To Pump or Not to Pump – Sensor-based Reinforcement Learning for an Optimal Scheduler
Müller AC, Stahlhofen P, Hammer B (2025) .
Paul Stahlhofen
PhD Student
pstahlhofen@techfak.uni-bielefeld.de +49 521 106-12146Room: CITEC 2-111
Paul Stahlhofen studied B.Sc. Cognitive Informatics and M.Sc. Intelligent Systems at Bielefeld University. During his master studies he worked as a scientist for the Environmental Research Center (Umweltforschungszerntrum, short UFZ) in Leipzig, where he was co-maintaining a software package for the processing of chemical mass-spectrometry data. After finishing his master studies in August 2022, he started as a PhD student in the Machine Learning group two months later. His research focusses on adversarial attacks and robustness, in particular for the application domain of water distribution systems.
Publications:
Adversarial Attacks on Leakage Detectors in Water Distribution Networks
Stahlhofen P, Artelt A, Hermes L, Hammer B (2023)
In: Advances in Computational Intelligence. 17th International Work-Conference on Artificial Neural Networks, IWANN 2023, Ponta Delgada, Portugal, June 19–21, 2023, Proceedings, Part II. Rojas I, Joya G, Catala A (Eds); Lecture Notes in Computer Science. Cham: Springer Nature Switzerland: 451-463.