Paolo Giudici

Professor of Statistics and Data Science at the Department of Economics and Management, University of Pavia

Professor of Statistics and of Financial data science. Supervisor of about 180 Master's students and of 16 Phd students, currently working in the financial industry, in IT/consulting companies or as academic researchers. Author of several scientific publications (89 in Scopus, with 1301 total citations and an h-index of 21). The publications have appeared in: Journal of the Royal Statistical Society, Biometrika, Journal of Business and Economics Statistics, Journal of the operational research society, Computational Statistics and data analysis, Journal of Computational and graphical statistics, Expert systems with applications, Machine Learning, Neurocomputing, Journal of Banking and Finance, Journal of Financial Stability, Finance research letters. Coordinator of 12 funded scientific projects, among which the European Horizon2020 projects “PERISCOPE: Pan-European response to the impacts of covid-19 and future pandemics and epidemics (2020-2023)”, “FIN-TECH: Financial supervision and Technological compliance" (2019-2020). Editor of "Artificial Intelligence in Finance", Frontiers. Associate Editor of “Digital Finance”, Springer; and of "Risks", MDPI . Member of the National committee for the career progression of statistics professors (ASN 2018-2020).Member of the HR committee of the Department of Economics and Management, University of Pavia. Research fellow at the Bank for International Settlements and at the University College London center for Blockchain technologies. Expert at the European Insurance and Occupational Pensions Authority (EIOPA). Expert at the Italian ministry of development for the National AI strategy. Member of the steering committee of the Italian Statistical Society (SIS), of the Association of Italian Financial Risk Managers (AIFIRM) and of the European Network for Business and Industrial Statistics (ENBIS). Member of the European Big Data Value Association (BDVA) , the International Society for Bayesian Analysis (ISBA), the Italian Econometric Society (SIDE),’ the International Association for applied econometrics (IAEE), the Cryptovalues association, AssoFintech. Principal investigator of research, training and consulting projects for: the Italian Banking Association, Intesa SanPaolo, Unicredit, UBI, BancoBpm, MPS, BPS, Creval, Accenture, KPMG, SAS, Mediaset, Sky.

Paolo is speaking at

Application Track 2 - Health
November 4, 2020
4:00 pm - 5:30 pm

Speakers

  • Paolo Giudici (Speaker) Professor of Statistics and Data Science at the Department of Economics and Management, University of Pavia
  • Martina Barbero (Speaker) Operations Manager, Big Data Value Association
  • Anna Cattani-Scholz (Speaker) Delegate for Key Technologies - Brussels office, Helmholtz Association
  • Andrew Emerson (Speaker) Application specialist, CINECA
  • Saila Rinne (Speaker) Head of Sector - EU policies, DG CONNECT, Unit "eHealth, Well-Being and Ageing", European Commission
  • Ralf Heyder (Speaker) Head of Administrative Office for External Networking and Strategic Partnerships - Coordinator of the National Research Network of University Medicine on Covid-19, Charité – Universitätsmedizin Berlin

Description

Most research programmes and projects which were launched at the very beginning of the COVID19 crisis are today in full speed and starting to produce results. The European Commission and national governments reacted fast in establishing specific calls for projects and initiatives for supporting R&I activities aimed at addressing the COVID 19 challenges. Many of these calls and initiatives involved the use of Big Data, Data Analytics or Artificial Intelligence technologies.

In this context and taking into account that a majority of project is still ongoing and more might come, it is worth looking at the experience of a) policy makers who set up AI and Big Data related COVID 19 funding instruments and/or reprioritised their R&I activities in these areas and b) research organisations who have started COVID 19 related projects leveraging AI and Big Data. In particular, this parallel session will address the following questions:
  • Were the calls and programmes established relevant instruments for leveraging AI and Big Data technologies in order to address the COVID 19 pandemic? Has the potential of AI and Big Data been sufficiently exploited?
  • What can be learnt from the experience of the Covid19 crisis in terms of flexibility of R&I programmes for AI and Big Data and adaptability of procedures and calls?
  • What have been the effects and preliminary outcomes of the Big Data and AI projects which were funded during the crisis and what has been the experience of research organisations in participating in such calls?
  • What needs to happen next for ensuring the impact of the programmes and projects funded in these areas? Is there a need for new funding activities?
By steering a discussion between policy makers and receivers of funding for Big Data and AI projects addressing COVID 19, this parallel session will try to draw a number of lessons on the importance of AI and Big Data R&I during the pandemics and discuss how to ensure the impact of the initiatives funded.

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