TOMMASO MINERVA, Senior Advisor

Tommaso Minerva is a Researcher of Statistics at the University of Modena, Italy. In 1992 he earned a Ph.D. in Physics of Matter from the University of Parma. His early interests were in computational physics, mainly parallel and vectorial computing, applied to electronic structure simulation of high temperature superconductors. He also studied the collective effects of many body interactions on the electronic structure of cuprate oxides and high temperature superconductors. He served in the Department of Physics at the University of Modena and in the Faculties of Economics at the University of Modena and Venezia. He has spent a couple of years at the IBM Research Labs at Almaden in San Jose working on electronic and magnetic properties of cuprate oxides and developing simulation code within a parallel computing environment. He is author of articles both in physics and statistical journals. His main, actual, research interest is in the development of artificial intelligence techniques for modeling and analyzing high dimensional data. In particular, he applies neural networks, genetic algorithm, fuzzy systems and wavelet filtering to model selection problems as well cellular automata as a tool for agent based simulation. Recently he has applied these techniques to the prediction of high tides in the Venetian laguna and of financial time series, as well as to the characterization of industrial districts. He developed a tool for genetic modelling and a package for dynamical portfolio allocation. He is also exploiting the use of physical paradigma to study complex economical systems. In this field he recently applied the Ising model to characterize the transition from plan to market in Russia and China.