Biography

My academic education, articulated between Sapienza and Universitè Paris-Dauphine, was mainly focused on Bayesian modeling and Markov Chain Monte-Carlo methods.
My research interests shifted towards the specific study of spatial and spatio-temporal phenomena later on, with a particular focus on the Bayesian Hierarchical Modeling for large geo-referenced data.
Since the beginning of the pandemic I focused on the analysis and proper media communication of the public epidemiological data together with StatGroup-19; we gave emphasis to the interpretability, transparency and reliability of our statistical findings.

My current lines of research mostly involve the modeling of phenomena characterized by complex dependence structures, whether the observations are organized at point-referenced locations, at nodes on a lattice, or on an arbitrary network. Whatever the application field (epidemiology, environmental, social), my efforts are always dedicated to finding a medium between the model adherence to the actual data generation mechanism and the feasibility of its estimation.