You may still reach me at my former email address:
updated November 2022
I am particularly interested in developing statistical methods for the analysis of biological data, with an emphasis on computational biology and high-throughput technologies. Recent projects involve Deep-Learning methods for the analysis of sequencing data (Nanopore technologies), and Markov Processes for the analysis of clinical data. My main research interests involve:
- Convolutional Neural Network for Nanopore Sequencing
- Machine learning techniques for genomics, in particular random forests
- Computation and algorithms for ultra-large genomic data
- Partially-Observable Markov Decision Processes (POMDP), Piece-wise Deterministic Markov Processes (PDMP), applications to medical data
- Change-point detection problems and model selection for discrete variables with special emphasis on sequencing data
- The 2023 edition of the SMPGD will be held in Ghent on 2-3 February 2023! Check out the web-page for an exciting program, and to submit an abstract for a talk or a poster!
- The annual meeting of the Australian Mathematical Society will host a special session on Mathematical Biology! Don’t hesitate to send an abstract!
- 2015-2022 CR CNRS at Université de Montpellier, IMAG
- 2013-2015 Post-doc at Harvard School of Public Health with Giovanni Parmigiani
- 2010-2013 PhD at AgroParisTech/INRA and UC Berkeley with Stéphane Robin and Sandrine Dudoit