Gaël Beaunée is a researcher in epidemiology, specialized in epidemic modeling and parameters estimation. His work aims to unravel the complexity of the mechanisms underlying the spread of infectious diseases at different scales, using mathematical models and computer simulations. His current research interests include inference procedure for partially observed dynamic processes, and more particularly on likelihood-free methods for simulation models, such as Approximate Bayesian Computation (ABC) and composite likelihood approach. The final purpose being to improve the reliability of the models and to provide predictions in adequacy with real situations.