Bio

I am Assistant Professor at the Department of Cognitive Science and Artificial Intelligence at Tilburg University. I obtained my Ph.D. in Computer Science at the University of Antwerp, where I subsequently worked as post-doc. My research interests cover a wide range of topics within Data Mining, Machine Learning and Artificial Intelligence, with a particular focus on sequential or temporal data. My publications can be found on my Google Scholar profile.

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Recent publications

  1. Unveiling the Power of ARIMA, Support Vector and Random Forest Regres…

    Gajewski, P., Čule, B., & Ranković, N. (2023). Unveiling the Power of ARIMA, Support Vector and Random Forest Regressors for the Future of the Dutch Employment Market. Journal of theoretical and applied electronic commerce research, 18(3), 1365-1403.
  2. PETSC: pattern-based embedding for time series classification

    Feremans, L., Čule, B., & Goethals, B. (2022). PETSC: pattern-based embedding for time series classification. Data Mining and Knowledge Discovery, 36(3), 1015-1061.
  3. Face in the Game - Using Facial Action Units to Track Expertise in Co…

    Guglielmo, G., Mavromoustakos Blom, P., Klincewicz, M., Čule, B., & Spronck, P. (2022). Face in the Game: Using Facial Action Units to Track Expertise in Competitive Video Game Play. In 2022 IEEE Conference On Games (CoG) (pp. 112-118). IEEE.
  4. RASCL: a randomised approach to subspace clusters

    Moens, S., Čule, B., & Goethals, B. (2022). RASCL: a randomised approach to subspace clusters. International Journal of Data Science and Analytics, 14(3), 243-259.
  5. Forecasting Electric Vehicle Supply Equipment Availability

    Rotman, S., & Čule, B. (2022). Forecasting Electric Vehicle Supply Equipment Availability. In BNAIC/BeNeLearn 2022 (pp. 1-17)

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