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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. 2021
  2. Published

    Evaluating one-shot tournament predictions

    Ekstrom, C. T., Van Eetvelde, H., Ley, C. & Brefeld, U., 05.04.2021, In: Journal of Sports Analytics. 7, 1, p. 37-46 10 p.

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

  3. Published

    Evaluation of mechanical property predictions of refill Friction Stir Spot Welding joints via machine learning regression analyses on DoE data

    Bock, F. E., Paulsen, T., Brkovic, N., Rieckmann, L., Kroeger, D., Wolgast, D., Zander, P., Suhuddin, U. F. H., dos Santos, J. F. & Klusemann, B., 02.04.2021, ESAFORM 2021: 24th International Conference on Material Forming. Liège: ULiège Library, 11 p. 2589. (ESAFORM 2021 - 24th International Conference on Material Forming).

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

  4. 2020
  5. Published

    Analysing Positional Data

    Brefeld, U., Mair, S. & Lasek, J., 01.10.2020, Science Meets Sports: When Statistics Are More Than Numbers. Ley, C. & Dominicy, Y. (eds.). Newcastle upon Tyne: Cambridge Scholars Publishing, p. 81-94 13 p. (Physical Sciences).

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

  6. Published

    Sensor Measures of Affective Leaning

    Martens, T., Niemann, M. & Dick, U., 30.04.2020, In: Frontiers in Psychology. 11, 10 p., 379.

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

  7. Published

    HyperUCB: Hyperparameter optimization using contextual bandits

    Tavakol, M., Mair, S. & Morik, K., 28.03.2020, Machine Learning and Knowledge Discovery in Databases: International Workshops of ECML PKDD 2019, Würzburg, Germany, September 16–20, 2019, Proceedings, Part I. Cellier, P. & Driessens, K. (eds.). Cham: Springer Nature, Vol. 1. p. 44-50 7 p. ( Communications in Computer and Information Science; vol. 1167).

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

  8. Published

    Assessing User Behavior by Mouse Movements

    Matthiesen, J. J. & Brefeld, U., 2020, HCI International 2020 - Posters - : 22nd International Conference, HCII 2020, Proceedings. Stephanidis, C. & Antona, M. (eds.). Cham: Springer Verlag, p. 68-75 8 p. (Communications in Computer and Information Science; vol. 1224 CCIS).

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

  9. Published

    Coresets for Archetypal Analysis

    Mair, S. & Brefeld, U., 2020, 32rd Conference on Neural Information Processing Systems (NeurIPS 2019): Vancouver, Canada, 8-14 December 2019. Wallach, H. & Larochelle, H. (eds.). Red Hook: Curran Associates, Vol. 10. p. 7215-7223 9 p. (Advances in neural information processing systems; vol. 32).

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

  10. 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

  11. 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

  12. 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

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