I am a professor at the Centre for Computational Biology (CBIO) of Mines Paris–PSL, Institut Curie and Inserm (which are all part of PSL University). I am also a Researcher at PRAIRIE–PSAI. My research interests revolve around machine learning techniques for therapeutic research.
En français : ma présentation du 23 novembre 2017 à l'Académie des Sciences sur la caractérisation des cancers par les données génomiques.
Short bio
2005 – 2010: PhD at UC Irvine with Pierre Baldi, working on chemoinformatics and drug design (more particularly, virtual high-throughput screening).
2011 – 2013: Postdoctoral stay at the Max Planck Institutes for Developmental Biology and Intelligent Systems in Tübingen, working with Karsten Borgwardt on methods for genome-wide association studies.
December 2013: Joined CBIO.
Supervision (current)
Alix Gillet — Genome-wide association study of transposable elements polymorphisms and epigenetic regulation in Arabidopsis thaliana
Master intern since March 2026.
Joint supervision with Katia Antonenko
Kareem Elgohary — Multimodal disease risk learning
PhD student since October 2025.
Joint supervision with Éloïse Berson.
Inès Kardous — Innovative liquid biopsy biomarkers to improve precision oncology
PhD student since October 2025.
Joint supervision with Charlotte Proudhon.
Youmna Ayadi — Machine learning analysis of transcriptomics data
PhD student since September 2025.
Joint supervision with Florian Massip.
Paul Etheimer — Analysis of the statistical properties of bacterial genomes to unravel the factors favoring gene exchange and migration events
PhD student since October 2023.
Joint supervision with Florian Massip.
Katia (Ekaterina) Antonenko — statistical machine learning for the integration of transposable elements variability and epivariability in genotype-to-phenotype studies
Postdoc since September 2023.
Teaching
I teach bioinformatics, machine learning and drug discovery. See my teaching page for more details.
I also wrote a machine learning textbook in French.
Women in Machine Learning and Data Science (WiMLDS Paris)
I am the co-founder of the Parisian chapter of Women in Machine Learning and Data Science. We organize events, where we discuss machine learning and data science with the purpose of building a community around women in these fields. As of January 2026, Paris WiMLDS counts over 6,700 members. For more details about this and diversity in general, please check out my Diversity in STEM page.
Open Science
I am a proponent and open science. I serve as an associate editor for Computo, an open access journal that publishes reproducible contributions in machine learning and statistics as notebooks. I am also a recommender for the Peer Community In (PCI) Statistics and Machine Learning.
