Operations Research

Main research directions


June  2023

Jessica Rodriguez Pereira

is awarded the “Best Operational Research Applied Paper” prize by SEIO (the Spanish Society for Statistics and Operational Research) and the BBVA Foundation. The work, titled “Optimizing access to drinking water in remote areas. Application to Nepal” was co-authored with Gilbert Laporte, Marie-Ève Rancourt, and Selene Silvestri.Analytics.

October 2022

Mohammad Ghaderi

wins the 2022 Multiple Criteria Decision Making Junior Researcher Best Paper award by INFORMS (the U.S. operations research and management science society). The awarded paper was “Incorporating uncovered structural patterns in value functions construction”, co-authored with Miłosz Kadziński.

September 2022

Mohammad Ghaderi

is awarded a 5-year Ramon y Cajal fellowship by the Spanish Government, aimed at “young scientists with a solid research career and international professional experience”.

January 2022

Helena Ramalhinho

wins the second prize for the 2021 Best Paper Award from the journal International Transactions in Operational Research, with the paper “Designing e-commerce supply chains: a stochastic facility–location approach”, co-authored with Adela Pagès-Bernaus, Angel Juan, and Laura Calvet..

September 2021

Alberto Santini

is awarded a Marie Curie Cofund fellowship with the project “Sustainable Integrated Last-mile Delivery”. The fellowship, funded through the Horizon 2020 programme, will allow the researcher to spend two years at ESSEC Business School in France.

O. Papaspiliopoulos and N. Chopia. Springer, 2020

An Introduction to Sequential Monte Carlo

This book provides a general introduction to Sequential Monte Carlo (SMC) methods, also known as particle filters. These methods have become a staple for the sequential analysis of data in such diverse fields as signal processing, epidemiology, machine learning, population ecology, quantitative finance, and robotics.

An Introduction to Sequential Monte Carlo

LP. Bartlett, P.L. Long, G. Lugosi, and A. Tsigler. PNAS, 2020.

Benign overfitting in linear regression

The phenomenon of benign overfitting is one of the key mysteries uncovered by deep learning methodology: deep neural networks seem to predict well, even with a perfect fit to noisy training data. Motivated by this phenomenon, Gábor and his co-authors consider when a perfect fit to training data in linear regression is compatible with accurate prediction. Their analysis shows that overparameterization is essential for benign overfitting in this setting: the number of directions in parameter space that are unimportant for prediction must significantly exceed the sample size. (link to the article)

S. Lauritzen, C. Uhler and P. Zwiernik

Total positivity in exponential families with application to binary variables

Annals of Statistics, to appear

  • Location of a new warehouse for Serveto transportation firm (2019)
  • Mathematical Models and Algorithm to solve Logistics Optimization Problems in SEAT-Volkswagen (2016-2019)
  • Crew Scheduling for Taxi Drivers – Application to Cabify. Funding: Job and Talent (2018)
  • Solving Optimization Problems for e-commerce in INDITEX. Funding: OESIA and INDITEX (2016-2017)
  • On the Improvement of Blood Sample Collection at a Clinical Laboratory, CATLAB (2013)
  • Tecnology Transder Software for Vehicle Route Optimization. Collaborating entities: Universitat de la Laguna and Ingeniería Electronica Canarias S.L. (2012)
  • Locating lottery retail stores in Spain (2009-2012). Funded by Loterías y Apuestas del Estado (LAE).
  • Local Fuel Markets. Funded by Comisión Nacional de Energía.
  • The demand for lottery in Spain: a territorial study. Funded by Loterías y Apuestas del Estado (LAE).
  • Economic impact of FGC tourism activities, Ferrocarrils de la Generalitat de Catalunya.
  • The costs of labor claims in Catalonia. Departament de Treball, Generalitat de Catalunya.
  • Study on the logistics of LAE warehouses. Funded by Sistemas Técnicos de Lotería (STL)
  • The logistics of fire fighting services in Barcelona, funded by Barcelona City Council
  • Economic Evaluation of the network of Access Highways to Buenos Aires, funded by OCRABA (Organo de Control de la Red de Accesos a B.A.)
  • The rescue of motorway concessions in Catalonia, funded by Dept. de Política Territorial I Obres Públiques, Generalitat de Catalunya
  • Barcelona Crane Logistics, funded by Barcelona City Council
  • Budget allocation of the Barcelona Primary Care Centers, funded by Servei Català de Salut
  • The economic impact of infrastructure investments made by the Generalitat de Catalunya, funded by Cable y Televisión de Catalunya
  • “The economic impact of infrastructure investments made by the Generalitat de Catalunya”, funded Generalitat de Catalunya
  • A. Corral, F. Udina and E. Arcaute, Truncated lognormal distributions and scaling in the size of naturally defined population clusters. Physical Review E, 2020, 101, No. 4.

  • 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.

  • 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.

  • 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.

  • 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.

  • 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.

  • Empirical risk minimization for heavy-tailed losses by C. Brownlees, E. Joly and G. Lugosi, Annals of Statistics, 2015, 43(6), 2507-2536.

  • Gavard R, Jones H, Palacio Lozano D, Thomas M, Rossell D, Spencer S, Barrow M (2020). KairosMS: A new solution for the processing of hyphenated ultrahigh resolution mass spectrometry data. Analytical Chemistry, 92.5 3775-86

  • Gavard R, Palacio Lozano D, Guzman A, Rossell D, Spencer S, Barrow M (2019). Rhapso: Automatic stitching of mass segments from Fourier transform ion cyclotron resonance mass spectra. Analytical Chemistry, 91:15130-37

  • M. Greenacre. Variable selection in compositional data analysis using pairwise logratios. Mathematical Geosciences, 2018, 1-34.

  • Marty R, Kaabinejadian S, van de Haar J, Rossell D, Ideker T, Hildebrand W, Engin HB, Font-Burgada J, Carter H. (2017) MHC-I genotype restricts the oncogenic mutational landscape. Cell, 171, 1272-1283

  • Font-Burgada J, Shalapour S, Ramaswamy S, Hsueh B, Rossell D, Umemura A, Taniguchi K, Nakagawa H, Valasek MA, Ye L, Kopp JL, Sander M, Carter H, Deisseroth K, Verma IM, Karin M. (2015) Hybrid Periportal Hepatocytes Regenerate the Injured Liver without Giving Rise to Cancer. Cell, 162(4):766-79.

  • Calon A, Lonardo E, Berenguer A, Espinet E, Hernando-Momblona X, Iglesias M, Sevillano M, Palomo-Ponce S, Tauriello DVF, Byrom D, Cortina C, Morral C, Barceló C, Tosi S, Riera A, Stephan-Otto Attolini C, Rossell D, Sancho E, Batlle E. (2015) Stromal gene expression defines poor prognosis subtypes in colorectal cancer. Nature Genetics, 47, 320-329. doi:10.1038/ng.3225

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

“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: Gábor 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

How we can help

Let us train you to acquire those data science analytics skills that you or your team are missing.

Need some help in any analytics challenge you are facing? Get your analytics to the next level: count on us as expert consultants!

Contact us

We’d love to hear from you… Drop us a line to get in touch!