Statistical learning and
Our research focuses on the study of the theoretical foundations
of learning; study and development of learning methods; design
and implementation of mathematically sound methods for extracting
visual information from images and image sequences.
The group is currently involved in the following projects:
- FIRB Project for the scientific and technological cooperation
Italy-USA: Learning theory and engineering applications.
(Partners are MIT and the Universities of Genova and Pavia).
The project studies scientific problems of learning theory
and explores a number of engineering applications. The lab
is involved on both theoretical and application aspects,
including computer vision and bioinformatics applications.
- EU Integrated Project Health-e-child,
whose main objective is to devise an integrated platform
for European paediatrics based on a grid-enabled network
of leading clinical centers.
Within the project the lab is mainly involved in three activities:
data processing for the construction of integrated desease
models that exploit all the available information levels
(medical images, genomic and proteomic data); model analysis
and design of data-base guided decision support systems;
information fusion and data mining for biomedical knowledge
- EU Network of Excellence PASCAL
(Pattern Analysis, Statistical modelling and ComputAtional
The objective of the network is to build a Europe-wide Distributed
Institute which will pioneer principled methods of pattern
analysis, statistical modelling and computational learning
as core enabling technologies for multimodal interfaces
that are capable of natural and seamless interaction with
and among individual human users.