About me

I am a PhD student in Machine Learning / Statistic at University Paris-Saclay at the institut de mathématiques d’orsay under the supervision of Gilles Blanchard and Marc Glisse. I’m also part of the Datashape team (INRIA).
My thesis is in collaboration with Metafora a biotechnology company based at the Cochin Hospital.

My thesis deals with the comparison of cytometric datasets. Metafora has developped a software (Metaflow), that allows automatic analysis of flow cytometry data. My work focuses on the use of machine learning models to transfer the analysis performed on one sample to a new unanalysed one. We rely on Reproducing Kernel Hilbert space to embed and store high-dimensional features in Euclidian Space. We use these representations to, firstly, estimate the proportions of each population in a new sample, and secondly to automatically name the cluster obtained by the software.

Research Interest

  • Label Shift and Quantification Learning.
  • Kernel Mean Embedding and kernel methods in general.

Pre-prints

Complete list on ArXiv.

  • Label Shift Quantification with Robustness Guarantees via Distribution Feature Matching (with G.Blanchard and B.Chérief-Abdellatif) ArXiv preprint and code

Talks

Invited talks

Poster presentations

  • ECML/PKDD 2023, Label Shift Quantification with Robustness Guarantees via Distribution Feature Matching (RT Track – Best Student Paper) (Poster)

Teaching

Since September 2022, I am a teaching assistant at IUT Sceaux (Part of University Paris-Saclay)

  • Outil Mathématiques de gestion 1, B.U.T. GEA, IUT Sceaux, 2022-2023, taught by Patrick Pamphile.
  • Outil Statistiques de gestion 2, B.U.T. GEA, IUT Sceaux, 2022-2023, taught by Patrick Pamphile.

Seminar

I Co-organize the seminar for master students in Statistics and Machine Learning at Université Paris-Saclay.

Short CV

Curriculum Vitae

Education

  • 2021--2024, PhD, University Paris-Saclay
  • 2020--2021, MSc, University Paris-Saclay (Master Mathématiques de l’Intelligence Artificielle)