teaching

I have been teaching assistant for Machine Learning and Physics courses at École Polytechnique Fédérale de Lausanne (EPFL).

EE-411: “Fundamental of Inference and Learning”

(Fall 2021 - 2024) - Link to course webpage

First year MSc course in Electrical Engineering covering the basics of statistical inference and learning. The course material is available on the Github repository and covers different topics ranging from Maximum Likelihood Estimation to modern deep learning techniques.

EE-209: “Eléments de statistiques pour les data sciences”

(Spring 2024) - Link to course webpage

Second year BSc course in Electrical Engineering taught in French on the basics of probability and statistics.

PHYS-642: “Statistical Physics for Optimization & Learning”

(Spring 2023) - - Link to course webpage

Doctoral course in the Physics and Engineering school on the connection between statistical physics and learning. The course material is available on the Github repository and covers a broad range of topics in statistical physics of disordered systems ranging from the fundamental tools (replica and cavity method) to their application in learning problems (inference on graph, neural networks).

PHYS-314: “Physique Quantique II”

(Spring 2022) - Link to course webpage

Third year BSc course in Physics taught in French focused on many-body quantum systems and group theory for physicists.