Welcome to my website !

I'm a PhD Student at IFP Énergies nouvelles (IFPEN) in the Control, Signal and System Department and Univerité Paris-Est in the Laboratoire d'Informatique Gaspard Monge (LIGM).

My PhD advisors are Jean-Christophe Pesquet (LIGM), Laurent Duval (IFPEN - Math.), Camille Couprie (Facebook, AI Research) and Frédérique Bidard-Michelot (IFPEN - Bio).

PhD Work

Graph-based and sparse variational analysis of biological networks, application to transcriptomics.
[Analyse de réseaux biologiques (transcriptomiques) par graphes structur és et contraintes variationnelles de parcimonie.]

At IFPEN, biologists work on various micro-organisms in an energetic context: bio-ethanol production. In this particular case, they aim at optimizing fungi strains to improve their production enzymes, used as catalyst(s) in the bio-ethanol production process. For this purpose, enzyme production mechanisms require a better understanding. This kind of information may by encoded as a graph structure whose nodes and edges are respectively derived from genes and their correlations or regulations. The resulting network is called a Gene Regulatory Network (GRN). Indeed, inferring GRNs from gene expression data is especially useful for sketching transcriptional regulatory pathways and helps to understand phenotype variations. However, these graphs, involving thousands of genes, are difficult to visualize or analyze, especially incorporating either experimental uncertainties or additional information retrieved from similar organisms. In this research work, we propose to address this problem with recently developed techniques pertaining to graph (nodes and edges) optimization with sparsity priors, leading to variational analysis based on sparsity-inducing metrics.

My thesis in 3 minutes

3 minutes thesis

Useful Links

LIGM: Laboratoire d'Informatique Gaspard Monge

IFPEN: IFP Énergies nouvelles

Linked in : see my profil


IFP Énergie nouvelles
Dir. Mécatronique et Numérique
1 & 4 avenue de Bois-Préau
92852 Rueil-Malmaison cedex - France
01 47 52 61 27

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