Julien Stoehr has been a lecturer at Université Paris-Dauphine since 2017. After graduating from the École Normale Supérieure Rennes (former École Normale Supérieure de Cachan - Antenne de Bretagne) and receiving an external degree (agrégation) in Mathematics, he got a PhD in statistics and specialized in the field of computational statistics. His research focuses on the design and implementation of statistical methodologies in a Bayesian setting where the statistical model is complex, e.g., likelihood with no closed form or generative models that are time consuming to simulate from, with a particular interest for the Monte Carlo methods (Markov chain Monte Carlo, Hamiltonian Monte Carlo and approximate Bayesian methods (ABC)).