My main research interests lie in the field of statistical multivariate techniques for handling complex multidimensional problems. In particular, in the past years I have carried out theoretical works in three main fields:

- Bayesian Networks: learning Bayesian Networks from data, development of new quasi-Bayesian metrics permitting the use of experts' prior knowledge on structures and the application of new population-based search algorithm to explore the space of structures.

- Composite Indicators and Sensitivity Analysis: building composite indicators to measure socio-economic phenomena with different geographical and time coverage, development of tools for the computation of experts elicited weights, application and development of sensitivity analysis techniques for testing the composite indicator robustness.

- Computational statistics: Development of R libraries for learning Bayesian Networks (MASTINO) and to build composite indicators using R (COMPOSITE)