersection of mathematics and computation, in having analytical insights on real-world applications, especially in problem related to healthcare. My current PhD subject is focused on application of Reinforcement Learning for optimisation of medical trajectory to avoid diagnostic wandering in rare diseases. I have a great interest in:
- Robust and Risk-Averse Reinforcement Learning, ( with Matthieu Geist at Google DeepMind)
- Bandit theory (Thomson Sampling), (with Tom Huix and Alain Durmus at Ecole Polytechnique)
- Sampling methods in large dimention.
News : I will be a visiting researcher in the California Institut of Technology in the group of Professor Adam Wierman and Eric Mazumdar working on Robust RL !
I am organizing with Neurips in Paris 2023 with Linus Bleistein among other colleagues on the 6th and 7th of December 2023 at Sorbonne Université (Paris 5). A great occasion to meet and discuss recent advances in ML in central Paris !
I have also co-funded a junior seminar at PariSanté Campus with ealing with interactions between mathematics, Machine Learning and healthcare. Don’t hesite to contact me if you want participate or present your work !