About Me

I am Statistician and Machine Learning scientist. I recently defended my PhD thesis in Statistics & Machine Learning at CMAP, Ecole Polytechnique and TotalEnergies in a CIFRE Contract (Industrial PhD). I am supervised by Josselin Garnier, professor at the CMAP Laboratory, Ecole Polytechnique and Antoine Bertoncello, senior research engineer at TotalEnergies OneTech.

My research project was about Statistical learning and causal inference. The objective is to develop a data-driven approach, coupling causality with machine learning, for optimization and decision making, with a focus on uncertainty quantification.

Here, you will find link to my publications, talks, and my resume. You can also find on the left-hand side links to my social accounts and e-mail, feel free to contact me. Have a good day !

News

• May 2023: Excited to announce that my paper work with Ramiro Lugo, Antoine Bertoncello and Josselin Garnier about Meta-Learners for Multi-Valued Heterogeneous Effects was accepted to ICML 2023!
• May 2023: I started a new position at namR as Data Scientist. I am working on developing, improving and validating the quality of buildings attributes produced by Machine Learning.
• February 2023: I gave at talk at “séminaire ONERA sur les incertitudes” organized by Jérôme Morio, ONERA.
• November 2022: I was very honored to defended my PhD thesis entited Statistical learning and causal inference for energy production. Many thanks to my jury members: Rémi Flamary, Josselin Garnier, Tim Sullivan, Marianne Clausel, Michèle Sebag, Olivier Roustant and Antoine Bertoncello.