Janine Strotherm

PhD Student

jstrotherm@techfak.uni-bielefeld.de +49 521 106-12125

Room: CITEC 2-112

Before joining the Machine Learning Group at the Center for Cognitive Interaction Technology in 2022, Janine received her Bachelor’s degree in Mathematics and Physics and her Master’s degree in Mathematics from Bielefeld University. Since then she is working as a PhD student within the project ‘Water Futures’ founded by the European Research Council (ERC). Her research focuses on fair Machine Learning, especially when applied to Water Distribution Networks.

Publications:

Challenges, Methods, Data–A Survey of Machine Learning in Water Distribution Networks

Vaquet V, Hinder F, Artelt A, Ashraf I, Strotherm J, Vaquet J, Brinkrolf J, Hammer B (2024)
In: Artificial Neural Networks and Machine Learning – ICANN 2024. 33rd International Conference on Artificial Neural Networks, Lugano, Switzerland, September 17–20, 2024, Proceedings, Part IX. Wand M, Malinovská K, Schmidhuber J, Tetko IV (Eds); Lecture Notes in Computer Science. Cham: Springer Nature Switzerland: 155-170.

Fairness-enhancing classification methods for non-binary sensitive features—How to fairly detect leakages in water distribution systems

Strotherm J, Ashraf MI, Hammer B (2024)
PeerJ Computer Science 10: e2317.

Fairness in KI-Systemen

Strotherm J, Müller A, Hammer B, Paaßen B (2024)
In: Vertrauen in Künstliche Intelligenz. Eine multi-perspektivische Betrachtung. Schork S (Ed); Wiesbaden: Springer Fachmedien Wiesbaden: 163-183.

Physics-Informed Graph Neural Networks for Water Distribution Systems

Ashraf MI, Strotherm J, Hermes L, Hammer B (2024)
In: THIRTY-EIGHTH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE, VOL 38 NO 20. Palo alto: Assoc Advancement Artificial Intelligence.

Fairness-Enhancing Ensemble Classification in Water Distribution Networks

Strotherm J, Hammer B (2023)
Presented at the International Work-Conference on Artificial Neural Networks (IWANN) 2023, Ponta Delgada.