I graduated from ENSTA Paris with a specialization in applied mathematics in 2020. In parallel, I also graduated from the Data Science Master of Université Paris-Saclay.

During my studies, I did a 6-month research internship under the supervision of Philippe Naveau, at the Laboratoire des Sciences du Climat et de l’Environnnement. I was working on rainfall extremes clustering, by coupling Kullback-Leibler divergence and machine learning algorithms. This research project was awarded the prize of the best end-of-studies project by ENSTA Alumni.

Before that, I also did a 3-month research internship at the University of Bristol, on non-parametric additive quantile regression. More specifically, it was about the statistical and computational advantages of smoothing the pinball loss. I was supervised by Matteo Fasiolo.

For more details, see my resume.