RESEARCH THEMES
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.