Teaching
Current teaching (2025–2026)
First semester
Introduction to programming with C++
Introductory course in algorithmic thinking and structured programming using modern C++.
Topics include: basic C++ syntax, types and I/O; control structures (conditionals, loops); functions and modular program design; fundamental data structures (arrays, vectors); introduction to object-oriented programming (classes, encapsulation); implementation of classical searching and sorting algorithms.
Machine learning
Practical sessions accompanying a core introduction to machine learning.
Topics include: linear and logistic regression, model evaluation; supervised classification and support vector machines; dimensionality reduction (PCA); unsupervised learning (clustering methods); ensemble methods (bagging, boosting, random forests); short introduction to deep learning concepts.
Second semester
Statistics and Learning
Core course covering mathematical statistics and an introduction to statistical learning, based on lecture notes by Paul-Henry Cournède.
Part I — Elements of Mathematical Statistics: data and statistical models (sampling theory, empirical methods, regression models); parameter estimation (Fisher information, method of moments, maximum likelihood, Bayesian estimation, confidence regions); statistical hypothesis testing (parametric tests, p-values, Pearson's χ² test, goodness-of-fit tests including χ² and Kolmogorov–Smirnov).
Part II — Statistical Learning: supervised learning (decision theory, linear and logistic regression, regularization and model selection, decision trees, artificial neural networks); unsupervised learning (principal component analysis, K-means clustering).
Previous teaching experience
Mathematics teacher (agrégé)
Between September 2021 and July 2024, I was assigned as an "agrégé" mathematics teacher to different secondary schools: Collège Saint-Exupéry (Villiers-le-Bel), Lycée Blaise Pascal (Châteauroux), and Lycée Bernard Palissy (Gien). This diversity of student levels further strengthened my pedagogical skills and classroom experience.
Teaching assistant (64 h/year)
During my PhD, I taught for the mathematics department of the University of Rennes:
Supervision
- Supervision of study-and-research dissertations on Stein's method for undergraduate ENS Rennes students.
- Preparation for the "agrégation" oral examination (Probability and Statistics option).
Assessment
Examiner for the Mathematics and Computer Science oral examinations (2023, 2024) and marker for the written MP examinations (2023, 2024, 2025) for CentraleSupélec.