Research Themes


Our goal is to study and develop computational methods and models for the understanding of biological processes. The starting point is often derived from our work in learning theory and algorithms with particular emphasis on the problems related to the role played by prior knowledge and the... Read more


We explore the multifaceted world of image and scene understanding combining computer vision and machine learning ingredients. Computer vision methods are used to extract information from the visual signals, while we resort to machine learning to model variability, and to gain robustness and... Read more


We focus on the mathematical aspects of Learning Theory to the purpose of developing algorithms which can effectively learn the solution to a given problem from small samples. Our approach is based on the theory of regularization of ill-posed inverse problems and uses methods from functional... Read more


The main research theme is to develop multi-scale methods for signal and image processing and to design efficient algorithms for signal enhancement and feature detection. The focus is both on the mathematical theory in the framework of non-commutative harmonic analysis and on the applications... Read more


We analyze the effects of current visual technologies (e.g. 3D displays, mobile devices, virtual and augmented reality headsets) on the human perceptual system. In particular, we aim to assess the undesired effects on the users (such as the visual fatigue and the perceptual discomfort), and to... Read more