Description

The current research of the Group addresses the development of new Machine Learning methodologies. The research is aimed at defining frameworks for the development of intelligent systems in different application fields, able to describe and exploit significant results of soft-computing, including its integration with symbolic methodologies.

The design of learning algorithms includes Neural Networks, Probabilistic models, Reservoir Computing models, Kernel-based methods, Support Vector Machines, Adaptive Processing of Structured Data, and other Pattern Recognition techniques.

The application fields include BioInformatics, ChemInformatics, Robotics, Image Processing and Web-Based Systems for Medicine. This is particularly important because of the fast growth of information sources due to the explosion in the use of Internet and of the new IT capabilities that results from the exploitation and integration of different intelligent approaches.

The Group has participated in many EU and Italian funded projects.

Topics

Methodologies		Application Fields
Machine Learning Machine Learning and Neural Networks for Structured Domains Neural Networks Unsupervised Learning Generative Approaches Reservoir Computing Kernel-based methods Data Mining		ChemInformatics (QSPR/QSAR, Toxicology) BioInformatics Robotics and Wireless Sensor Networks Web Signal and Image Analysis Telemedicine (Electronic Patient Records)

• “Robotics UBIquitous COgnitive Network” EU FP7 RUBICON