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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. 2025
  2. E-pub ahead of print

    Self-improvement for Computerized Adaptive Testing

    Rudolph, Y., Neubauer, K. & Brefeld, U., 2026, Machine Learning and Knowledge Discovery in Databases - Research Track: European Conference, ECML PKDD 2025, Porto, Portugal, September 15–19, 2025, Proceedings. Ribeiro, R. P., Jorge, A. M., Soares, C., Gama, J., Pfahringer, B., Japkowicz, N., Larrañaga, P. & Abreu, P. H. (eds.). Cham: Springer International Publishing, Vol. 2. p. 70-86 17 p. (Lecture Notes in Computer Science; vol. 16014 LNCS).

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

  3. Published

    Muses or Stereotypes? Identifying Historical Patterns of Sexism in a Corpus of Brazilian Lyrics

    Lopes, J. N. D. S., Firmino, V. P. & Dos Reis, V. Q., 05.06.2025, In: Journal on Interactive Systems. 16, 1, p. 369-380 12 p.

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

  4. Published

    The promise and challenges of computer mouse trajectories in DMHIs – A feasibility study on pre-treatment dropout predictions

    Zantvoort, K., Matthiesen, J., Bjurner, P., Bendix, M., Brefeld, U., Funk, B. & Kaldo, V., 06.2025, In: Internet Interventions. 40, 7 p., 100828.

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

  5. Published

    Interactive sequential generative models for team sports

    Fassmeyer, D., Cordes, M. & Brefeld, U., 02.2025, In: Machine Learning. 114, 2, 15 p., 38.

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

  6. Published

    Masked autoencoder for multiagent trajectories

    Rudolph, Y. & Brefeld, U., 02.2025, In: Machine Learning. 114, 2, 18 p., 44.

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

  7. Accepted/In press

    Joint Item Response Models for Manual and Automatic Scores on Open-Ended Test Items

    Bengs, D., Brefeld, U., Kroehne, U. & Zehner, F., 2025, (Accepted/In press) In: Psychometrika.

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

  8. Published

    Machine Learning and Data Mining for Sports Analytics: 11th International Workshop, MLSA 2024, Vilnius, Lithuania, September 9, 2024, Revised Selected Papers

    Brefeld, U. (Editor), Davis, J. (Editor), Van Haaren, J. (Editor) & Zimmermann, A. (Editor), 2025, Cham: Springer Verlag. 119 p. (Communications in Computer and Information Science; vol. 2460)

    Research output: Books and anthologies › Conference proceedings › Research

  9. Published

    Toward Learning Distributions of Distributions

    Wohlstein, M. & Brefeld, U., 2025, In: Proceedings of Machine Learning Research. 265, p. 269-275 7 p.

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

  10. 2024
  11. Submitted

    Studying properties of water data using manifold-aware anomaly detectors

    Paulsen, T. & Brefeld, U., 23.04.2024, (Submitted) Design of Cyber-Secure Water Plants. Mathur, A., Zhou, J. & Raman, G. (eds.). MDPI AG, (Water).

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

  12. Published

    Masked Autoencoder Pretraining for Event Classification in Elite Soccer

    Rudolph, Y. & Brefeld, U., 26.02.2024, Machine Learning and Data Mining for Sports Analytics: 10th International Workshop, MLSA 2023, Revised Selected Papers. Brefeld, U., Davis, J., Van Haaren, J. & Zimmermann, A. (eds.). Cham: Springer Nature Switzerland AG, p. 24-35 12 p. (Communications in Computer and Information Science; vol. 2035).

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

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