Professorship for Information Systems, in particular Machine Learning

Organisational unit: Professoship

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).

  1. 2022
  2. Published

    Semi-Supervised Generative Models for Multi-Agent Trajectories

    Brefeld, U., Fassmeyer, D. & Fassmeyer, P., 2022, Advances in Neural Information Processing Systems 35: 36th Conference on Neural Information Processing Systems (NeurIPS 2022). Koyejo, S., Mohamed, S., Agarwal, A., Belgrave, D., Cho, K. & Oh, A. (eds.). Red Hook: Curran Associates, Vol. 48. p. 37267-37281 15 p. (Advances in Neural Information Processing Systems; vol. 35).

    Research output: Contributions to collected editions/worksArticle in conference proceedingsResearchpeer-review

  3. 2021
  4. Published

    The origins of goals in the German Bundesliga

    Anzer, G., Bauer, P. & Brefeld, U., 17.11.2021, In: Journal of Sports Sciences. 39, 22, p. 2525-2544 20 p.

    Research output: Journal contributionsJournal articlesResearchpeer-review

  5. Published

    Toward Automatically Labeling Situations in Soccer

    Fassmeyer, D., Anzer, G., Bauer, P. & Brefeld, U., 03.11.2021, In: Frontiers in Sports and Active Living. 3, 15 p., 725431.

    Research output: Journal contributionsJournal articlesResearchpeer-review

  6. Published

    Principled Interpolation in Normalizing Flows

    Fadel, S., Mair, S., da Silva Torres, R. & Brefeld, U., 09.2021, Machine Learning and Knowledge Discovery in Databases. Research Track: European Conference, ECML PKDD 2021, Bilbao, Spain, September 13–17, 2021, Proceedings, Part II. Oliver, N., Pérez-Cruz, F., Kramer, S., Read, J. & Lozano, J. A. (eds.). Cham: Springer Nature AG, p. 116-131 16 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 12976 LNAI).

    Research output: Contributions to collected editions/worksArticle in conference proceedingsResearchpeer-review

  7. Published

    Space and Control in Soccer

    Martens, F., Dick, U. & Brefeld, U., 16.07.2021, In: Frontiers in Sports and Active Living . 3, 13 p., 676179.

    Research output: Journal contributionsJournal articlesResearch

  8. Published

    Rating Player Actions in Soccer

    Dick, U., Tavakol, M. & Brefeld, U., 15.07.2021, In: Frontiers in Sports and Active Living. 3, 14 p., 682986.

    Research output: Journal contributionsJournal articlesResearchpeer-review

  9. Published

    Joint optimization of an autoencoder for clustering and embedding

    Boubekki, A., Kampffmeyer, M., Brefeld, U. & Jenssen, R., 01.07.2021, In: Machine Learning. 110, 7, p. 1901-1937 37 p.

    Research output: Journal contributionsJournal articlesResearchpeer-review

  10. Published

    Simultaneous Constrained Adaptive Item Selection for Group-Based Testing

    Bengs, D., Kroehne, U. & Brefeld, U., 01.06.2021, In: Journal of Educational Measurement. 58, 2, p. 236-261 26 p.

    Research output: Journal contributionsJournal articlesResearchpeer-review

  11. 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 contributionsJournal articlesResearchpeer-review

  12. 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/worksArticle in conference proceedingsResearchpeer-review