Katharina Prasse

Researcher & PhD Candidate

University of Mannheim
Data and Web Science Group
School of Business Informatics and Mathematics
B6, 26, Room B 003
D-68159 Mannheim

Email: katharina.prassemail-uni-mannheim.de

About

I'm a Ph.D. candidate in the Machine Learning group supervised by Prof. Margret Keuper. My research interests are computer vision in climate change related applications and XAI. My research is funded by the state of Baden-Würrtemberg.

Project

ClimateVisions (16DKWN027b): 01/2023–11/2025

Working with an inter-disciplinary project group, we investigate how climate change is discussed on social media.

More information can be found on our project website.

Education

2024-present, Ph.D. student, Computer Science, University of Mannheim
2023–2024, Ph.D. student, Computer Science, University of Siegen
2020–2022, M.Sc., Mannheim Master in Data Science, University of Mannheim
2014–2017, B.A., Liberal Arts & Sciences, Utrecht University's Honors College (Roosevelt University College)

Publications

Prasse, K., Bravo, I., Walter, S. & Keuper, M. (2025). I spy with my little eye a minimum cost multicut investigation of dataset frames. In Proceedings of the Winter Conference on Applications of Computer Vision (WACV) (S. 2134–2143). , Computer Vision Foundation: Online. https://doi.org/10.1109/WACV61041.2025.00214
Prasse, K., Knab, P., Marton, S., Bartelt, C. & Keuper, M. (2025). DCBM: data-efficient visual concept bottleneck models. In N. Lawrence (eds.), Proceedings of the 42nd International Conference on Machine Learning, PMLR (S. 1–31). Proceedings of Machine Learning Research : PMLR, Curran Associates, Inc.: Red Hook, NY.
Prasse, K., Jung, S., Zhou, Y. & Keuper, M. (2024). Local spherical harmonics improve skeleton-based hand action recognition. In U. Köthe & C. Rother (eds.), Pattern recognition : 45th DAGM German Conference, DAGM GCPR 2023, Heidelberg, Germany, September 19–22, 2023 ; proceedings (S. 67–82). Lecture Notes in Computer Science, Springer: Berlin [u. a.]. https://doi.org/10.1007/978-3-031-54605-1_5
Prasse, K., Jung, S., Bravo, I., Walter, S. & Keuper, M. (2023). Towards understanding climate change perceptions : a social media dataset. In R. Bhalerao, M. Roth, K. Jeggle, J. Montalvo Arvizu, S. Madadkhani & Y. bengio (eds.), NeurIPS 2023 Workshop on Tackling Climate Change with Machine Learning: Blending New and Existing Knowledge Systems : workshop (S. 1–20). , : .

[BibTex]

Teaching

Team Project: ClimateWeb – Analysis of Social Media Network
Team Project: Computer Vision for Social Media Analysis
Bachelor/Master Thesis Co-Supervision
Seminar supervisor (AI Safety & Robustness, Causality & Neurosymbolic Learning)