Prof. Dr. Dirk Wilhelm

Work at ZHAW

Position

Dean School of Engineering

Experience

• External Lecturer
  University of Zurich
  2020 - today
• Dean ZHAW School of Engineering
  ZHAW
  2019 - today
• Professor Medical Physics
  ZHAW
  2016 - today
• Head of Departement for Applied Mathematics, Physics, Systems and Operations
  ZHAW
  2013 - 2018
• Head of R&D Department
  Bruker BiosSpin
  2003 - 2013
• Research Engineer
  Alston
  2001 - 2003
• Postdoc
  UC Santa Barbara
  2000 - 2001

Network

ORCID digital identifier

ORCID ID: 0000-0001-5109-9803

Projects

• Smart Acquisition for Ultra-High field NMR Spectroscopy / Team member / ongoing
• PhD Program in Data Science / Co-project leader / completed
• European Conference Series on Artificial Intelligence in Industry and Finance / Team member / completed
• Machine learning for NMR spectroscopy / Deputy project leader / completed
• SCIS Simulation Based Calibration of Infusion Systems / Team member / completed
• 3rd European COST Conference on Mathematics for Industry in Switzerland / Team member / completed
• PhD Network in Data Science / Project leader / completed
• 2nd European COST Conference on Mathematics for Industry in Switzerland / Team member / completed
• 1st European COST Conference on Mathematics for Industry in Switzerland / Team member / completed
• Development of Ultra-Low-Temperature NMR Probehead for MAS with Computational Fluiddynamic simulations / Project leader / completed

Publications

Articles in scientific journal, peer-reviewed

• Schmid, N. et al. (2026) 'MolDeTr : a chemistry-informed deep learning model for next-generation automated analysis of 1H NMR spectra', Analytical Chemistry, 98(32), pp. 23399–23412. doi: 10.1021/acs.analchem.5c03465.
• 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.
• 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.
• 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.
• 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.

Books, 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.

Written conference contributions, peer-reviewed

• Fischetti, G. et al. (2026) 'Ultrafast automated analysis for NMR fragment screening', in 31st International Conference on Magnetic Resonance in Biological Systems (ICMRBS), Davos, Switzerland, 23-27 August 2026. ZHAW Zurich University of Applied Sciences. doi: 10.21256/zhaw-37487.
• 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.

Other publications

• 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.

Oral conference contributions and 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.

Affiliations

Current Affiliations

Member of Executive Committee
Schweizer Akademie der Technischen Wissenschaften SATW, Zürich
Participating in Executive Committee meetingsAttending SATW eventsSupporting the SATW
05 / 2026 - today

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