Research interests

My research focuses on the following subjects.

  • Adversarial examples (theoretical understanding, efficient generation and detection methods)
  • Understanding neural network (generalization, optimization, robustness)
  • Structured prediction (determinantal point processes, etc.)
  • Sampling

These days, I also have an interest in privacy and fairness in machine learning.


Checkout my list of publications here on Google scholar.

Supervision roles


  • Meyer Scetbon: Doctoral internship on “Understanding adversarial training”; in July – November 2022
  • Morgane Goibert: End of M.Sc. internship on “Label-smoothing for better adversarial robustness”; January – July 2019

PhD students

  • Morgane Goibert: Robust Ranking (co-supervised with Stéphan Clémançon); 2019 – present