Room “Sala Seminari” - Abacus Building (U14)
Different Takes on the Causal Modelling of Spatio-Temporal Data
Speaker
Dr Marco Scutari
IDSIA - Istituto Dalle Molle di Studi sull'Intelligenza Artificiale (Switzerland)
Abstract
The assumption that data are independent and identically distributed samples from a single underlying population is pervasive in statistical modelling. Regression models have been extended over time to deal with structured data that are collected over time, spaces and different populations. But what about causal models? In this talk, we will discuss some of the different trade-offs we should take into account to produce models that can answer the causal queries we want to investigate.
Short bio
Marco Scutari is a Senior Researcher at Istituto Dalle Molle di Studi sull'Intelligenza Artificiale (IDSIA), Switzerland. He has held positions in Statistics, Statistical Genetics and Machine Learning in the UK and Switzerland since completing his Ph.D. in Statistics in 2011. His research focuses on the theory of Bayesian networks and their applications to biological and clinical data, as well as statistical computing and software engineering.
Contact person for the seminar: fabio.stella@unimib.it