- Artificial intelligence: mainly focused on the constraint satisfaction problem (CSP), a NP-hard problem defined in the AI community in the seventies and more specifically weighted and valued constraint networks, I'm more largely interested in all sorts of graphical models (Bayesian nets, SAT, QBF, MDP, POMDP, Stochastic and mixed CSP, influence diagrams, CP-nets...)
- Bioinformatics: the application of CSP and other techniques originating from artificial intelligence and operations research to constrained optimisation problems, more specifically in computational biology. Actually, this is mainly genetic markers ordering, genetic map joining, RNA secondary structure prediction and also RNA/protein gene finding and prediction (with frameshift detection) both for prokaryotic and eukaryotic organisms, biological network inference and protein redesign.
RESEARCH THEMES
EXTERNAL COLLABORATIONS
- With the Combinatorial optimization group of CERT (Centre d'Études et de Recherches de Toulouse de l'ONERA) on algorithms for CSP.
- With Hélène Fargier, Jérôme Lang, Martin Cooper from the Institut de Recherches en Informatique de Toulouse for extensions of the CSP formalism and valued constraint network properties and algorithms.
- With the team of F. Rossi, University of Padova, Italy, for the comparison of Valued CSP and Semi-ring CSP.
- With Pedro Meseguer and Javier Larrosa (Polytechnic University of Catalunya, Spain), for the algorithmic of Valued and weighted CSP.
- With P. Rouzé (University of Ghent, Belgium) for gene finding in Arabidopsis thaliana. and other plants.
- With Marie-France Sagot on the algorithmic of gene finding.