I am Associate Professor of Statistics for social sciences at the University of Padova and I am affiliated with the GNCS research group of INdAM.

My research has long focused on fuzzy statistics, an area in which I remain actively engaged, particularly in developing methods to address non-stochastic measurement error in the modeling of social and behavioral data. I also study models for latent structure estimation, including approaches to decouple measurement information in both structured and unstructured survey data. I am particularly interested in Bayesian methodologies for modeling complex social and behavioral data, including both approximate and computationally intensive approaches to inference. More recently, I have extended these interests to text and network data, with the aim of integrating diverse sources and uncovering complex patterns in social phenomena.

I completed my doctoral studies at the University of Trento and KU Leuven, combining psychometrics with statistical modeling for behavioral sciences, and later held a postdoctoral position at the Wigner Research Centre for Physics (MTA) in Budapest.

In my research practice, I am guided by the principles of Slow Science.