Paolo Giudici
Paolo Giudici is a data scientist and professor of statistics at the University of Pavia. His research focuses on statistical learning methods to obtain data driven predictions and risk measures in economics, finance and fintech innovations.
 |
| Born |
| March 23, 1965 Sondrio, Italy |
| Nationality |
| Italian |
| Education |
| Bocconi University, Italy, M.Sci. Economics, 1989 |
| University of Minnesota, USA, M.Sci. Statistics, 1990 |
| University of Trento, Italy, Phd Statistics, 1994 |
| Fields |
| Statistics; Machine learning; Finance |
| Institutions |
| University of Pavia (1994-Present) |
| Notes |
| Top Italian Scientist in Business Sciences [1] |
Education and career
Paolo Giudici, born in Valtellina, earned a master's degree in economics from Bocconi University in 1989, a master's degree in statistics from the University of Minnesota in 1990 and a doctorate in statistics from the University of Trento in 1994. He became assistant professor of statistics at the University of Pavia in 1994.
After visiting periods at the University of Bristol, at the University of Cambridge and at the Fields Institute, funded by the European Science Foundation, in 2007 he became full professor of statistics. He has been lecturer of statistics, data science, financial risk management and machine learning classes and has supervised 18 PhD students and 13 post doc researchers within the statistical laboratory of the department of economics and management of the University of Pavia. He is editorial board member of the scientific journals, Risks and Frontiers in Artificial Intelligence.
Research interests
The research activity of Paolo Giudici has developed at the interplay between the academia and the financial industry. He is an elected member of the International Statistical Institute[2] and an executive member of the Italian statistical society[3]. He has been research and training expert for the Bank for International Settlements[4], the European Commission[5], the European University Institute[6], the European Insurance and Occupational Pensions Authority[7], the Centre for European Policy Studies[8], the Bank of Italy[9], the Associazione Bancaria Italiana[10], the Italian National Institute of Statistics[11], the Ministry of Economic Development (Italy)[12]. He has served as an independent board member of Credito Valtellinese from 2010 to 2018[13].
He has been coordinator and principal investigator of several industrial projects and of 12 competitive scientific projects, among which the European Horizon 2020 projects FIN-TECH (2018-2021)[14], PERISCOPE (2020-2023)[15] and the CARIPLO Foundation cultural heritage project "ANTICA PIEVE DI MAZZO” (2006-2010)[16]. He has also coordinated the Pavia unit of the European VI framework project MUSING[17]. He is a research fellow at the University College of London Blockchain centre[18].
Notable pubblications
Research stream 1: Structural learning in high dimensional models
- Giudici P., Green P.J. Decomposable graphical Gaussian model determination. (1999) Biometrika, 86 (4), pp. 785 - 801. DOI: 10.1093/biomet/86.4.785
- Giudici P., Castelo R. Improving Markov Chain Monte Carlo model search for data mining. (2003). Machine Learning, 50 (1-2), pp. 127 - 158, DOI: 10.1023/A:1020202028934
- Brooks S.P., Giudici P., Roberts G.O. Efficient construction of reversible jump Markov chain Monte Carlo proposal distributions. (2003). Journal of the Royal Statistical Society. Series B: Statistical Methodology, 65 (1), pp. 3 - 39. DOI: 10.1111/1467-9868.03711
- Brooks S.P., Giudici P. Markov Chain Monte Carlo Convergence Assessment via Two-Way Analysis of Variance. (2000). Journal of Computational and Graphical Statistics, 9 (2), pp. 266 - 285. DOI: 10.1080/10618600.2000.10474880
Research stream 2: Statistical learning in business and industry
- Giudici, Paolo. Applied data mining : statistical methods for business and industry. (2003). New York: J. Wiley. ISBN 978-0470846780.
- Cornalba C., Giudici P. Statistical models for operational risk management. (2004). Physica A: Statistical Mechanics and its Applications, 338 (1-2 SPEC. ISS.), pp. 166 - 172, DOI: 10.1016/j.physa.2004.02.039
- Giudici P., Passerone G. Data mining of association structures to model consumer behaviour. (2002). Computational Statistics and Data Analysis, 38 (4), pp. 533 - 541, DOI: 10.1016/S0167-9473(01)00077-9
Research stream 3: Explainable machine learning in economics and finance
- Giudici P., Spelta A. Graphical Network Models for International Financial Flows. (2016). Journal of Business and Economic Statistics, 34 (1), pp. 128 - 138. DOI: 10.1080/07350015.2015.1017643
- Giudici P., Abu-Hashish I. What determines bitcoin exchange prices? A network VAR approach. (2019). Finance Research Letters, 28, pp. 309 - 318. DOI: 10.1016/j.frl.2018.05.013
- Bussmann N., Giudici P., Marinelli D., Papenbrock J. Explainable Machine Learning in Credit Risk Management (2021) Computational Economics, 57 (1), pp. 203 - 216
Awards and honours
- 2017: Parliamentary hearing on the impact of financial technologies[19]
- 2016: Best risk management paper from the Global Association of Risk Professionals[20]
- 2013: Honorary membership of the Italian financial industry risk managers association[21]
- 2000: Grant prize for conference on statistical models for data mining from Microsoft research[22]
- 1998: Best research on statistical analysis of consumer habits from Nielsen Corporation[23]
References
- ↑ Paolo Giudici - Top Italian Scientist in Business Sciences
- ↑ ISI Membership Elections 2022: Third round results
- ↑ Società Italiana di Statistica
- ↑ Press release: BIS Innovation Hub and Bank of Italy announce shortlist and judges for the G20 green and sustainable finance challenge
- ↑ Model: UNIPV-BayesINGARCHX - Zoltar
- ↑ FBF will host a workshop on Artificial intelligence and Machine Learning in finance - Florence School of Banking and Finance
- ↑ EIOPA establishes Consultative Expert Group on Digital Ethics in Insurance
- ↑ Monitoring Covid-19 contagion growth in Europe – CEPS
- ↑ Bank of Italy - FinTech Milano Hub: Call for Proposals 2021 - list of selected projects
- ↑ Relatori 2021 - Supervision, Risks & Profitability
- ↑ I gruppi sociali nel Rapporto Istat 2017
- ↑ Intelligenza artificiale e blockchain: Prof. Paolo Giudici UniPV selezionato tra gli esperti dal Ministero dello Sviluppo Economico
- ↑ assemblea dei soci del credito valtellinese assemblea dei soci del
- ↑ A FINancial supervision and TECHnology compliance training programme - CORDIS - European Commission
- ↑ Pan-European Response to the ImpactS of COVID-19 and future Pandemics and Epidemics - CORDIS - European Commission
- ↑ Progetto “Circuito Antica Pieve di Mazzo”. Se ne discute domenica alla Campionaria di Milano - TELLUS folio - stampa
- ↑ MUlti-Industry, Semantic-based Next Generation Business INtelliGence - CORDIS - European Commission
- ↑ Associates | UCL Blockchain
- ↑ XVII Legislatura - XVII Legislatura - Comunicazione - Archivio di Prima Pagina - Audizione su tecnologia finanziaria
- ↑ EFMA 2016 Conference Awards
- ↑ Organi Sociali - www.aifirm.it
- ↑ Statistical Models for Data Mining
- ↑ Data mining of association structures to model consumer behaviour
