I am currently a part-time lecturer (enseignant vacataire) in Statistics within the Bachelor of Technology (BUT) in Data Science at IUT Aurillac (Clermont Auvergne University). My research interests include multivariate count data modeling, variable selection, latent and deep latent variable models, and the application of statistical methodologies to the life sciences, including agriculture, environmental science, human health, and related fields.
I obtained my PhD in biostatistics at Unité Mixte de recherche sur le Fromage under the supervision of Paul-Marie GROLLEMUND, Jocelyn CHAUVET and Christophe CHASSARD. During my PhD, I developed a statistical method for selecting variables in a multivariate Poisson Log-Normal (PLN) model, with application to the study of microbial communities involved in the milk production process.
Feel free to contact me by email for further information about my research or to discuss potential collaborations.
PhD in Biostatistics, 2025
Clermont Auvergne University
Master's in Applied Statistics and Decision Analysis, 2022
University of Caen Normandy
BSc in mathematics and computer science applied to human and social sciences, 2020
University of Caen Normandy
Responsibilities include:

This paper relies on the random matrix theory to reduce data dimension and to identify useful data sources in the unsupervised context. A so-called random matrix based principal component analysis algorithm is thus developed and then applied to the well-known 2008 PHM dataset to build efficient but less costly degradation indices. A comparison of the degradation indices obtained with and without sensors selection confirms the performances of our proposed approach.