The group of Statistics is characterized by its intense methodological and applied research activity aimed at the development of models and algorithms for the statistical analysis of complex and high-dimensional data coming from numerous application fields, including: biomedical sciences, medicine and public health, transport, energy and industry, Earth and Universe sciences and social sciences. In detail, the methodological research pursued by the group is aimed at the development of non-parametric, semi-parametric or parametric methods of Bayesian, likelihood-based or algorithmic nature for the supervised and non-supervised analysis of functional, hierarchical, non-Euclidean and non-structured data possibly also with spatial and/or temporal dependence.

The group collaborates intensely and works in synergy with other departments of the Politecnico di Milano and of other universities, research centers, institutions and companies on the national and international scene.

The members of the group hold numerous courses in both basic and advanced statistics in bachelor's, master's and doctoral courses at the Politecnico di Milano. Among these, the one with the greatest exposure of the group are the Statistical Learning track of the master's degree in Mathematical Engineering, the Ph.D. program in Mathematical Models and Methods in Engineering and the Ph.D. program in Data Analytics & Decision Sciences.

Many members of the group develop their research activity within the MOX Laboratory, in the Statistics group of MOX Laboratory.