Biography

Starting Fall 2025, I will join the Courant Institute of Mathematical Sciences and the Department of Biology at New York University as an Assistant Professor of Computer Science and Biology. Please check out the webpage for the group! My research interests lie at the intersection of statistics, computation and modeling with a focus on biological applications.

In the meantime, I am still a Postdoctoral Fellow jointly appointed between Genentech Research & Early Development and the Stanford University School of Medicine. I was hosted by Jonathan Pritchard and Aviv Regev. Before that, I obtained my PhD degree from the department of Electrical Engineering and Computer Sciences at UC Berkeley, advised by Mike Jordan & Nir Yosef.

A significant part of my research is driven by building more statistically accurate and faster machine learning software for analyzing single-cell omics data. I developed single-cell Variational Inference (scVI), a flexible model and a scalable inference method for comprehensive analysis of single-cell transcriptomes. I co-developed scvi-tools, an open-source software suite for fully-probabilistic modeling of single-cell multi-omics data. You may learn more about these topics in my guest lecture of the Deep Learning in the Life Sciences class at MIT.

More generally, I am interested in the broader area of ML + Science. Deep generative models provide an appealing and flexible paradigm for learning distributions, but quite some work is needed to fully exploit them as part of a scientific hypothesis testing pipeline (e.g., causality, interpretability, disentanglement, decision-making).

Previously, I worked on counterfactual inference and offline policy learning methods in collaboration with technology companies. In 2018, I visited Le Song at the Ant Group in Hangzhou. In 2019, I visited Inderjit Dhillon at Amazon Science in Berkeley. Before graduate school, I obtained a MSc in applied mathematics from Ecole polytechnique, Palaiseau in 2016. Additionally, I worked as an intern at the Harvard Medical School with Allon Klein in 2016. I was born and grew up in Bedarieux, France.

Interests

  • Machine Learning + Science
  • Computational Biology
  • Causal Inference
  • Applied Statistics

Education

  • PhD in Electrical Engineering & Computer Sciences, 2021

    University of California, Berkeley

  • MSc in Applied Mathematics, 2016

    Ecole polytechnique, France