Officers

Carlo Cavicchia (2020-2022) - Coordinator

I am Carlo Cavicchia and I am an Assistant Professor at the Econometric Institute, Erasmus University Rotterdam. In February 2020 I obtained my PhD in Statistics at the Department of Statistical Sciences, Sapienza University of Rome. My research is focused on the methodological and computational aspects of data analysis. The best feeling is when I can use my knowledge to solve practical and real problems. I am currently working on latent variable models, unsupervised classification and model-based composite indicators. At present, I am teaching Data Science for Marketing Analytics at master’s level. For more info about me, see my webpage!

Augusto Fasano (2020-2022) - Secretary

I am Augusto Fasano and I am a Scientific Officer at the Joint Research Centre of the European Commission. I obtained my PhD in Statistics (XXXII cycle) from Bocconi University, where I was jointly advised by Profs. D. Durante and I. Prünster. Prior to the PhD experience, I also had the opportunity to work for almost two years in a multicultural environment at the European Central Bank, before coming back to more research-oriented tasks. Broadly speaking, my research interests lie at the intersection between mathematical statistics and machine learning, with a particular focus on Bayesian inference. In particular, I am working on Bayesian modelling and related computational methods, both exact (Monte Carlo, MCMC and sequential Monte Carlo) and approximate (Variational Inference). If you are interested, you can find out more at my personal page!

Marta Catalano (2020-2022)

I am a Harrison Early Career Assistant Professor in the Department of Statistics at the University of Warwick. My research targets Bayesian nonparametric models for complex data structures, with a particular focus on statistical applications of optimal transport and completely random measures.
Previously, I completed my PhD in Statistics at Bocconi University, under the supervision of Antonio Lijoi and Igor Prünster. I am currently involved in the Bayes Lab at the Bocconi Institute for Data Science and Analytics (BIDSA), where I coordinate a biweekly internal seminar series that brings together PhD students and faculty members. Moreover, I am member of the “de Castro” Statistics Initiative at Collegio Carlo Alberto and in the MIDAS Complex Data Modeling Research Network. More info on my webpage.

Pierfrancesco Alaimo Di Loro (2021-2023)

I am Pierfrancesco Alaimo Di Loro, and I am an Assistant Professor (RTDa) at LUMSA University. My studies have been focused on Bayesian modeling and Markov Chain Monte-Carlo methods, and during my PhD in "Sapienza" I developed a particular interest for the analysis of spatial and spatio-temporal phenomena. I visited Prof. Sudipto Banerjee at UCLA for 1 year, learning tricks and ropes of Bayesian Hierarchical Modeling for large geo-referenced data. Lately, I have been involved in the analysis and media communication of the Italian COVID-19 pandemic data, with emphasis on the interpretability, transparency and reliability of the statistical analyses. My current lines of research involve the modeling of phenomena characterized by complex dependence structures, whether the observations are organized at point-referenced locations or at nodes on a lattice.

Fabio Centofanti (2021-2023)

I am a post-doc researcher at the University of Naples Federico II, where I also completed my PhD in Industrial Engineering (XXXIII cycle) in September 2021, under the supervision of Profs. Biagio Palumbo and Simone Vantini. My research interests regard statistical methodology for the analysis of complex data in the Industry 4.0 framework. I am currently working on functional data analysis methods for regression, clustering, and statistical process control, with a particular focus on robustness and interpretability. During my PhD, I was visiting student at the Department of Mathematics of the Politecnico di Milano and at the Department of Applied Mathematics and Computer Science of the Technical University of Denmark.