Dr. Volker Ziebart
Dr. Volker Ziebart
ZHAW
School of Engineering
Machine Learning in Optimal Control for Industry
Technikumstrasse 71
8400 Winterthur
Personal profile
Projects
- Risiken aus Radardaten / Team member / Project ongoing
- Ecological and economic process optimization in cement production through machine learning / Project leader / Project ongoing
- Machine learning for NMR spectroscopy / Team member / Project ongoing
- Feasibility Study Reinforcement Learning for Heating Systems / Project leader / Project completed
Publications
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Schmid, N.; Bruderer, S.; Paruzzo, F.; Fischetti, G.; Toscano, G.; Graf, D.; Fey, M.; Henrici, A.; Ziebart, V.; Heitmann, B.; Grabner, H.; Wegner, J.D.; Sigel, R.K.O.; Wilhelm, D.,
2023.
Deconvolution of 1D NMR spectra : a deep learning-based approach.
Journal of Magnetic Resonance.
347(107357).
Available from: https://doi.org/10.1016/j.jmr.2022.107357
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Schmid, Nicolas; Bruderer, Simon; Fischetti, Giulia; Paruzzo, Federico; Toscano, Giuseppe; Graf, Dominik; Fey, Michael; Ziebart, Volker; Henrici, Andreas; Grabner, Helmut; Wegner, Jan Dirk; Sigel, Roland K.O.; Heitmann, Björn; Wilhelm, Dirk,
2023.
Deconvolution of NMR spectra : a deep learning-based approach [poster].
In:
Datalab Symposium, Winterthur, Schweiz, 11. Januar 2023.
ZHAW Zürcher Hochschule für Angewandte Wissenschaften.
Available from: https://doi.org/10.21256/zhaw-27429
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Bolt, Peter; Ziebart, Volker; Jaeger, Christian; Ritzmann, Remo; Meier, Olaf; Füchslin, Rudolf Marcel,
2018.
Model predictive control for building automation [paper].
In:
EuroSun 2018 : conference proceedings.
12th International Conference on Solar Energy and Buildings (EuroSun 2018), Rapperswil, 10-13 September 2018.
International Solar Energy Society.
pp. 1330-1341.
Available from: https://doi.org/10.18086/eurosun2018.11.05
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Bolt, Peter; Künzi, Raffael; Ziebart, Volker; Füchslin, Rudolf Marcel; Motich, Mohammed; Antoni, Mathieu; Finger, Marc-Aurèle; Bürki, Matthias,
2023.
Optimizing cement production by employing physics informed machine learning [poster].
In:
Datalab Symposium, Winterthur, Schweiz, 11. Januar 2023.
ZHAW Zürcher Hochschule für Angewandte Wissenschaften.
Available from: https://doi.org/10.21256/zhaw-26666