Research @ CMP

Coordinator: Riccardo Zecchina

The research interest of our group lies at the interface between statistical physics, computer science, information theory and computational biology. Its main themes include equilibrium and out-of-equilibrium phenomena in disordered systems, statistical physics of inverse problems, statistical inference and combinatorial optimization, probabilistic message-passing algorithms, stochastic processes, randomized algorithms, graphical games and coding. Currently we are focused on the understanding and the development of probabilistic message passing algorithms (MPA) of different degrees of complexity.

MPA have been developed in the last few years in the context of Statistical Physics of Constraint Satisfaction Problems where they have proven to be effective in dealing with optimization problems over random structures. In many cases, MPA are able to explore efficiently the space of solutions in parallel, maintaining a fully distributed updating scheme that keeps the computational effort at a low level. The main field of applications of our techniques is large scale inverse problems in Computational Biology. The members of the group cover a wide spectrum of competence, from statistical physics, to computer science and information theory, to computational biology and computational neuroscience. The research activity in computational biology is supported by Microsoft External Research Initiative.