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Professorship for Information Systems, in particular Machine Learning

Organisational unit: Professoship

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Main research areas

Research

We are interested in statistical machine learning with a focus on spatiotemporal problems, such as user navigation on the web, adaptive testing and adaptive learning environments, and the coordination of football players on the pitch. While we mainly focus on basic research, we also collaborate with selected partners in academia, sports and industry in different projects.

Teaching

Our teaching focuses on introductory/advanced machine learning and data mining as well as basic statistics. We regularly offer courses in the Management & Data Science Master and the Information Systems Bachelor programs. Exemplary courses comprise Deep Learning (Data Science), Statistics (Information Systems), and Machine Learning & Data Mining (Engineering).

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  1. 2020
  2. Published

    Graph Conditional Variational Models: Too Complex for Multiagent Trajectories?

    Rudolph, Y., Brefeld, U. & Dick, U., 2020, In: Proceedings of Machine Learning Research. 137, p. 136-147 12 p.

    Research output: Journal contributions › Conference article in journal › Research › peer-review

  3. Published

    Machine Learning and Data Mining for Sports Analytics: 7th International Workshop, MLSA 2020, Co-located with ECML/PKDD 2020, Ghent, Belgium, September 14–18, 2020, Proceedings

    Brefeld, U. (Editor), Davis, J. (Editor), van Haaren, J. (Editor) & Zimmermann, A. (Editor), 2020, Cham: Springer International Publishing. 146 p. (Communications in Computer and Information Science; vol. 1324)

    Research output: Books and anthologies › Conference proceedings › Research

  4. Published

    Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2019, Würzburg, Germany, September 16–20, 2019, Proceedings, Part I

    Brefeld, U. (Editor), Fromont, E. (Editor), Hotho, A. (Editor), Knobbe, A. (Editor), Maathuis, M. (Editor) & Robardet, C. (Editor), 2020, Cham: Springer Nature Switzerland AG. 766 p. (Lecture notes in computer science; vol. 11906)(Lecture Notes in Artificial Intelligence; vol. 11906)

    Research output: Books and anthologies › Conference proceedings › Research

  5. Published

    Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2019, Würzburg, Germany, September 16–20, 2019, Proceedings, Part II

    Brefeld, U. (Editor), Fromont, E. (Editor), Hotho, A. (Editor), Knobbe, A. (Editor), Maathuis, M. (Editor) & Robardet, C. (Editor), 2020, Cham: Springer Nature Switzerland AG. 732 p. (Lecture notes in computer science; vol. 11906)(Lecture Notes in Artificial Intelligence; vol. 11906)

    Research output: Books and anthologies › Conference proceedings › Research

  6. Published

    Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2019, Würzburg, Germany, September 16–20, 2019, Proceedings, Part III

    Brefeld, U. (Editor), Fromont, E. (Editor), Hotho, A. (Editor), Knobbe, A. (Editor), Maathuis, M. (Editor) & Robardet, C. (Editor), 2020, Cham: Springer Nature Switzerland AG. 804 p. (Lecture notes in computer science; vol. 11906)(Lecture Notes in Artificial Intelligence; vol. 11906)

    Research output: Books and anthologies › Conference proceedings › Research

  7. 2019
  8. Published

    Zur empirischen Beforschung des mBooks Belgien: Die Chancen eines Methodenmix

    Schreiber, W., Wagner, W., Trautwein, U. & Brefeld, U., 10.2019, Das Geschichtsschulbuch: Lehren – Lernen – Forschen . Kühberger, C., Bernhard, R. & Bramann, C. (eds.). Münster: Waxmann Verlag, p. 57-80 24 p. (Salzburger Beiträge zur Lehrer/innen/bildung; vol. 6).

    Research output: Contributions to collected editions/works › Contributions to collected editions/anthologies › Research › peer-review

  9. Published

    Personalized Transaction Kernels for Recommendation Using MCTS

    Tavakol, M., Joppen, T., Brefeld, U. & Fürnkranz, J., 01.09.2019, KI 2019: Advances in Artificial Intelligence - 42nd German Conference on AI, Proceedings. Benzmüller, C. & Stuckenschmidt, H. (eds.). Wiesbaden: Springer Verlag, p. 338-352 15 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 11793 LNAI).

    Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review

  10. Published

    Predicting the Difficulty of Exercise Items for Dynamic Difficulty Adaptation in Adaptive Language Tutoring

    Pandarova, I., Schmidt, T., Hartig, J., Boubekki, A., Jones, R. D. & Brefeld, U., 15.08.2019, In: International Journal of Artificial Intelligence in Education. 29, 3, p. 342-367 26 p.

    Research output: Journal contributions › Journal articles › Research › peer-review

  11. Published

    Machine Learning and Data Mining for Sports Analytics: 5th International Workshop, MLSA 2018, colocated with ECML/PKDD 2018, Dublin, Ireland, September 10, 2018, Proceedings

    Brefeld, U. (Editor), Davis, J. (Editor), Van Haaren, J. (Editor) & Zimmermann, A. (Editor), 05.04.2019, Springer Nature. 179 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 11330 LNAI)

    Research output: Books and anthologies › Collected editions and anthologies › Research

  12. Published

    Learning to Rate Player Positioning in Soccer

    Dick, U. & Brefeld, U., 01.03.2019, In: Big Data. 7, 1, p. 71-82 12 p.

    Research output: Journal contributions › Journal articles › Research › peer-review

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