Irene Poli is Research Professor of Statistics at ECLT, of which she is a founding member and currently Chair of the Science Board. She leads the ECLT Complexity and Data Analysis group, developing procedures to design informative experiments and to model high dimensional data. She has served as Professor (at the Universities of Bologna, Modena, Bocconi and Ca’ Foscari) and as research scientist at the Imperial College of Science and Technology of London (UK), at the Centre for Non-linear Science (CNLS) of the Los Alamos National Laboratory (California University, USA), and at the Santa Fe Institute (NM, USA). She is Fellow of the New York Academy of Science, the Bernoulli Society, the Italian Statistical Society, and the Royal Statistical Society. She is (or has been) Partner and Coordinator of several large interdisciplinary and international research projects, including Programmable Artificial Cell Evolution (PACE, EU-FP6, www.istpace.org), Design and Building Lead Optimization Over Large Molecular Space (BLOOM, Research Agreement with GlaxoSmithKlein; 2013 - now).
models for high dimensional small data, nonlinear time series, deep learning neural networks; machine learning procedures; evolutionary designs for optimization.
Last update: 13/02/2020