Irene POLI
- Qualifica
- Senior Researcher
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irenpoli@unive.it
- SSD
- STATISTICA [SECS-S/01]
- Sito web
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www.unive.it/persone/irenpoli (scheda personale)
- Struttura
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Centro Europeo Interuniversitario di Ricerca - European Center for Living Technology
Sito web struttura: https://www.unive.it/eclt
Sede: Ca' Bottacin
- Struttura
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Dipartimento di Scienze Ambientali, Informatica e Statistica
Sito web struttura: https://www.unive.it/dais
Sede: Campus scientifico via Torino
Irene Poli is Research Professor of Statistics at the European Centre for Living Technology (ECLT, www.ecltech.org), 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 served 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), and as Professor at the Universities of Bocconi, Bologna, Modena, and Ca’ Foscari. 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, European Commission’s Directorate of Information Technologies (PACE, EU-FP6, www.istpace.org, 2004-2008); Designing Informative Combinatorial Experiments, Foundation Grant (DICE, 2006-2010); Development of systematic packages for deep energy renovation of residential and tertiart buildings including envelope and systems, European Commission’s project (iNSPiRe - FP7-NMP-ENV-ENERGY-ICT-EeB, 2012-2016); New pathways for sustainable urban development in China’s medium-sized cities, European Commission's EuropeAid project (MEDIUM-EU-CHINA Research and Innovation Partnership ICI, 2015-2018); Building Lead Optimization Over large Molecular spaces (BLOOM, Research Agreement with GlaxoSmithKlein, London, UK; 2014- now). Her current research interests are in: statistical models for high dimensional small data, nonlinear time series, predictive neural networks; machine learning procedures; evolutionary designs for optimization.
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