I am a postdoc researcher using and developping statistical learning methods to extract knowledge from large biological datasets and decipher the mechanisms behind gene regulation. I completed my PhD in bioinformatics and biostatistics in the Institute for Plant Science of Montpellier, France, where I applied machine learning to genomic data to understand plants responses to climate change. In particular, I modelled the gene regulatory networks in Arabidopsis thaliana under high atmospheric CO2 concentration using regression frameworks in high dimensional settings.
PhD in biostatistics for gene regulation - Integrative Biology, Diversity and Plant Improvement, 2022
University of Montpellier, France
MSc in Computer Science - Artificial Intelligence, 2019
Université Claude Bernard Lyon I, France
Engineering degree in Bioinformatics and Modelling, 2019
National Institute of Applied Sciences (INSA) Lyon, France
R programming, Shiny apps, R packages, Rmarkdown, Python, Git, Latex
Modelling, Statistics, Data visualization
Systems biology, Gene Regulatory Networks, quantitative biology
Organiser of the international workshop hosted by the BPMP research unit
Dashboard for the Inference and Analysis of Networks from Expression data.
Evaluate the result of a network inference method against known, experimentally determined, regulatory interactions in Arabidopsis thaliana
Statistical learning for the prediction of chromosomic interactions