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. 2018
  2. European conference an Data Analysis -ECDA 2018

    Gaonkar, R. (Coauthor), Tavakol, M. (Coauthor) & Brefeld, U. (Coauthor)

    04.07.201806.07.2018

    Activity: Participating in or organising an academic or articstic eventConferencesResearch

  3. Educational Data Mining - EDM 2018

    Boubekki, A. (Coauthor), Jain, S. (Coauthor) & Brefeld, U. (Speaker)

    15.07.201817.07.2018

    Activity: Participating in or organising an academic or articstic eventConferencesResearch

  4. Exploiting the Frame for Active Learning in Multi-class Classification

    Mair, S. (Coauthor) & Brefeld, U. (Coauthor)

    15.07.201818.07.2018

    Activity: Talk or presentationConference PresentationsResearch

  5. Concurrent Adaptive Tests for Formative Assessments in School Classes

    Bengs, D. (Speaker), Brefeld, U. (Speaker) & Kröhne, U. (Speaker)

    26.07.2018

    Activity: Talk or presentationConference PresentationsResearch

  6. MDP-based Itinerary Recommendation using Geo-Tagged Social Media

    Gaonkar, R. (Speaker), Tavakol, M. (Speaker) & Brefeld, U. (Speaker)

    24.10.2018

    Activity: Talk or presentationConference PresentationsResearch

  7. 2020
  8. Companion Proceedings of the 10th International Conference on Learning Analytics & Knowledge LAK20

    Neubauer , K. (Participant) & Brefeld, U. (Participant)

    25.03.202027.03.2020

    Activity: Participating in or organising an academic or articstic eventConferencesResearch

  9. Graph Conditional Variational Models: Too Complex for Multiagent Trajectories?

    Rudolph, Y. (Speaker), Brefeld, U. (Coauthor) & Dick, U. (Coauthor)

    12.12.2020

    Activity: Talk or presentationPresentations (poster etc.)Research

  10. 2022
  11. Detection of tactical patterns using semi-supervised graph neural networks

    Anzer, G. (Speaker), Bauer, P. (Speaker), Brefeld, U. (Speaker) & Faßmeyer, D. (Speaker)

    2022

    Activity: Talk or presentationConference PresentationsResearch

  12. Modeling Conditional Dependencies in Multiagent Trajectories

    Rudolph, Y. (Speaker) & Brefeld, U. (Coauthor)

    28.03.2022

    Activity: Talk or presentationPresentations (poster etc.)Research

  13. 2023
  14. Data-efficient Pattern Detection in Elite Soccer

    Rudolph, Y. (Speaker), Faßmeyer, D. (Coauthor) & Brefeld, U. (Coauthor)

    26.05.2023

    Activity: Talk or presentationConference PresentationsResearch

Recently viewed