Eugène Berta

I am a third year PhD student in the SIERRA team at INRIA Paris and École Normale Supérieure. I am advised by Francis Bach and Michael I. Jordan.

Prior to that, I graduated from Télécom Paris and got my Master's degrees in Mathematics, Vision and Learning at Université Paris Saclay.

Email  /  Scholar  /  Github  /  LinkedIn

While machine learning systems can be incredibly powerful, it is of crucial interest to understand how confident we can be in their outputs. My work focuses on providing statistical guarantees for these predictions. In particular, I do research on classifier calibration, proper scoring rules, and conformal prediction.

I am developping the probmetrics Python package with David Holzmüller. The package provides efficient implementations for various post-hoc calibration methods, as well as classification metrics, especially metrics for assessing the quality of probabilistic predictions.

I co-organised the workshop Towards Trustworthy Predictions: Theory and Applications of Calibration for Modern AI at AISTATS 2026. The event was held on May 5, 2026 in Tangier, Morocco. A list of accepted paper can be found on the workshop website or on OpenReview.

I regularly review for the AISTATS, ICML, and NeurIPS conferences.

2025-2026: Teaching assistant for the second year course "Mathématiques fondamentales" in the "Cycle Pluridisciplinaire d’Études Supérieures" (CPES) of Lycée Henri IV and PSL university.