Welcome

Research interests

Bayesian Statistics: Approximations; Computation; Nonparametrics; Extreme value theory; Objective Bayes.
Bayesian Machine Learning: Bayesian neural networks; Variational inference.
Applications of the above in environmental science and neuroscience.

Associate editorship

AISTATS (Area chair 2026)
Statistics and Computing (2025 - )
Bayesian Analysis (2019 - )
Australian and New Zealand Journal of Statistics (2019 - )
Statistics & Probability Letters (2019 - )
Statistical Methods & Applications (2024 - )
Computational Statistics & Data Analysis (2020 - 2023)

News

[Apr 2026]  Organizing StatLearn in Grenoble.

[Dec 2025]  Gianni Franchi (IP Paris) HDR committee: "Towards trustworthy AI".
[Nov 2025] Bayesian Analysis discussion paper webinar: Model Uncertainty and Missing Data. [site]
[Nov 2025] Talk at Recent Advances in Machine Learning in Aussois.
[Oct 2025]  Antoine van Biesbroeck (Polytechnique) PhD committee: "Reference prior theory".
[Sep 2025] Organized Bayesian Analysis discussion paper webinar: Tree Perspective on Stick-Breaking Models. [site]
[Sep 2025] Talk at RSS Workshop in Edinburgh. [slides]
[Aug 2025] Qian Jin (Sydney) PhD committee: "Latent Structure Models".
[Jul 2025] Talk at BNP14 @ UCLA. [slides]
[Jun 2025] Keynote talk at Journées de Statistique in Marseille. [slides]
[Apr 2025] Jan Greve (Wien) PhD committee: "Probability Distributions on Partitions".
[Apr 2025] Meriam Ezziati (Marseille) PhD committee: "High-z quasars in the Euclid Wide Survey".
[Apr 2025] Discussant @ BAYSM 2025.
[Feb 2025] Organized Bayesian Analysis discussion paper webinar: Sparse Bayesian Factor Analysis. [site]

[Dec 2024] Tom Huix (Polytechnique) PhD committee: "Variational Inference: theory and large scale applications".
[Dec 2024] Nikita Kotelevskii (Skoltech) PhD committee: "Predictive Uncertainty Quantification in Federated Learning".
[Nov 2024] Invited to Dagstuhl Seminar Rethinking the Role of Bayesianism in the Age of Modern AI.
[Oct 2024] Davide Agnoletto (Padova) PhD committee: "Generalized Bayes statistical modeling".
[Sep 2024] Member of ISBA Social Media Team.
[Mar 2024] Andrea Mascaretti (Padova) PhD committee: "Bayesian Sparse Models for Complex Data".
[Mar 2024] Alice Giampino (Bicocca) PhD committee: "Bayesian clustering methods".
[Sep 2024] Invited to GenU Workshop in Copenhagen.
[Aug 2024] I organized a Bayesian deep learning session at Journées MAS, Poitiers.
[Jun 2024] Wonderful conferences: Bayes-Duality at RIKEN, Tokyo, and ISBA World Meeting in Venice.
[May 2024] Louise & Dasha's paper on Bayesian mixture models (in)consistency accepted at Scandinavian Journal of Statistics.
[May 2024] Papers on Bayesian deep learning: ICML position paper, and Bayesian neural networks review.
[Apr 2024] Dasha and Charles' paper on discovering summary causal graphs accepted at TMLR.

[Dec 2023] Otmane Sakhi (IP Paris) PhD committee: "Offline Contextual Bandit".
[Dec 2023] Mica Teo (Edinburgh) PhD committee: "Bayesian scalar-on-image regression".
[Oct 2023] Bayesian autumn school, CIRM, Marseille.
[Oct 2023] Talk in Edinburgh Stat Seminar.
[Sep 2023] "A Primer on Bayesian Neural Networks: Review and Debates" on arXiv.
[May 2023] Four PhD students have defended: Giovanni Poggiato, Daria Bystrova, Minh Tri Lê, and Théo Moins.
[Apr 2023] Miguel Palencia-Olivar (Lyon 1) PhD committee: "Topical approach to capturing customer insight in social media".

[Dec 2022] Yuqing Hu (Rennes) PhD committee: "Transductive Few-Shot Image Classification".
[Mar 2022] Meryem Bousebata (Inria Grneoble) PhD committee: "Extreme value theory and high-dimensional statistics".
[Mar 2022] Ioanni Niko Mitro (UC Dublin) PhD committee: "Bayesian Neural Networks for OOD Detection".
[May 2022] Gabriel Durocq (IP Paris) PhD committee: "Bayesian algorithms in high dimension".

[Jun 2019] Romain Mismer (Sorbonne) PhD committee: "Posterior convergence of spike-and-slab models".