research

My main interest is computational and machine learning in the framework of statistical learning theory. In particular I am interested in the problem of learning from small samples of high dimensional data. Learning in such regime raises non trivial problems from the statistical as well as the computational point of view. Empirical studies are often limited by the small amount of available data and the interplay between theory and algorithms becomes a key to build reliable data models. A main feature of my research has been considering the problem of learning from examples within the general framework of ill-posed inverse problems to derive new theoretical results as well as new learning algorithms. I gathered experience in the analysis of financial data, web documents and i am mostly interested into bioinformatics where i am working on transcription binding sites discovery, analisys of gene-arrays expression data and the problem of vertical data integration.