About
Julien Bastian
PhD student in Computer Science
Since October 2024, I have been a PhD student in Computer Science at the Hubert Curien Laboratory, Université Jean Monnet (France) in Saint-Étienne, where I am a member of the Machine Learning team. My research lies in the field of statistical machine learning, with a particular focus on algorithmic fairness and PAC-Bayesian theory. I am interested in understanding how learning algorithms can be designed with (and from) theoretical guarantees while taking fairness-related constraints into account.
My PhD is supervised by Christine Largeron, Emilie Morvant, and Guillaume Metzler, and is funded by the french project ANR Famous (Fairness-Aware Multimodal Learning Under Structured Assumptions). The goal of my research is to study how PAC-Bayesian tools can contribute to the analysis and design of fair learning algorithms. More broadly, my work aims to connect theoretical machine learning with questions related to the fairness of predictive models.
Research interests
- Fairness and Bias in Machine Learning
- PAC-Bayesian theory
- Statistical machine learning
- Learning theory
- Generalization guarantees
- Supervised learning
- Self-bounding algorithms