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).
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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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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 AG. 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
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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 AG. 146 p. (Communications in Computer and Information Science; vol. 1324)Research output: Books and anthologies › Conference proceedings › Research
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Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2018, Dublin, Ireland, September 10-14, 2018, Proceedings - Part III
Brefeld, U. (Editor), Curry , E. (Editor), Daly, E. (Editor), MacNamee, B. (Editor), Marascu, A. (Editor), Pinelli , F. (Editor), Berlingerio, M. (Editor) & Hurley, N. (Editor), 2019, Cham: Springer. 706 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 11054 LNAI)Research output: Books and anthologies › Collected editions and anthologies › Research
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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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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
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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
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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
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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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MDP-based itinerary recommendation using geo-tagged social media
Gaonkar, R., Tavakol, M. & Brefeld, U., 25.10.2018, Advances in Intelligent Data Analysis XVII - 17th International Symposium, IDA 2018, Proceedings. Duivesteijn, W., Siebes, A. & Ukkonen, A. (eds.). Basel: Springer Nature AG, p. 111-123 13 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); no. 11191).Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review