Omiros Papaspiliopoulos

Omiros Papaspiliopoulos

Universitat Pompeu Fabra

Social & Behavioural Sciences

Previously to becoming ICREA Research Professor I had been Research Associate at Lancaster and Oxford University, Assistant Professor at Warwick University, and Professor at UPF. I am currently the director of the Masters in Data Science and the Data Science Center at Barcelona GSE. I have extensively published in the top journals in Statistics, have served as Associate Editor for several journals and as of January 2018 as Deputy Editor for Biometrika. I have delivered more than 100 invited talks & seminars, and given courses at ENSAE in Paris, the Berlin Mathematical School, the Department of Mathematics at University of Copenhagen, the Engineering Department at Osaka University, CEMFI. In 2010 I was awarded the Royal Statistical Society's Guy Medal in Bronze, which is arguably the highest distinction in Statistics in Europe.


Research interests

I am involved with the whole spectrum of Data Science, from real practical problems to serious mathematics for developing and analyzing methods. My current research evolves along the following three non-orthogonal axes: Axis 1: Methodological work in the intersection of Statistics, Machine Learning and Applied Mathematics; Axis 2: Data Science within Social Sciences; Axis 3: Applied Machine Learning projects. Major subtheme in Axis 1  is scalable Bayesian computation. Bayesian models provide an excellent framework for synthesizing heterogenous data, learning and predicting with big but sparse data, and  principled regularization in high-dimensional models. Scalable Bayesian computation refers to computational methods for solving large scale Bayesian learning problems whose complexity scales favourably with the amount of data and parameters, ideally as a linear function of these two quantities. This is enourmously important in practice: it makes an approach realistic for large scale applications. Within Axis 2 I have been involved in a range of application that despite their apparent diversity they have important common components and strong links with Axis 1: predicting electoral outcomes in elections with emerging political parties, long-term forecasting of real estate prices at zip-code level;  understanding channels of central bank communication; surveilance and prediction of social unrest.  As founder and director of the Barcelona Graduate School of Economics Data Science Center (DSC), I have been involved in all the projects the DSC undertakes and fall within Axis 3. Recent collaborations include the Reuters Institute for the  Study of Journalism in Oxford, Accenture Health Analytics, Banco de España, ZDF (German public-service television broadcaster).

Selected publications

– Montalvo JG, Papaspiliopoulos O, Stumpf-Fétizon T 2019, “Bayesian forecasting of electoral outcomes with new parties’ competition”, European Journal of Political Economy, 59, pp.52-70.


Selected research activities

Book Reviews:

High-Dimensional Probability by R. Vershynin, for the Bachelier Finance Society Newsletter

Editorial activities and reviewing for major funding bodies:

  • Deputy Editor for Biometrika
  • Finnish Academy of Sciences: member of a six-people panel that decides on the whole funding program of the Academy for the scientific fields of Statistics and Applied Mathematics.
  • Associate Editor for SIAM Journal of Uncertainty Quantification

Conference organization:

  • Scientific committee member for European Meeting of Statisticians, Palermo, July 2019
  • Co-organised a BGSE Summer Forum on Machine Learning for Economics

Seminars:

  • Department of Mathematics, University of California San Diego, March 2019
  • Department of Statistics, University of California Santa Cruz, March 2019

Public lectures:

  • Is attention in Twitter turned to the extremes? (Pint of Science, Athens)

Academic Leadership:

  • In the BGSE: Director of the Data Science Center; Director of the Master in Data Science; Director of the Summer School in Data Science; and Director of the Winter School in Data Science.

Research stays:

  • Caltech, February 2019
  • Courant Institute, March 2019

Funding:

  • BBVA grant (co-PI)
  • Plan Estatal (co-PI)