Emiliano Torre received his BSc (2009) and MSc (2011) in Mathematics from the University of Torino, Italy in 2011, where he specialized in probability and mathematical statistics. His MSc thesis concerned the use of copula models of temporal dependencies to generalize stochastic diffusions. In 2011, Emiliano joined the Institute of Neuroscience and Medicine (INM-6) and Institute for Advanced Simulation (IAS-6) of the Jülich Research Centre, Germany, where, as a PhD student of the RWTH Aachen University, he pursued his PhD in computational and statistical neuroscience. He obtained his PhD in 2016 with a thesis of pattern mining and efficient Monte Carlo statistical testing for massively parallel spike train data.
Since 2016, Emiliano is a joint research fellow at the Chair of Risk, Safety and Uncertainty Quantification and at the RiskLab of ETH Zürich. Together with Prof. Bruno Sudret and Prof. Emer. Paul Embrechts, he investigated copula dependence models for improving estimation in uncertainty quantification and machine learning problems. His research focus has been on risk and reliability analysis for computationally expensive models and data-driven predictions under data scarcity. As a UQLab developer, he has been responsible for a major overhaul of the INPUT module, newly featuring vine copula models of input dependencies as well as statistical inference of probabilistic input models.