Research

My main research interests are different techniques of analysing and inferring from data: statistical, data mining and machine learning methods, and their applications. My current research focuses particularly on:

  • Sport analytics (especially for association football)
  • Ranking algorithms
  • Preference modelling
  • Evaluation methods for information resources: bibliometrics, scientometrics, informetrics.

Publications:
Lasek J., Gagolewski M.: The Efficacy of League Formats in Ranking Teams, Statistical Modelling, 2018.
Brefeld U., Lasek J., Mair S.: Probabilistic movement models and zones of control, Machine Learning, 2018.
Lasek J.: Euro 2016 Predictions Using Team Rating Systems, Proc. Machine Learning and Data Mining for Sports Analytics (at ECML/PKDD), 2016.
Bogucki R., Milczek J., Lasek J., Tadeusiak M.: Early Warning System for Seismic Events in Coal Mines Using Machine Learning, Proc. FedCSIS, 2016.
Lasek J., Szlavik Z., Gagolewski M., Bhulai S.: How to Improve a Team’s Position in the FIFA Ranking – A Simulation Study, Journal of Applied Statistics, Vol. 43, Is. 7, pp. 1349–1368, 2016.
Lasek J., Gagolewski M., The Winning Solution to the AAIA’15 Data Mining Competition: Tagging Firefighter Activities at a Fire Scene, Proc. FedCSIS, 2015.
Lasek J., Gagolewski M.: Predictive Efficacy of a New Association Football League Format in Polish Ekstraklasa, Proc. Machine Learning and Data Mining for Sports Analytics (at ECML/PKDD), 2015.
Gagolewski M., Lasek J.: Learning Experts’ Preferences from Informetric Data, in: Proc. IFSA-EUSFLAT, 2015.
Lasek M., Lasek J.: Are Stock Markets Driven More by Sentiments than Efficiency? Accepted for publication at Journal of Engineering, Project, and Production Management, 2015.
Gagolewski M., Lasek J.: The Use of Fuzzy Relations in the Assessment of Information Resources Producers’ Performance, in: Filev D. et al. (Eds.), Proc. 7th IEEE International Conference Intelligent Systems IS’2014, Springer, 2015.
Lasek J., Szlávik Z., Bhulai S.: The Predictive Power of Ranking Systems in Association Football, International Journal of Applied Pattern Recognition, Vol. 1, Is. 1, pp. 27–43, 2013.

Selected presentations:
Euro 2016 Predictions Using Team Rating Systems, Machine Learning and Data Mining for Sports Analytics, ECML/PKDD 2016 workshop, Riva Del Garda, September 2016.
The Winning Solution to AAIA’15 Data Mining Competition: Tagging Firefighters Activities at a Fire Scene, FedCSIS, Łódź (Poland), September 2015.
Predictive Efficacy of a New Association Football League Format in Polish Ekstraklasa, Machine Learning and Data Mining for Sports Analytics, ECML/PKDD 2015 workshop, Porto, September 2015.
Learning Experts’ Preferences from Informetric Data, joint conference IFSA/EUSFLAT, Gijon, July 2015.
TThe Use of Fuzzy Relations in the Assessment of Information Resources Producers’ Performance, 7th IEEE International Conference Intelligent Systems IS’2014, Warsaw (Poland), September 2014.
Methods for Improving a Team’s Position in the FIFA Ranking, IPIPAN PhD Summer School, June 2014.
European Parliament Elections on Twitter, Institute of Computer Science, Polish Academy of Sciences, June 2014.
On Football Team Rankings, Workshop on Mining Football–related Data, VU University Amsterdam, June 2012.

Miscellaneous:
Retrieving table of contents from scholarly publications, ADA Lab blog post summarising my internship (summer 2014) at Interdisciplinary Centre for Mathematical and Computational Modelling (University of Warsaw).
AAIA’15 Data Mining Competition: Tagging Firefighter Activities at a Fire Scene, source code for my (winning) solution to the data mining contest, where the task was to reconize what actions are performed by firemen at an emergency scene.