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. 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

  2. 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

  3. Published

    Contextual movement models based on normalizing flows

    Fadel, S., Mair, S., da Silva Torres, R. & Brefeld, U., 03.2023, In: AStA Advances in Statistical Analysis. 107, 1-2, p. 51-72 22 p.

    Research output: Journal contributionsJournal articlesResearchpeer-review

  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

    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

  6. 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/worksChapterpeer-review

  7. Published

    Uma Caracterização das Polı́ticas de Privacidade Utilizadas em Aplicativos no Brasil

    Jardim, G. P. S., Rabello, M. E. R., Lima, A. C., Brefeld, U. & Quadros dos Reis, V., 05.08.2022, Anais do III Workshop sobre as Implicações da Computação na Sociedade (WICS). Sociedade Brasileira de Computação (SBC), p. 13-25 13 p. (WORKSHOP SOBRE AS IMPLICAÇÕES DA COMPUTAÇÃO NA SOCIEDADE (WICS); no. 3/2022).

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

  8. 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

  9. Published

    Modeling Conditional Dependencies in Multiagent Trajectories

    Rudolph, Y. & Brefeld, U., 2022, In: Proceedings of Machine Learning Research. 151, p. 10518-10533 16 p.

    Research output: Journal contributionsConference article in journalResearchpeer-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 contributionsConference article in journalResearchpeer-review