I am assistant professor at École polytechnique. Prior to that, I was a postdoc at ENSAE in the FairPlay team, under the supervision of Vianney Perchet. I received my PhD from Université Paris-Saclay, working in the Laboratoire de Mathématiques d’Orsay under the supervision of Christophe Giraud and Olga Klopp.

I am mainly interested in sequential learning and sequential decision-making problems, and in fair machine learning.

News

Our paper Supervised Contamination Detection, with Flow Cytometry Application has been accepted for publication at Biometrika !

I am thrilled to announce that I have been named one of the 2024 French Young Talents of the Fondation L’Oreal-UNESCO For Women in Science! I am incredibly honored to be sharing this award with 34 brilliant women.

Papers, preprints, and software

Non-Stationary Lipschitz Bandits (2025) N. Nguyen, S. Gaucher, and C. Vernade. Preprint

Supervised Contamination Detection, with Flow Cytometry Application S. Gaucher, G. Blanchard, and F.Chazal (2025). Biometrika. Preprint

Demographic parity in regression and classification within the unawareness framework (2024) V. Divol and S. Gaucher. Preprint

Feature-Based Online Bilateral Trade S. Gaucher, M. Bernasconi, M. Castiglioni, A. Celli and V. Perchet (2025). ICLR 2025. Preprint

Improved Algorithms for Contextual Dynamic Pricing M. Tullii, S. Gaucher, N. Merlis and V. Perchet (2024). NeurIPS 2024. Preprint

Open Research Challenges for Private Advertising Systems under Local Differential Privacy M. Tullii, S. Gaucher, H. Richard, E. Diemert, V. Perchet, A. Rakotomamonjy, C. Calauzènes, and M. Vono (2024). Wise 2024. Preprint

Fair learning with Wasserstein barycenters for non-decomposable performance measures S. Gaucher, N. Schreuder, and E. Chzhen (2023). AISTATS 2023. Paper

The price of unfairness in linear bandits with biased feedback, S. Gaucher, A. Carpentier, and C. Giraud (2022). NeurIPS 2022. Preprint on Hall, Short Presentation

Hierarchical transfer learning with applications for electricity load forecasting, A. Antoniadis, S. Gaucher, and Y. Goude (2021). International Journal of Forecasting. Preprint on HAL

Maximum Likelihood Estimation of Sparse Networks with Missing Observations, S. Gaucher, O. Klopp (2021). Journal of Statistical Planning and Inference, Preprint on HAL

Outliers Detection in Networks with Missing Links, S. Gaucher, O. Klopp, G. Robin (2021). Computational Statistics and Data Analysis.Preprint on Arxiv

Optimality of Variational Inference for Stochastic Block Model with Missing Links, S. Gaucher, O. Klopp (2021). NeuRIPS 2021

Finite Continuum-Armed Bandits (2020), S. Gaucher. NeuRIPS 2020, Short Presentation, Poster

R package gsbm (2020). S Gaucher, G. Robin. The package allows to robustly estimate probabilities of connections in the presence of missing observations and outlier nodes, while detecting those outlier nodes.