PhD Student
fstoerck@techfak.uni-bielefeld.deRoom: CITEC 2-217
Felix Störck received his Bachelor’s degree in Digital Technologies (2022) at Bielefeld University of Applied Sciences and Arts which was part of a dual study cooperation with Beckhoff Automation GmbH & Co. KG. After a short stint in industry, he joined Bielefeld University for the completion of a Master’s degree in Intelligent Systems (2025). He is now a Ph.D. student in the machine learning group at the Center for Cognitive Interaction Technology. His research interests lie in learning with non-stationary environments, kernel methods and other theoretical as well as applied aspects of machine learning.
Extending Fair Null-Space Projections for Continuous Attributes to Kernel Methods
Störck F, Hinder F, Hammer B (2026)
In: Proceedings of the 43rd International Conference on Machine Learning. Zhang T, Dudik M, Jaggi M, Agarwal A, Li S, Schuurmans D, Zhu J, Berkenkamp F, Dong H, Bietti A (Eds); Proceedings of Machine Learning Research, 306. PMLR: 115812-115825.
FairGLVQ: Fairness in Partition-Based Classification
Störck F, Hinder F, Brinkrolf J, Paaßen B, Vaquet V, Hammer B (2024)
In: Advances in Self-Organizing Maps, Learning Vector Quantization, Interpretable Machine Learning, and Beyond. Proceedings of the 15th International Workshop, WSOM+ 2024, Mittweida, Germany, July 10–12, 2024. Villmann T, Kaden M, Geweniger T, Schleif F-M (Eds); Lecture Notes in Networks and Systems. Cham: Springer Nature Switzerland: 141-151.