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).
- PublishedDiscriminação Algorítmica de Gênero: Estudo de Caso e Análise no Contexto BrasileiroTaso, F. T. D. S., Quadros dos Reis, V. & Martinez, F. H. V., 06.08.2023, Anais do IV Workshop sobre as Implicações da Computação na Sociedade . Porto Alegre: Sociedade Brasileira de Computação (SBC), p. 13-25 13 p. (Anais do Workshop sobre as Implicações da Computação na Sociedade.; no. 4).Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review 
- PublishedData practices in apps from Brazil: What do privacy policies inform us about?Quadros dos Reis, V., Rabello, M. E. R., Lima, A. C., Jardim, G. P. S., Fernandes, E. R. & Brefeld, U., 10.02.2023, In: Journal on Interactive Systems. 14, 1, p. 1-8 8 p.Research output: Journal contributions › Journal articles › Research › peer-review 
- PublishedData-driven analyses of electronic text booksBoubekki, A., Kröhne, U., Goldhammer, F., Schreiber, W. & Brefeld, U., 2016, Solving large scale learning tasks: Challenges and algorithms : essays dedicated to Katharina Morik on the occasion of her 60th birthday. Michaelis, S., Piatkowski, N. & Stolpe, M. (eds.). Cham: Springer International Publishing, p. 362-376 15 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 9580).Research output: Contributions to collected editions/works › Contributions to collected editions/anthologies › Research 
- PublishedCoresets for Archetypal AnalysisMair, 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 
- PublishedConvolutional Neural NetworksRudolph, Y. & Brefeld, U., 01.01.2023, Sportinformatik: Modellbildung, Simulation, Datenanalyse und Visualisierung von sportbezogenen Daten. Memmert, D. (ed.). Berlin: Springer Spektrum, p. 207-215 9 p.Research output: Contributions to collected editions/works › Chapter 
- PublishedContextual movement models based on normalizing flowsFadel, 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 contributions › Journal articles › Research › peer-review 
- PublishedConstrained Independence for Detecting Interesting PatternsDelacroix, T., Boubekki, A., Lenca, P. & Lallich, S., 02.12.2015, 2015 IEEE International Conference on Data Science and Advanced Analytics (DSAA). Pasi, G., Kwok, J., Zaiane, O., Gallinari, P., Gaussier, E. & Cao, L. (eds.). IEEE - Institute of Electrical and Electronics Engineers Inc., 10 p. 7344897. (Proceedings of the 2015 IEEE International Conference on Data Science and Advanced Analytics, DSAA 2015).Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review 
- PublishedA Unified Contextual Bandit Framework for Long- and Short-Term RecommendationsTavakol, M. & Brefeld, U., 30.12.2017, Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2017 Skopje, Macedonia, September 18 – 22, 2017; Proceedings, Part II. Ceci, M., Hollmen, J., Todorovski, L., Vens, C. & Dzeroski, S. (eds.). Springer Verlag, Vol. 2. p. 269-284 16 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 10535 LNAI).Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review 
- PublishedAssessing User Behavior by Mouse MovementsMatthiesen, 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 
- PublishedAnalysing Positional DataBrefeld, 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 
