i got my master degree in physics from the university of genova and my major was signal processing and cybernetics. my master thesis, supervised by alessandro verri and entitled "on the choice of the regularization parameter in learning theory", considered the problem of parameter tuning for support vector machines classification.

after graduation i worked as a consultant in the start-up SLAM - statistical learning applied to markets, dealing with statistical models for financial data.

during my PhD i worked under the supervision of alessandro verri and ernesto de vito focusing on the connections and interplays between learning from examples and inverse problems. though my work focused especially on theoretical and foundational issues, during this period i also made experience in the analysis of various kind of data. some of the problem i worked on are text categorization and transcription factors binding sites discovery. during my PhD i had the opportunity to spend quite a good amount of time abroad visiting the Center for Biological and Computational Learning at MIT, Toyota Technological Institute at Chicago (TTI-Chicago) and the Johann Radon Institute for Computational and Applied Mathematics.

my research interests are the various aspects of learning from examples both from the theoretical and the applied point of view. in particular i am interested into the connections between learning theory and regularization of ill-posed inverse problems