Frank-Peter Schilling

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Zurich University of Applied Sciences (ZHAW)

Centre for AI (CAI)

Office TN 03.64

Technikumstrasse 71

CH-8401 Winterthur

I am a senior lecturer and group leader at Zuerich University of Applied Sciences ZHAW, located in Winterthur, Switzerland. I am deputy director of ZHAW’s Centre for Artificial Intelligence CAI, and lead its Intelligent Vision Systems (IVS) research group. I am the scientific coordinator of the PhD programme in Data Science, a collaboration between ZHAW and University of Zurich. I am also adjunct professor for data science and AI at Victoria University of Wellington (NZ), and a IEEE CertifAIed Lead Assessor.

My research focus is on AI and generative Deep Learning methods for image analysis, understanding Machine Learning Systems (MLOps), Trustworthy AI and applications of AI/Deep Learning in the Sciences. I teach lectures at the BSc and MSc level in computer science and data science.

In a previous life, I performed fundamental research in Particle Physics at major international research Labs such as CERN (Geneva) and DESY (Hamburg). In 2012, I contributed to the experimental discovery of the Higgs particle at CERN, whose theoretical prediction was awarded with the 2013 Nobel Prize in Physics. I obtained a PhD in physics from the University of Heidelberg in 2001.

Profile page at ZHAW

Some recent publications are listed below:

selected publications

  1. Diffusion
    Models
    3D Diffusion Models for Medical Imaging
    Frank-Peter Schilling, Daniel Barco, Philipp Denzel, and Marc Stadelmann
    arXiv preprint 2610.26475, 2026
  2. Energy Matching
    in GenAI
    Projected Energy Matching for Generative 3D Priors
    Daniel Barco, Michal Balcerak, Suprosanna Shit, Chinmay Prabhakar, Philipp Denzel, Bjoern Menze, and Frank-Peter Schilling
    arXiv preprint 2607.07749, 2026
  3. AI for Science
    The Role of Artificial Intelligence in the SKA Era
    Philipp Denzel, Elena Gavagnin, and Frank-Peter Schilling
    In Advancing Astrophysics with the SKA II (AASKAII), 2026
  4. AI for
    Med. Imaging
    MInDI-3D: Iterative Deep Learning in 3D for Sparse-View Cone Beam Computed Tomography
    Daniel Barco, Marc Stadelmann, Martin Oswald, Ivo Herzig, Lukas Lichtensteiger, Pascal Paysan, Igor Peterlik, Michal Walczak, Bjoern Menze, and Frank-Peter Schilling
    IEEE Access, 2026
  5. GenAI for
    Astrophysics
    Galactic Alchemy: Deep Learning Map-to-Map Translation in Hydrodynamical Simulations
    Philipp Denzel, Yann Billeter, Frank-Peter Schilling, and Elena Gavagnin
    Monthly Notices of the Royal Astronomical Society, Feb 2026