Lately, I have focused on dealing with the constraints appearing in optimal control or trajectory reconstruction. This is part of a work on general shape constraints in kernel regression with Zoltán Szabó, for e.g. non-crossing quantile regression.
I graduated from École polytechnique (X2013) in 2017, then obtained my Master degree (MVA, Mathematics-Vision-Learning) with Highest Honours after an internship with Jean-Philippe Vert (CBIO-Google) on gene network inference (based on single-cell RNA sequencing).
PhD in Machine Learning, 2018-
MS (M2) in Machine Learning, 2016-2017
MS (M1) in Applied Maths, 2013-2016
PCAF, Nicolas Petit and Zoltan Szabo, Kernel Regression for Trajectory Reconstruction of Vehicles under Speed and Inter-Vehicular Distance Constraints, Proceedings IFAC WC 2020, July 2020, [article], pdf, slides, video
Hired as top civil servant (Corps des IPEF). Specialized in:
Worked on artificial intelligence tailored to the strategies of the technical and scientific network of the French Ministry of Environment. I handed a report shortly after the Villani mission “For a meaningful Artificial Intelligence”. This report focuses on conceptualizing machine learning approaches and details its possible effects in institutions transforming due to the Digital Revolution.