Research

In contemporary science, I find statistics to be an essential tool to understand phenomena, and to draw reliable conclusions. I am broadly interested in the analysis of large and complex data, with particular emphasis on structured objects such as functional data and networks. I am also involved in projects at the intersection of computer science, optimization, and statistical learning, where computational feasibility and inferential stability play crucial roles.

Ongoing projects

Currently, I am taking classes as core requirements of my Ph.D. at CMU. I am trying to work on the following research projects in some of my spare time:

• Functional Feature Selection, jointly with Tobia Boschi, Francesca Chiaromonte and Matthew Reimherr. This is a poster on FAStEN, an efficient algorithm for feature selection and coefficient estimation in functional regression models. The preprint is available here

• The Weighted Climate Dataset Project, together with Marco Gortan, Giorgio Fagiolo and Francesco Lamperti. The paper introducing this tool is available here

• COVID-19 Project, a joint work with Tobia Boschi, Jacopo Di Iorio, Francesca Chiaromonte and Marzia A. Cremona. Results of our first paper appeared in the news [1], [2, Italian], [3, Italian], and as a SciPod’s audio book. A second paper is now available as a preprint here!

Previous projects

I have also been involved in a project on the analysis of the determinants of success of start-ups financing through venture capitals. Results, which were obtained and validated with a combination of network, functional data and multivariate analysis tools, were published here (as a journal article) and here (as a conference proceeding). This is a very short and informal presentation of the results (in Italian).

You can find my publication list in my CV and on my Google Scholar profile.