I would like to think of myself as a scientist, who happens largely to specialise in the use of statistics.

– David Cox

My primary research interests concern robust statistics, high-dimensional modeling and computational statistics.

I am currently part of the research group of Stéphane Guerrier and Maria-Pia Victoria-Feser at the Research Center for Statistics – Geneva School of Economics and Management – Université de Genève.

I obtained my PhD in Data Science at Scuola Normale Superiore (cum laude) in 2022, with a thesis on “Approaches for Outlier Detection in Sparse High-Dimensional Regression Models”, where I developed statistical methods for analyzing sparse regression problems affected by different forms of adversarial data contamination. The developed methodologies encompass continuous optimization methods as well as mixed-integer programming techniques. I applied these tools to analyze biomedical data and to investigate the main possible drivers of honey bee colony loss.

Between 2021 and 2022, I was a Research Fellow at Sant’Anna School for Advanced Studies, and a Research Associate at the Italian National Research Council. Between 2019 and 2020, I spent a period in the United States as a visiting scholar at Penn State University, where I worked with Runze Li and Francesca Chiaromonte. In 2017 I had a traineeship at the Joint Research Center of the European Commission, where I worked with Domenico Perrotta, and I received a M.Sc. (cum laude) from the University of Parma, where I worked with Marco Riani on a thesis entitled “A Modern Approach to Robust Regression”. I am also a developer of the FSDA MATLAB Toolbox and a member of the Robust Statistics Academy.