I am a fifth year PhD candidate in the department of Electrical Engineering and Computer Sciences at UC Berkeley advised by Mike Jordan & Nir Yosef. My research interests lie at the intersection of statistics, computation and modeling.
A significant part of my research is driven by building more statistically accurate and faster machine learning software for analyzing biological data, with a focus on transcriptomics. I am the lead contributor to single-cell Variational Inference (scVI), a set of tools for fully-probabilistic modeling of scRNA-seq data. To learn more about scVI, check out this Bioinformatics chat episode or this feature in Nature Methods.
Aside from that, I worked on counterfactual inference and offline policy learning methods in collaboration with technology companies. In 2018, I visited Le Song at Ant Financial in Hangzhou. In 2019, I visited Inderjit Dhillon at Amazon in Berkeley.
Before graduate school, I obtained a MSc in applied mathematics from Ecole polytechnique, Palaiseau in 2016. Additionally, I worked as in intern at the Harvard Medical School with Allon Klein in 2016. I was born and grew up in Bedarieux, France.
PhD in Electrical Engineering & Computer Sciences
University of California, Berkeley
MSc in Applied Mathematics, 2016
Ecole polytechnique, France