In January 2022, I joined as post-doctorate the Systems Biology of Decision Making team of Laboratory of Biology and Modeling of the Cell at ENS Lyon to work on the SingleStatOmics project, which aims to develop new methodologies to investigate cell identity and the dynamics of cell differentiation by integrating single-cell expression and epigenomic data. My work is to develop new methods based on dimension reduction and integration of spatial genomic data.
Before, I was a research engineer within the Statistics and genome of the LaMME at Evry University and the Gnet team of the IPS2 (Plant institute of Paris-Saclay). My research work consists to detect PPR footprints by using machine learning methods at Arabidopsis Thaliana. Previously, I was a PhD student within the Biomathematics team of the MICS laboratory at CentraleSupélec (Paris-Saclay University) supervised by Paul-Henry Cournède and Sarah Lemler. My research works focused on survival analysis and marker detection in Oncology. I use machine learning and statistical methods to predict the survival duration and detect the biomarkers in high-dimension.
I did an two-year’s apprenticeship at both LMRS (Laboratoire Mathématiques Raphaël Salem) and LITIS (Laboratoire d’Infomratique et traitement de l’information et des systèmes). My principle work was to develop mixture models bivariate Negative Binomiale for RNA-seq data. In addition, I developed an R package for the simulation and estimation of Markov and Semi-Markov models and a Shiny application for the processing of qRT-PCR data called PROqPCR