Prof. Dr. Dirk Wilhelm

Arbeit an der ZHAW

Tätigkeit

• Unterricht im BSc: Numerik für Maschinentechnik und Systemtechnik, Medizintechnik
• Unterricht im MSc: OpenFoam EVA
• F&E: Nuclear Magnetic Resonance (NMR), Computational Fluid Dynamics (CFD), Numerik
• Direktor School of Engineering

Berufserfahrung

• Externer Dozent
  Universität Zürich
  2020 - heute
• Direktor ZHAW School of Engineering
  ZHAW
  2019 - heute
• Professor Medizinphysik
  ZHAW
  2016 - heute
• Leiter Abteilung für Angewandte Mathematik, Physik, Systems and Operations
  ZHAW
  2013 - 2018
• Abteilungsleiter F&E
  Bruker BioSpin
  2003 - 2013
• Entwicklungsingenieur
  Alstom
  2001 - 2003
• Postdoc
  UC Santa Barbara
  2000 - 2001

Netzwerk

Mitglied in Netzwerken

• COST Mathematics for Industry Network
• Innovationspanel der DIZH (Digitalisierungsinitiative des Kanton Zürich)
• Winlink (Präsident)
• Swiss Engineering STV
• VDI
• FTAL (Präsident)
• DPG
• ASME

ORCID digital identifier

ORCID ID: 0000-0001-5109-9803

Projekte

• Smart Acquisition for Ultra-High field NMR Spectroscopy / Teammitglied / laufend
• NMR-based drug discovery / Teammitglied / laufend
• PhD Program in Data Science / Co-Projektleiter:in / abgeschlossen
• Europäische Konferenzserie zu Künstlicher Intelligenz (KI) in Industrie und Finanzwesen / Teammitglied / abgeschlossen
• Maschinelles Lernen für NMR-Spektroskopie / Stellv. Projektleiter:in / abgeschlossen
• SCIS Simulation Based Calibration of Infusion Systems / Teammitglied / abgeschlossen
• 3rd European COST Conference on Mathematics for Industry in Switzerland / Teammitglied / abgeschlossen
• PhD Network in Data Science / Projektleiter:in / abgeschlossen
• 2nd European COST Conference on Mathematics for Industry in Switzerland / Teammitglied / abgeschlossen
• 1st European COST Conference on Mathematics for Industry in Switzerland / Teammitglied / abgeschlossen
• Entwicklung eines Ultra-Low-Temperature NMR Probenkopfes für hochgeschwindigkeits Magic-Angle-Spinning Anwendungen mit Hilfe von Computational Fluid Dynamics (CFD) Simulationen / Projektleiter:in / abgeschlossen

Publikationen

Beiträge in wissenschaftlicher Zeitschrift, peer-reviewed

• Fischetti, G. et al. (2025) 'A deep learning framework for multiplet splitting classification in 1H NMR', Journal of Magnetic Resonance, 373(107851). doi: 10.1016/j.jmr.2025.107851.
• Hostettler, M. et al. (2023) 'Modelling of peristaltic pumps with respect to viscoelastic tube material properties and fatigue effects', Fluids, 8(9), pp. 254–269. doi: 10.3390/fluids8090254.
• Schmid, N. et al. (2023) 'Deconvolution of 1D NMR spectra : a deep learning-based approach', Journal of Magnetic Resonance, 347(107357). doi: 10.1016/j.jmr.2022.107357.
• Fischetti, G. et al. (2023) 'Automatic classification of signal regions in 1H nuclear magnetic resonance spectra', Frontiers in Artificial Intelligence, 5(1116416). doi: 10.3389/frai.2022.1116416.
• Herzog, N. et al. (2022) 'Ultra low temperature microturbine for magic angle spinning system', Journal of Fluids Engineering, 144(8), pp. 081205–1–081205–12. doi: 10.1115/1.4053746.
• Cousin, S. et al. (2016) 'High-resolution two-field nuclear magnetic resonance spectroscopy', Physical Chemistry Chemical Physics, 18(48), pp. 33187–33194. doi: 10.1039/C6CP05422F.
• Herzog, N. et al. (2016) 'Aerodynamic optimization of a microturbine inserted in a magic-angle spinning system', Journal of Fluids Engineering, 138(12), p. 121106.
• Wilhelm, D., Purea, A. and Engelke, F. (2015) 'Fluid flow dynamics in MAS systems', Journal of Magnetic Resonance, 257, pp. 51–63. doi: 10.1016/j.jmr.2015.05.006.
• Meiburg, E. et al. (2004) 'Density-driven instabilities of variable-viscosity miscible fluids in a capillary tube', Annals of the New York Academy of Sciences, pp. 383–402. doi: 10.1196/annals.1324.032.
• Wilhelm, D. and Meiburg, E. (2004) 'Three-dimensional spectral element simulations of variable density and viscosity, miscible displacements in a capillary tube', Computers & Fluids, 33(3), pp. 485–508. doi: 10.1016/S0045-7930(03)00059-8.
• Vanaparthy, S. H., Meiburg, E. and Wilhelm, D. (2003) 'Density-driven instabilities of miscible fluids in a capillary tube : linear stability analysis', Journal of Fluid Mechanics, 497, pp. 99–121. doi: 10.1017/S0022112003006499.
• Wilhelm, D., Härtel, C. and Kleiser, L. (2003) 'Computational analysis of the two-dimensional–three-dimensional transition in forward-facing step flow', Journal of Fluid Mechanics, 489, pp. 1–27. doi: 10.1017/S0022112003004440.
• Jenny, B., Wilhelm, D. and Valero-Garcés, B. L. (2003) 'The southern westerlies in central chile : holocene precipitation estimates based on a water balance model for Laguna Aculeo (33°50′S)', Climate Dynamics, 20(2-3), pp. 269–280. doi: 10.1007/s00382-002-0267-3.
• Wilhelm, D. and Kleiser, L. (2002) 'Application of a spectral element method to two-dimensional forward-facing step flow', Journal of Scientific Computing, 17(1-4), pp. 619–627. doi: 10.1023/A:1015178831786.
• Kleiser, L. and Wilhelm, D. (2001) 'Stability analysis for different formulations of the nonlinear term in PN−PN−2 spectral element discretizations of the navier–stokes equations', Journal of Computational Physics, 174(1), pp. 306–326. doi: 10.1006/jcph.2001.6912.
• Wilhelm, D. and Kleiser, L. (2000) 'Stable and unstable formulations of the convection operator in spectral element simulations', Applied Numerical Mathematics, 33(1-4), pp. 275–280. doi: 10.1016/S0168-9274(99)00093-8.
• Wilhelm, D., Härtel, C. and Eckelmann, H. (1998) 'On the relation between fronts and high-shear layers in wall turbulence', Flow, Turbulence and Combustion, 60(1), pp. 87–103. doi: 10.1023/A:1009952224076.

Bücher, peer-reviewed

Wilhelm, D. (2000) Numerical investigation of three-dimensional separation in a forward-facing step flow using a spectral element method. Doctoral dissertation. ETH Zürich. doi: 10.3929/ethz-a-004037003.

Schriftliche Konferenzbeiträge, peer-reviewed

• Fischetti, G. et al. (2025) 'Fully automated analysis of photo-CIDNP NMR spectra for fast fragment screening', in 21st European Magnetic Resonance Congress (EUROMAR), Oulu, Finnland, 6-10 July 2025. ZHAW Zurich University of Applied Sciences. doi: 10.21256/zhaw-33657.
• Schmid, N. et al. (2025) 'MolDETR : next-generation analysis of molecular spectra with deep learning', in 21st European Magnetic Resonance Congress (EUROMAR), Oulu, Finnland, 6-10 July 2025. Oulu: EUROMAR. doi: 10.21256/zhaw-33659.
• Schmid, N. et al. (2024) 'Automated spin system analysis in NMR spectroscopy with SpinDETR : a deep learning approach', in Datalab-Symposium, Winterthur, Schweiz, 12. September 2024. Winterthur: ZHAW Zurich University of Applied Sciences. doi: 10.21256/zhaw-31443.
• Fischetti, G. et al. (2024) 'MuSe Net : a deep learning framework for trustworthy multiplet segmentation in 1D 1H NMR spectra', in Datalab-Symposium, Winterthur, Schweiz, 12. September 2024. Winterthur: ZHAW Zurich University of Applied Sciences. doi: 10.21256/zhaw-31444.
• Fischetti, G. et al. (2024) 'MuSe Net : a deep learning framework for trustworthy multiplet segmentation in 1D 1H NMR spectra', in 20th European Magnetic Resonance Congress (EUROMAR), Bilbao, Spain, 30 June - 4 July 2024. ZHAW Zürcher Hochschule für Angewandte Wissenschaften. doi: 10.21256/zhaw-31102.
• Schmid, N. et al. (2024) 'Automated spin system analysis in NMR spectroscopy with SpinDETR : a deep learning approach', in 20th European Magnetic Resonance Congress (EUROMAR), Bilbao, Spain, 30 June - 4 July 2024. ZHAW Zürcher Hochschule für Angewandte Wissenschaften. doi: 10.21256/zhaw-31101.
• Schmid, N. et al. (2023) 'Transforming NMR spectroscopy : extraction of multiplet parameters with deep learning', in Prisner, T. (ed.) Euromar 2022 Abstractbook. ZHAW Zürcher Hochschule für Angewandte Wissenschaften, p. 291. doi: 10.21256/zhaw-29510.
• Fischetti, G. et al. (2023) 'Uncertainty quantification for reliable automatic multiplet classification in 1H NMR spectra', in Prisner, T. (ed.) Euromar 2023 Programme & Abstract Book. ZHAW Zürcher Hochschule für Angewandte Wissenschaften, p. 350. doi: 10.21256/zhaw-29538.
• Schmid, N. et al. (2023) 'Deconvolution of NMR spectra : a deep learning-based approach', in Datalab Symposium, Winterthur, Schweiz, 11. Januar 2023. ZHAW Zürcher Hochschule für Angewandte Wissenschaften. doi: 10.21256/zhaw-27429.
• Fischetti, G. et al. (2022) 'A deep ensemble learning method for automatic classification of multiplets in 1D NMR spectra', in Prisner, T. (ed.) EUROMAR 2022 Abstractbook. ZHAW Zürcher Hochschule für Angewandte Wissenschaften, p. 236. doi: 10.21256/zhaw-27328.
• Schmid, N. et al. (2022) 'Deconvolution of NMR spectra : a deep learning-based approach', in Prisner, T. (ed.) EUROMAR 2022 Abstractbook. ZHAW Zürcher Hochschule für Angewandte Wissenschaften, p. 242. doi: 10.21256/zhaw-27336.

Weitere Publikationen

• Henrici, A. et al. (eds) (2023) Artificial Intelligence in Finance and Industry : Volume II - Highlights from the 7th European Conference, 7th European COST Conference on Artificial Intelligence in Industry and Finance, Winterthur, Switzerland, 28 September 2022. Frontiers Research Foundation. Available at: https://www.frontiersin.org/research-topics/38909/.
• Deflorin, P. et al. (eds) (2022) Artificial Intelligence in Finance and Industry : highlights from 6 European COST conferences, 5th European COST Conference on Artificial Intelligence in Industry and Finance, Winterthur, Switzerland (online), 3 September 2020. Frontiers Research Foundation. Available at: https://www.frontiersin.org/research-topics/18514/.
• Dep, R. et al. (2019) 'Stability analysis of gas bearing in Magic Angle Spinning (MAS) systems', in 3rd Gas Bearing Workshop, Düsseldorf, Germany, 25 March 2019. VDE/VDI-Gesellschaft Mikroelektronik Mikrosystem- und Feinwerktechnik.
• Wilhelm, D. (2015) 'Fluid flow dynamics in a Nuclear Magnetic Resonance system', Atlas of Science. Available at: http://atlasofscience.org/fluid-flow-dynamics/.
• Wilhelm, D. (2015) 'Rotating flow simulations with OpenFOAM', International Journal of Aeronautical Science & Aerospace Research, S1:001. doi: 10.21256/zhaw-1441.

Mündliche Konferenzbeiträge und Abstracts

Hostettler, M. et al. (2022) 'Modelling of peristaltic pumps for viscoelastic tube material properties under consideration of fatigue effects', in Multiphysics 2022. International Society of Multiphysics, p. 33. Available at: https://static1.squarespace.com/static/5c9f89c101232c1d41297d67/t/639912525a90a93394aa8b71/1670976084271/MULTIPHYSICS+2022-Abstract+Booklet.pdf.

Interessenbindungen

Aktuelle Interessenbindungen

Schweizer Akademie der Technischen Wissenschaften SATW: Vorstandsmitglied
Mitarbeit im Vorstand der SATWTeilnahme an VorstandssitzungenTeilnahme an SATW Veranstaltungen Unterstützung der SATW, Zürich
05 / 2026 - heute

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