Biography:Paolo Giudici

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Paolo Giudici is an Italian 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.

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 an assistant professor of statistics at the University of Pavia in 1994.

After visiting periods at the University of Bristol, the University of Cambridge, and the Fields Institute, funded by the European Science Foundation, in 2007 he became a full professor of statistics. He has been a lecturer of statistics, data science, financial risk management, and machine learning classes and has supervised several Ph.D. students and postdoc researchers within the statistical laboratory of the department of economics and management of the University of Pavia. He is an editorial board member of the scientific journals Fintech, Risks, and Frontiers in Artificial Intelligence. He is a research fellow of the University College of London Blockchain centre, and a Top Italian Scientists [1]

The research activity of Paolo Giudici has developed the interplay between academia and the financial industry. He is an elected member of the International Statistical Institute and an executive member of the Italian statistical society. He has received a prize for the best 2016 risk management paper from the Global Association of Risk Professionals and he is an honorary member of the Italian financial industry risk managers association. He has been a research and training expert for the Bank for International Settlements,[2] ,the European Commission, the European University Institute,[3] the European Insurance and Occupational Pensions Authority,[4] the Centre for European Policy Studies, the Bank of Italy, the Deutsche Bundesbank, the Associazione Bancaria Italiana, the Italian National Institute of Statistics, the Ministry of Economic Development (Italy).[5] He has served as an independent board member of Credito Valtellinese from 2010 to 2018.[6]

He has been the 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) [7] and PERISCOPE (2020-2023),[8] and the CARIPLO Foundation cultural heritage project "ANTICA PIEVE DI MAZZO” (2006-2010).

Selected books

  • Giudici, Paolo (2003). Applied data mining : statistical methods for business and industry. New York: J. Wiley. ISBN 978-0470846780.[9]
  • Giudici, Paolo (2009). Applied data mining for business and industry (2nd ed.). Chichester, U.K.: Wiley. ISBN 978-0470058862.[10]

Selected publications

  • 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
  • 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
  • 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

References

  1. "Paolo Giudici" (in en). https://en.wiki.topitalianscientists.org/Paolo_Giudici. 
  2. "BIS Innovation Hub and Bank of Italy announce shortlist and judges for the G20 green and sustainable finance challenge" (in en). 25 June 2021. https://www.bis.org/press/p210625.htm. 
  3. "FBF will host a workshop on Artificial Intelligence and Machine learning in finance" (in en). 3 June 2022. https://fbf.eui.eu/fbf-will-host-a-workshop-on-artificial-intelligence-and-machine-learning-in-finance/. 
  4. Delcea, Ramona (19 December 2019). "EIOPA establishes Consultative Expert Group on Digital Ethics in Insurance" (in en). https://www.eiopa.europa.eu/media/news/eiopa-establishes-consultative-expert-group-digital-ethics-insurance_en. 
  5. "Intelligenza artificiale e blockchain: Prof. Paolo Giudici UniPV selezionato tra gli esperti dal Ministero dello Sviluppo Economico" (in it-IT). http://news.unipv.it/?p=36520. 
  6. "Paolo Giudici" (in en). https://cepr.org/about/people/paolo-giudici. 
  7. A FINancial supervision and TECHnology compliance training programme, European Union, https://cordis.europa.eu/project/id/825215/ 
  8. Pan-European Response to the ImpactS of COVID-19 and future Pandemics and Epidemics, European Union, https://cordis.europa.eu/project/id/101016233 
  9. "A Review of: "Applied Data Mining – Statistical Methods for Business and Industry"". IIE Transactions 38 (12): 1131–1131. 1 December 2006. doi:10.1080/07408170600582880. ISSN 0740-817X. https://www.tandfonline.com/doi/abs/10.1080/07408170600582880. 
  10. Pardo, J. A. (1 August 2011). "Paolo Giudici and Silvia Figini: Applied data mining for business and industry (Second Edition)" (in en). Statistical Papers 52 (3): 739–740. doi:10.1007/s00362-010-0310-0. ISSN 1613-9798. https://link.springer.com/article/10.1007/s00362-010-0310-0. 

External links