Welcome to my personal web page!
I’m a Postdoctoral Associate in Statistics at the Department of Mathematics, University of Maryland, College Park, mentored by Lizhen Lin. Previously, I was a Robert and Sara Lumpkins Postdoctoral Fellow in Statistics at the Department of Applied and Computational Mathematics and Statistics, University of Notre Dame, with the same mentor. I’m an external affiliate of the Bayesian Learning Laboratory, a research unit of the Bocconi Institute for Data Science and Analytics (BIDSA).
My research interests include topics in Bayesian nonparametrics and statistical properties of deep generative models. I am currently working on random partition and permutation structures for multilayer and dynamic network data, posterior consistency for stochastic block models and conditional deep generative models.
I received my Ph.D. in Statistics at Bocconi University, advised by Antonio Lijoi and Igor Prünster.
Previously, I’ve obtained a bachelor and a master in Mathematics, focused on probability theory and functional analysis, both at Università di Roma Tor Vergata. My master thesis was about functional data analysis in the space of square-integrable functions on the sphere, supervised by Domenico Marinucci.
I had music education at Conservatorio Licinio Refice in Frosinone. I play clarinet and bass clarinet.
Research Interests
- Bayesian nonparametrics:
- Linear functionals of random probability measures
- Modelling complex network structures with generalized exchangeability
- Posterior consistency in stochastic block models
- Deep generative models:
- Conditional density estimators based on integral probability metrics and diffusion models