In this work, we employ statistical and Bayesian techniques to analyze mathematical forward models. The forward models usually arise from phenomenological and physical phenomena and are expressed through regression-based models or partial differential equations (PDEs) associated with uncertain parameters and input data.
Prof. Tempone and some members of the Stochastic Numerics Research Group gave invited presentations to the mini-symposium hosted at the School of Economics and Administration of the Universidad de la República, Montevideo, Uruguay, on December 22, 2016. This event, chaired by Prof. Scavino and co-organized with Prof. Goyeneche (UdelaR), has consisted of two parts.
On November 7-9, Prof. Marco Scavino will participate in KAUST recruiting activities developed by the Office of International Programs with visits to Tecnológico de Monterrey and Universidad Nacional Autónoma de México (UNAM).