I am an associate professor at the Centre for Computational Biology (CBIO) of ARMINES/MINES ParisTech, 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.

Le deuxième tirage de mon Introduction au Machine Learning à destination des élèves ingénieur·e·s ou mastérien·ne·s est parue en juillet 2019 aux éditions Dunod. La version électronique (pdf) sans exercices est disponible ici.

Pour découvrir mes thématiques de recherche en français : ma présentation du 23 novembre 2017 à l'Académie des Sciences sur la caractérisation des cancers par les données génomiques.

Postdoctoral position I am looking for someone with a PhD in statistics or machine learning to work on high-dimensional inference in genomics, as part of Prairie. Start date Fall 2021 or later. Details here (pdf).

Short bio

Previously I have worked in the area of chemoinformatics and drug design (more particularly, virtual high-throughput screening) during my PhD at UC Irvine with Pierre Baldi. I switched my focus to the other side of the coin during my postdoctoral stay at the Max Planck Institutes for Developmental Biology and Intelligent Systems in Tübingen, where I worked with Karsten Borgwardt as a member of the Machine Learning and Computational Biology (MLCB) research group on methods for genome-wide association studies. I joined CBIO in December 2013.


  • Vivien Goepp — Complex epistasis detection in genome-wide association studies.
    Postdoctoral researcher since January 2020.
  • Asma Nouira — Stable feature selection for multi-locus genome-wide association studies.
    PhD student since January 2018.
  • Ndèye Maguette Mbaye — Learning from multi-modal data to improve cancer treatment.
    PhD student since September 2019.
  • Marc Michel — Determining the potential of methylation of circulating tumor DNA as a pan-cancer biomarker.
    PhD student at Paris Saclay since October 2019.
    Joint supervision with Charlotte Proudhon.
  • Élise Dumas — Evaluation of the interactions between comedications and recurrence-free survival in breast cancer from SNDS data.
    PhD student at Paris Saclay since October 2019.
    Joint supervision with Fabien Reyal.



I teach lectures related to bioinformatics, machine learning and drug discovery at several places, including MINES ParisTech, Centrale Paris and Paris-Diderot. I'm also teaching online courses (in French) at OpenClassrooms. See my teaching page for more details.

Women in Machine Learning and Data Science

I am the co-founder of the Parisian chapter of Women in Machine Learning and Data Science. For more details about this and diversity in general, please check out my Diversity in STEM page.