Stochastic models for epigenetic processes • Optimization, parameter inference • Machine learning for whole genome analysis • Implementation of a complete tool targeted to biologists • Numerical algorithms for huge Markov chains • Optimal experiment design and chemical kinetics • Aggregation of mean-field ODEs for epidemic dynamics. • Author of 9 publications (lead author in 6 of those) in major journals and conferences • Co-supervisor of 2 master theses, T.A. in 5 courses

Computational Epigenetics, Markov Chains, Machine learning, Non linear optimization, Bayesian statistics, MCMC methods, Whole genome analysis, Optimal experiment design, Stochastic chemical kinetics, Epidemic modeling, Random Graphs.

Computational Complexity, Computability, Game Theory, Probabilities, Number Theory, Approximation and Parallel Algorithms.