Prof. Dr. Frank-Peter Schilling

Work at ZHAW

Position

• Director a.i., Deputy Director, Centre for Artificial Intelligence (CAI)
• Group Leader, Intelligent Vision Systems (IVS), CAI
• Coordinator, PhD Programme in Data Science (with Univ. Zurich)
• Adjunct Professor, Victoria University of Wellington (NZ)

Focus

Artificial Intelligence, Machine Learning, Deep Learning, Physics

Teaching

• Machine Learning Operations (MLOps, BSc IT+DS, 2024)
• Computer Vision with Deep Learning (CVDL, BSc IT+DS, 2024)
• Artificial Intelligence I (AI1, BSc IT, 2019, 2020, 2021, 2022)
• Deep Learning (CAS Machine Intelligence, 2022, 2023)
• Machine Intelligence Lab (MSc, 2019)
• AI Seminar (MSc, 2019)

Professional development teaching

• WBK Generative KI in Lehre und Weiterbildung
• CAS Advanced Machine Learning and Machine Learning Operations

Experience

• Senior Lecturer
  ZHAW
  2022 - today
• Senior Researcher
  ZHAW
  2019 - 2022

Education and Continuing education

Education

• PhD / Physics
  University of Heidelberg
  1998 - 2001
• Dipl.-Phys. (MSc equiv.) / Physics
  University of Heidelberg
  1992 - 1998

Continuing Education

• CAS University Didactics
  PH Zurich
  2024
• Certified Project Management Associate
  IPMA
  2015

Network

Membership of networks

• Confederation of Laboratories for AI Research in Europe CLAIRE
• data innovation alliance
• European Lab for Learning and Intelligent Systems ELLIS (Supporter)
• European Physical Society EPS
• Deutsche Physikalische Gesellschaft DPG
• ZHAW Datalab
• ZHAW Digital Health Lab
• ZHAW Digital Futures Lab

Awards

EPS HEP Prize
European Physical Society
07 / 2013

Social media

• LinkedIn
• Personal Home Page

Projects

• Certification program for assessing ethics of Autonomous Intelligent Systems (IEEE CertifAIEd Assessor Training) / Project leader / laufend
• certAInty – A Certification Scheme for AI systems / Team member / laufend
• AC3T – AI powered CBCT for improved Combination Cancer Therapy / Project leader / laufend
• Square Kilometre Array: Mock-observations via generative deep learning / Deputy project leader / laufend
• PhD Program in Data Science / Project leader / laufend
• OSR4H – Open Set Recognition for Hematology / Project leader / abgeschlossen
• DIR3CT: Deep Image Reconstruction through X-Ray Projection-based 3D Learning of Computed Tomography Volumes / Project leader / abgeschlossen
• TAILOR – Foundations of Trustworthy AI - Integrating Reasoning, Learning and Optimization / Team member / abgeschlossen
• RealScore – Scanning of Real-World Sheet Music for a Digital Music Stand / Co-project leader / abgeschlossen
• FWA: Visual Food Waste Analysis for Sustainable Kitchens / Team member / abgeschlossen

Publications

• Amirian, Mohammadreza; Barco, Daniel; Herzig, Ivo; Schilling, Frank-Peter,

  2024.

  Artifact reduction in 3D and 4D cone-beam computed tomography images with deep learning - a review.

  IEEE Access.

  Available from: https://doi.org/10.1109/ACCESS.2024.3353195

• Amirian, Mohammadreza; Montoya-Zegarra, Javier A.; Herzig, Ivo; Eggenberger Hotz, Peter; Lichtensteiger, Lukas; Morf, Marco; Züst, Alexander; Paysan, Pascal; Peterlik, Igor; Scheib, Stefan; Füchslin, Rudolf Marcel; Stadelmann, Thilo; Schilling, Frank-Peter,

  2023.

  Mitigation of motion-induced artifacts in cone beam computed tomography using deep convolutional neural networks.

  Medical Physics.

  50(10), pp. 6228-6242.

  Available from: https://doi.org/10.1002/mp.16405

• Schilling, Frank-Peter; Flumini, Dandolo; Füchslin, Rudolf Marcel; Gavagnin, Elena; Geller, Armando; Quarteroni, Silvia; Stadelmann, Thilo,

  2022.

  Foundations of Data Science : a comprehensive overview formed at the 1st International Symposium on the Science of Data Science.

  Archives of Data Science, Series A.

  8(2).

  Available from: https://doi.org/10.5445/IR/1000146422

• Tuggener, Lukas; Amirian, Mohammadreza; Benites de Azevedo e Souza, Fernando; von Däniken, Pius; Gupta, Prakhar; Schilling, Frank-Peter; Stadelmann, Thilo,

  2020.

  Design patterns for resource-constrained automated deep-learning methods.

  AI.

  1(4), pp. 510-538.

  Available from: https://doi.org/10.3390/ai1040031

• Stadelmann, Thilo; Schilling, Frank-Peter, eds.,

  2022.

  Advances in deep neural networks for visual pattern recognition.

  Basel:

  MDPI.

  Journal of Imaging ; 8.

  Available from: https://www.mdpi.com/journal/jimaging/special_issues/deep_neural_network

• Schilling, Frank-Peter; Stadelmann, Thilo, eds.,

  2020.

  Artificial neural networks in pattern recognition.

  Basel:

  MDPI.

  Computers ; 9.

  Available from: https://www.mdpi.com/journal/computers/special_issues/ANNPR2020

• Billeter, Yann; Denzel, Philipp; Chavarriaga, Ricardo; Forster, Oliver; Schilling, Frank-Peter; Brunner, Stefan; Frischknecht-Gruber, Carmen; Reif, Monika Ulrike; Weng, Joanna,

  2024.

  MLOps as enabler of trustworthy AI [paper].

  In:

  2024 11th IEEE Swiss Conference on Data Science (SDS).

  11th IEEE Swiss Conference on Data Science (SDS), Zurich, Switzerland, 30-31 May 2024.

  IEEE.

  pp. 37-40.

  Available from: https://doi.org/10.1109/SDS60720.2024.00013

• Denzel, Philipp; Brunner, Stefan; Billeter, Yann; Forster, Oliver; Frischknecht-Gruber, Carmen; Reif, Monika Ulrike; Schilling, Frank-Peter; Weng, Joanna; Chavarriaga, Ricardo; Amini, Amin; Repetto, Marco; Iranfar, Arman,

  2024.

  Towards the certification of AI-based systems [paper].

  In:

  2024 11th IEEE Swiss Conference on Data Science (SDS).

  11th IEEE Swiss Conference on Data Science (SDS), Zurich, Switzerland, 30-31 May 2024.

  IEEE.

  pp. 84-91.

  Available from: https://doi.org/10.1109/SDS60720.2024.00020

• Weng, Joanna; Denzel, Philipp; Reif, Monika Ulrike; Schilling, Frank-Peter; Billeter, Yann; Frischknecht-Gruber, Carmen; Brunner, Stefan; Chavarriaga, Ricardo; Repetto, Marco; Iranfar, Arman,

  2024.

  Certification scheme for artificial intelligence based systems [paper].

  In:

  34th European Safety and Reliability Conference (ESREL), Cracow, Poland, 23-27 June 2024.

  ZHAW Zürcher Hochschule für Angewandte Wissenschaften.

  Available from: https://doi.org/10.21256/zhaw-30549

• Herzig, Ivo; Paysan, Pascal; Scheib, Stefan; Züst, Alexander; Schilling, Frank-Peter; Montoya, Javier; Amirian, Mohammadreza; Stadelmann, Thilo; Eggenberger Hotz, Peter; Füchslin, Rudolf Marcel; Lichtensteiger, Lukas,

  2022.

  Deep learning-based simultaneous multi-phase deformable image registration of sparse 4D-CBCT [poster].

  In:

  AAPM Annual Meeting, Washington, DC, USA, 10-14 July 2022.

  American Association of Physicists in Medicine.

  pp. e325-e326.

  Available from: https://doi.org/10.1002/mp.15769

• Simmler, Niclas; Sager, Pascal; Andermatt, Philipp; Chavarriaga, Ricardo; Schilling, Frank-Peter; Rosenthal, Matthias; Stadelmann, Thilo,

  2021.

  A survey of un-, weakly-, and semi-supervised learning methods for noisy, missing and partial labels in industrial vision applications [paper].

  In:

  Proceedings of the 8th SDS.

  8th Swiss Conference on Data Science, Lucerne, Switzerland, 9 June 2021.

  IEEE.

  pp. 26-31.

  Available from: https://doi.org/10.1109/SDS51136.2021.00012

• Amirian, Mohammadreza; Tuggener, Lukas; Chavarriaga, Ricardo; Satyawan, Yvan Putra; Schilling, Frank-Peter; Schwenker, Friedhelm; Stadelmann, Thilo,

  2021.

  Two to trust : AutoML for safe modelling and interpretable deep learning for robustness [paper].

  In:

  Postproceedings of the 1st TAILOR Workshop on Trustworthy AI at ECAI 2020.

  1st TAILOR Workshop on Trustworthy AI at ECAI 2020, Santiago de Compostela, Spain, 29-30 August 2020.

  Springer.

  Available from: https://doi.org/10.21256/zhaw-22061

• Schilling, Frank-Peter; Stadelmann, Thilo, eds.,

  2020.

  Artificial neural networks in pattern recognition : proceedings of the 9th IAPR TC3 workshop, ANNPR 2020, Winterthur, Switzerland, September 2–4, 2020.

  9th IAPR TC 3 Workshop on Artificial Neural Networks for Pattern Recognition (ANNPR'20), Winterthur, Switzerland, 2-4 September 2020.

  Springer.

  Lecture Notes in Computer Science ; 12294.

  ISBN 978-3-030-58308-8.

  Available from: https://doi.org/10.1007/978-3-030-58309-5

• Denzel, Philipp; Schilling, Frank-Peter; Gavagnin, Elena,

  2023.

  Map-to-map translation for SKA mock observations and cosmological simulations [poster].

  In:

  Hammers & Nails 2023 - Swiss Edition, Ascona, Switzerland, 29 October - 3 November 2023.

  Winterthur:

  ZHAW Zürcher Hochschule für Angewandte Wissenschaften.

  Available from: https://doi.org/10.21256/zhaw-29047

• Weng, Joanna; Reif, Monika; Chavarriaga, Ricardo; Schilling, Frank-Peter,

  2023.

  certAInty : a certification scheme for AI systems (Innosuisse project) [poster].

  In:

  Datalab Symposium, Winterthur, Schweiz, 11. Januar 2023.

  ZHAW Zürcher Hochschule für Angewandte Wissenschaften.

  Available from: https://doi.org/10.21256/zhaw-27261

• Denzel, Philipp Benedikt; Schilling, Frank-Peter; Gavagnin, Elena,

  2023.

  Deep learning the SKA : the Square Kilometer Array project [poster].

  In:

  Datalab Symposium, Winterthur, Schweiz, 11. Januar 2023.

  ZHAW Zürcher Hochschule für Angewandte Wissenschaften.

  Available from: https://doi.org/10.21256/zhaw-27219

• Stadelmann, Thilo; Schilling, Frank-Peter,

  2019.

  Deep Learning in medizinischer Diagnostik und Qualitätskontrolle.

  Netzwoche.

  Available from: https://doi.org/10.21256/zhaw-20163

• Amirian, Mohammadreza; Rombach, Katharina; Tuggener, Lukas; Schilling, Frank-Peter; Stadelmann, Thilo,

  2019.

  Efficient deep CNNs for cross-modal automated computer vision under time and space constraints [paper].

  In:

  ECML-PKDD 2019, Würzburg, Germany, 16-19 September 2019.

  ZHAW Zürcher Hochschule für Angewandte Wissenschaften.

  Available from: https://doi.org/10.21256/zhaw-18357

• Denzel, Philipp; Brunner, Stefan; Luley, Paul-Philipp; Frischknecht-Gruber, Carmen; Reif, Monika Ulrike; Schilling, Frank-Peter; Amini, Amin; Repetto, Marco; Iranfar, Arman; Weng, Joanna; Chavarriaga, Ricardo,

  2023.

  A framework for assessing and certifying explainability of health-oriented AI systems.

  In:

  Explainable AI in Medicine Workshop, Lugano, Switzerland, 2-3 November 2023.

Other publications

• https://fpschill.github.io/publications/
• Google Scholar
• ORCID

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