Courses taught at Ecole Normale Superieure (2022 - )
Undergraduate Level:
Introduction to Machine Learning (with Alessandro Rudi)
Courses taught at Ecole Polytechnique (2023- )
Graduate Level:Deep Learning
Courses taught at Telecom-Paris (2016 - 2020)
Graduate Level:Introduction to Probabilistic Graphical Models
Mathematical Statistics
Factorization-Based Data Analysis
Basics of Statistical Machine Learning (partial)
Adaptive Methods (partial)
Practical Machine Learning (partial)
Optimization for Machine Learning (partial)
Adaptive Methods I: Stochastic Approximation (partial)
Adaptive Methods II: Bayesian Filtering (partial)
Industrial Masters:
Machine Learning and Data Mining (partial)
Advanced Machine Learning (partial)
Undergraduate Level:
Tools and Applications for Signals, Images, and, Sounds (partial)
PhD Students
Dario Shariatian — PhD student (2023-2026, co-supervised with Alain Durmus)
Benjamin Dupuis — PhD student (2023-2026, co-supervised with George Deligiannidis)
Alumni
Paul Viallard — Postdoc (2023 — 2024)
Krunoslav Pavasovic — Intern (2022-2023, co-supervised with Alain Durmus)
Sarah Sachs — PhD intern (2022-2023)
Milad Sefidgaran — Postdoc (2020-2021, co-supervised with Gaël Richard)
Kimia Nadjahi — PhD student (2018-2021, co-supervised with Alain Durmus and Roland Badeau)
Ondřej Cífka — PhD student (2018-2021, co-supervised with Gaël Richard)
Thanh Huy Nguyen — PhD student (2017-2021, co-supervised with Gaël Richard)
Simon Henriet — PhD student (2017 — 2020, co-supervised with Gaël Richard and Benoît Fuentes)
Çağatay Yıldız — Intern (summer 2017)
Halil Erdoğan — Intern (summer 2017)