Data Science Research

Main research directions

  • Applied Statistics, Management Science
  • Graphical Models and Network Analysis
  • High-dimensional Statistics
  • Stochastic Analysis and Malliavin Calculus
  • Bayesian Statistics and Monte Carlo Methods
  • Time Series and Econometrics

Forthcoming publications

Alphabetical by first author's name. Last updated: December 2019

Forthcoming L. Beauchemin, M. Slifker, D. Rossell, and J. Font-Burgada

Characterizing MHC-I genotype predictive power for oncogenic mutation probability in cancer patients

Immunoinformatics, Methods and Protocols. Springer, in press, 2019

ForthcomingR. Gavard, D. Palacio Lozano, A. Guzman, D. Rossell, S. Spencer, and M. Barrow

Rhapso: Automatic stitching of mass segments from Fourier transform ion cyclotron resonance mass spectra

Analytical Chemistry, in press. 2019

Forthcoming G. Lugosi, and S. Mendelson

Risk minimization by median-of-means tournaments

Journal of the European Mathematical Society

Forthcoming G. Lugosi, and S. Mendelson

Near-optimal mean estimators with respect to general norms

Probability Theory and Related Fields, to appear, 2019

Forthcoming G. Lugosi, and S. Mendelson

Regularization, sparse recovery, and median-of-means tournaments

Bernoulli, to appear, 2018

Forthcoming J.G. Montalvo, O. Papaspiliopoulos and T. Stumpf-Fetizon

Predicting election results with emerging parties

European Journal of Political Economy

Forthcoming D. Rossell, and M.F.J. Steel

Continuous mixtures with skewness and heavy tails.

In Handbook of mixture analysis, Chapter 10, CRC press

A selection of recent publications
  • An Introduction to Sequential Monte Carlo by O. Papaspiliopoulos and N. Chopin. Springer, 2020.
  • On choosing mixture components via non-local priors by J. Fúquene, M.F.J. Steel, and D. Rossell. Journal of the Royal Statistical Society B, 2019, 81, 5, 809-837.
  • Maximum likelihood estimation in Gaussian models under total positivity by S. Lauritzen, C. Uhler, and P. Zwiernik. Annals of Statistics, 2019, Vol. 47, No. 4, 1835-1863.
  • Sub-Gaussian estimators of the mean of a random vector by G. Lugosi, and S. Mendelson. Annals of Statistics, 2019, Vol. 47, No. 2, pp 783-794.
  • Variable selection in compositional data analysis using pairwise logratios by M. GreenacreMathematical Geosciences, 2018, 1-34.
  • Learning and hierarchies in service systems by Bimpikis, Kostas, and M.G. Markakis. Management Science, 2018.
  • Auxiliary gradient‐based sampling algorithms by Titsias, Michalis K., and O. Papaspiliopoulos. Journal of the Royal Statistical Society: Series B, (Statistical Methodology) 80.4, 2018, pp 749-767.
  • Tractable Bayesian variable selection: beyond normality by D. Rossell and F.J. Rubio. Journal of the American Statistical Association, 2018, pp 1-17.
  • Nonlocal priors for high-dimensional estimation by D. Rossell and D. Telesca. Journal of the American Statistical Association, 2017, 112.517, pp 254-265.
  • Maximum likelihood estimation for linear Gaussian covariance models by P. Zwiernik, C. Uhler, and D. Richards. Journal of the Royal Statistical Society: Series B, 79(4), 2017, 1269–1292.
  • A Unifying Theory of Tests of Rank by M. Al-Sadoon. Journal of Econometrics, Volume 199, Issue 1, July 2017, Pages 49-62. 
  • Total positivity in Markov structures by S. Fallat, S. Lauritzen, K. Sadeghi, C. Uhler, N. Wermuth, and P. Zwiernik. Annals of Statistics 2017, Vol. 45, No. 3, 1152-1184.
  • Set estimation from reflected Brownian motion by A. Cholaquidis, R. Fraiman, G. Lugosi, and B. Pateiro-López. Journal of the Royal Statistical Society: Series B, 2016, 78:1057–1078.
  • Sub-Gaussian mean estimators by L. Devroye, M. Lerasle, G. Lugosi, and R. Imbuzeiro Oliveira. Annals of Statistics, 2016, 44:2695-2725.
  • Valuation of Barrier Options Via a General Self‐Duality by E. Alòs, Z. Chen, and T. Rheinländer. Mathematical Finance, 2016, 26:3, pp 492–515.
  • Almost optimal sparsification of random geometric graphs by N. Broutin, L. Devroye, and G. Lugosi, Annals of Applied Probability, 2016, 26:5, 3078-3109.
  • On probability laws of solutions of differential systems driven by fractional Brownian motion by F. Baudoin, E. Nualart, C. Ouyang, and S. Tindel, Annals of Probability, 2016, 44, pp 2554-2590.
  • Exact sampling of diffusions with a discontinuity in the drift by O. Papaspiliopoulos, G. Roberts, and K. Taylor, Advances in Applied Probability, 2016, 48(A), 249-259.
  • Inventory Pooling under Heavy-Tailed Demand, K. Bimpikis, M. Markakis, Management Science, 2016, 62(6), 1800-1813.
  • Exponential varieties by M. Michałek, B. Sturmfels, C. Uhler, and P. Zwiernik, Proceedings of the London Mathematical Society (3) 112 (2016), no. 1, 27–56.
  • On the short-maturity behaviour of the implied volatility skew for random strike options and applications to option pricing approximation by E. Alòs and J. León, Quantitative Finance 16.1 (2016): 31-42.
  • Empirical risk minimization for heavy-tailed losses by C. Brownlees, E. Joly and G. Lugosi, Annals of Statistics, 2015, 43(6), 2507-2536.
  • Analysis of the Gibbs sampler for hierarchical inverse problems by S. Agapiou, J. Bardsley, O. Papaspiliopoulos and A. Stuart Journal on Uncertainty Quantification (SIAM/ASA) 2014.
  • Throughput Optimal Scheduling over Time-Varying Channels in the presence of Heavy-Tailed Traffic by K. Jagannathan, M. Markakis, E. Modiano, J.N. Tsitsiklis, IEEE Transactions on Information Theory, 60(5), 2014.
  • Disentangling Systematic and Idiosyncratic Risk for Large Panels of Assets by M. Barigozzi, C. Brownlees, G. M. Gallo and D. Veredas Journal of Econometrics, 2014, 182: 364-382
  • Geometric and Long Run Aspects of Granger Causality by M. Al-Sadoon, Journal of Econometrics, 2014, 178: 558–568.
  • Groups acting on Gaussian graphical models by J. Draisma, S. Kuhnt, and P. Zwiernik, Annals of Statistics, 2013, 41:4, 1944-1969
  • SMC2: an efficient algorithm for sequential analysis of state-space models by N. Chopin, P. Jacob and O. Papaspiliopoulos, Journal of the Royal Statistical Society: Series B, 2013, 75: 397–42
  • Bayesian model selection in high-dimensional settings by V.E. Johnson and D. Rossell, Journal of the American Statistical Association, 2012, 107(498): 649-660.
  • Sharp threshold for percolation on expanders by I. Benjamini, S. Boucheron, G. Lugosi, and R. Rossignol, Annals of Probability, 2012, 40:130–145.
  • Detection of correlations by E. Arias-Castro, S. Bubeck, and G. Lugosi, Annals of Statistics , 2012, 40: 412-435.
  • Critical Brownian sheet does not have double points by R.C. Dalang, D. Khoshnevisan, E. Nualart, Y. Xiao, and D. Wu, Annals of Probability, 2012 40: 1829-1859
  • Bayesian non-parametric hidden Markov models with applications in genomics by C. Yau, O. Papaspiliopoulos, G. O. Roberts, and C. Holmes, Journal of the Royal Statistical Society: Series B, 2011 73(1):37-57
  • Comparison of Volatility Measures: A Risk Management Perspective by C. Brownlees and G. M. Gallo, Journal of Financial Econometrics, 2010 8: 29-56
    Winner of the 2013 Robert Engle young scholar award for best paper published in 2010, 2011 and 2012.
Current editorial services

Christian Brownlees:
Annals of Financial Economics, Econometrics, Journal of Network Theory in Finance, Journal of Risk and Financial Management 

Gábor Lugosi:
Annals of Applied Probability, Journal of Machine Learning Research, Probability Theory and Related Fields 

Eulàlia Nualart:
Stochastic Processes and their Applications (Associate Editor)

Omiros Papaspiliopoulos:
Biometrika (Deputy Editor), SIAM Journal of Uncertainty Quantification 

David Rossell:
Bayesian Analysis (Associate Editor)

Piotr Zwiernik:
Biometrika, Journal of Algebraic Statistics, Scandinavian Journal of Statistics

Research and consulting projects

"Prediccion, Inferencia y Computacion en Modelos Estructurados de Alta Dimension"

  • Reference: PGC2018-101643-B
  • Financing entity: Ministerio de Economía y Competitividad (MINECO)
  • Dates: 2019-2021
  • Principle investigators: Gábor Lugosi, Omiros Papaspiliopoulos
  • Amount: € 141,812

"Algorithms and Learning for AI"

  • Financing entity: Google
  • Dates: 2018-2020
  • Principle investigator: Gabor Lugosi
  • Amount: USD 150,000

“High-dimensional problems in structured probabilistic models”

  • Financing entity: Fundación BBVA
  • Dates: 2018-2020
  • Principle investigator: Gabor Lugosi
  • Amount: € 100,000

“Estimación de redes latentes”

  • Reference: MTM2015-67304-P
  • Financing entity: Ministerio de Economía y Competitividad (MINECO)
  • Dates: 2016-2018
  • Principle investigators: Gabor Lugosi, Omiros Papaspiliopoulos
  • Amount: € 52,998