I am a professor at the Centre for Computational Biology (CBIO) of ARMINES/Mines Paris–PSL, Institut Curie and INSERM (which are all part of PSL Research University), and hold a Springboard Chair at PRAIRIE. 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)

Giann Karlo Aguirre-Samboní — Network-guided GWAS analysis of biobank whole-exome sequencing data
Postdoc since March 2024.
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.

Ekaterina Antonenko — statistical machine learning for the integration of transposable elements variability and epivariability in genotype-to-phenotype studies
Postdoc since September 2023.

Gwenn Guichaoua — Development of machine-learning approaches for identification of a molecular signature, therapeutic targets, and drugs for ATIP3-low Triple Negative Breast Cancer
PhD student since November 2022.
Joint supervision with Olivier Collier, Clara Nahmias and Véronique Stoven.

Ndèye Maguette Mbaye — Learning from multi-modal data to improve cancer treatment.
PhD student since September 2019.  


I teach bioinformatics, machine learning and drug discovery at Mines Paris. I'm also teaching online courses (in French) at OpenClassrooms. See my teaching page for more details.

I also wrote a machine learning textbook in French.

Machine Learning in Computational and Systems Biology (MLCSB)

MLCSB is a community of researchers from systems biology, computational biology and machine learning that promotes the exchange of ideas, interactions and collaborations on these topics.

Formally, MLCSB is a community of special interest (COSI) of the International Society for Computational Biology (ISCB). Our main activities are the organization of workshops and the management of a mailing list (Google Group) of more than 1,000 members as of June 2021. Magnus Rattray and I have been presidents of MLCSB since March 2020.

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 May 2023, Paris WimLDS counts over 4,800 members. For more details about this and diversity in general, please check out my Diversity in STEM page.


I am an associate editor of Computo, an open access journal that publishes reproducible contributions in machine learning and statistics as notebooks.