Prof. Dr. Frank-Peter Schilling

Persönliches Profil

Leitungsfunktion

Leitung Gruppe "Intelligent Vision Systems" am CAI

Tätigkeit an der ZHAW

Dozent und Gruppenleiter, Centre for Artificial Intelligence (CAI)
Adjunct Professor, Victoria University of Wellington (NZ)
Leiter Weiterbildung CAI
Akademischer Koordinator, Doktoratsprogram Data Science (mit Univ. Zürich)
Forschungsschwerpunkt: Computer Vision / MLOps
Mitglied der Arbeitsgruppe DIZH fellowships, ZHAW digital
Organisator des Datalab-Seminars

Homepage: fpschill.github.io
Arbeitsgruppe: www.zhaw.ch/de/engineering/institute-zentren/cai/intelligent-vision-systems-group/

www.zhaw.ch/en/engineering/institutes-centres/cai/

Lehrtätigkeit in der Weiterbildung

CAS Machine Intelligence

Arbeits- und Forschungsschwerpunkte, Spezialkenntnisse

Künstliche Intelligenz, Deep Learning, Physik

Aus- und Fortbildung

Adjunct Professor, Victoria University of Wellington (NZ), 2022
IPMA Zertifizierung im Projektmanagment, 2015
Doktorat in Physik, Universität Heidelberg, 2001

Beruflicher Werdegang

- Leitender wissenschaftlicher Mitarbeiter, CERN & Karlsruher Institut für Technologie KIT, Genf (CH)
- Research Fellow, CERN, Genf (CH)
- Wissenschaftlicher Mitarbeiter, Deutsches Elektronen-Synchrotron DESY, Hamburg (DE)

Mitglied in Netzwerken

• ZHAW Datalab
• Deutsche Physikalische Gesellschaft DPG
• European Physical Society EPS
• Confederation of Laboratories for AI Research in Europe CLAIRE
• European Lab for Learning and Intelligent Systems ELLIS

Projekte

• certAInty – A Certification Scheme for AI systems / Teammitglied / Projekt laufend
• OSR4H – Open Set Recognition for Hematology / ProjektleiterIn / Projekt laufend
• AC3T – AI powered CBCT for improved Combination Cancer Therapy / ProjektleiterIn / Projekt laufend
• Square Kilometre Array: Simulierte astronomische Beobachtungen durch generative Deep Learning / Stellv. ProjektleiterIn / Projekt laufend
• Standardized Data and Modeling for AI-based CoVID-19 Diagnosis Support on CT Scans (SDMCT) / Teammitglied / Projekt abgeschlossen
• DIR3CT: Deep Image Reconstruction through X-Ray Projection-based 3D Learning of Computed Tomography Volumes / ProjektleiterIn / Projekt abgeschlossen
• TAILOR – Foundations of Trustworthy AI - Integrating Reasoning, Learning and Optimization / Teammitglied / Projekt abgeschlossen
• RealScore – Scanning of Real-World Sheet Music for a Digital Music Stand / Co-ProjektleiterIn / Projekt abgeschlossen
• FWA: Visual Food Waste Analysis for Sustainable Kitchens / Teammitglied / Projekt abgeschlossen
• QualitAI - Quality control of industrial products via deep learning on images / Teammitglied / Projekt abgeschlossen

Publikationen

• 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).

  Verfügbar unter: 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), S. 510-538.

  Verfügbar unter: https://doi.org/10.3390/ai1040031

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

  2022.

  Advances in deep neural networks for visual pattern recognition.

  Basel:

  MDPI.

  Journal of Imaging ; 8.

  Verfügbar unter: https://www.mdpi.com/journal/jimaging/special_issues/deep_neural_network

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

  2020.

  Artificial neural networks in pattern recognition.

  Basel:

  MDPI.

  Computers ; 9.

  Verfügbar unter: https://www.mdpi.com/journal/computers/special_issues/ANNPR2020

• 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.

  S. e325-e326.

  Verfügbar unter: 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.

  S. 26-31.

  Verfügbar unter: 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.

  Verfügbar unter: https://doi.org/10.21256/zhaw-22061

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

  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.

  Verfügbar unter: https://doi.org/10.1007/978-3-030-58309-5

• Stadelmann, Thilo; Schilling, Frank-Peter,

  2019.

  Deep Learning in medizinischer Diagnostik und Qualitätskontrolle.

  Netzwoche.

  Verfügbar unter: 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.

  Verfügbar unter: https://doi.org/10.21256/zhaw-18357

Publikationen vor Tätigkeit an der ZHAW

See also: fpschill.github.io/publications/

Google Scholar: scholar.google.com/citations

Selected most important publications:

[1] F.-P. Schilling, “Top Quark Physics at the LHC: A Review of the First Two Years,” Int. J. Mod. Phys., vol. A27, no. 17, p. 1230016, 2012, doi.org/10.1142/s0217751x12300165.

[2] S. Chatrchyan et al., “Measurement of the mass difference between top quark and antiquark in pp collisions at $sqrt{s} = 8$ TeV,” Phys. Lett. B, vol. 770, pp. 50–71, 2017, doi.org/10.1016/j.physletb.2017.04.028.

[3] S. Chatrchyan et al., “Evidence for the direct decay of the 125 GeV Higgs boson to fermions,” Nature Phys., vol. 10, p. 557, 2014, doi.org/10.1038/nphys3005.

[4] S. Chatrchyan et al., “Search for the standard model Higgs boson produced in association with a W or a Z boson and decaying to bottom quarks,” Phys. Rev., vol. D89, p. 012003, 2014, doi.org/10.1103/PhysRevD.89.012003.

[5] S. Chatrchyan et al., “Observation of a new boson with mass near 125 GeV in pp collisions at $sqrt{s}$ = 7 and 8 TeV,” JHEP, vol. 1306, p. 081, 2013, doi.org/10.1007/JHEP06(2013)081.

[6] S. Chatrchyan et al., “A New Boson with a Mass of 125 GeV Observed with the CMS Experiment at the Large Hadron Collider,” Science, vol. 338, p. 1569, 2012, doi.org/10.1126/science.1230816.

[7] S. Chatrchyan et al., “Observation of a new boson at a mass of 125 GeV with the CMS experiment at the LHC,” Phys.Lett., vol. B716, pp. 30–61, 2012, doi.org/10.1016/j.physletb.2012.08.021.

[8] S. Chatrchyan et al., “Measurement of the single-top-quark t-channel cross section in pp collisions at $sqrt{s}=7$ TeV,” JHEP, vol. 1212, p. 035, 2012, doi.org/10.1007/JHEP12(2012)035.

[9] S. Chatrchyan et al., “Inclusive and differential measurements of the tt̄ charge asymmetry in proton-proton collisions at 7 TeV,” Phys.Lett., vol. B717, pp. 129–150, 2012, doi.org/10.1016/j.physletb.2012.09.028.

[10] S. Chatrchyan et al., “Measurement of the charge asymmetry in top-quark pair production in proton-proton collisions at sqrt(s) = 7 TeV,” Phys.Lett., vol. B709, pp. 28–49, 2012, doi.org/10.1016/j.physletb.2012.01.078.

[11] S. Chatrchyan et al., “Measurement of the tt̄ Production Cross Section in pp Collisions at 7 TeV in Lepton + Jets Events Using b-quark Jet Identification,” Phys.Rev., vol. D84, p. 092004, 2011, doi.org/10.1103/PhysRevD.84.092004.

[12] S. Chatrchyan et al., “Measurement of the t-channel single top quark production cross section in pp collisions at sqrt(s) = 7 TeV,” Phys.Rev.Lett., vol. 107, p. 091802, 2011, doi.org/10.1103/PhysRevLett.107.091802.

[13] S. Chatrchyan et al., “Measurement of the t t-bar production cross section and the top quark mass in the dilepton channel in pp collisions at sqrt(s) =7 TeV,” JHEP, vol. 7, p. 049, 2011, doi.org/10.1007/JHEP07(2011)049.

[14] S. Chatrchyan et al., “Measurement of the Top-antitop Production Cross Section in pp Collisions at sqrt(s)=7 TeV using the Kinematic Properties of Events with Leptons and Jets,” Eur. Phys. J., vol. C71, p. 1721, 2011, doi.org/10.1140/epjc/s10052-011-1721-3.

[15] V. Khachatryan et al., “First Measurement of the Cross Section for Top-Quark Pair Production in Proton-Proton Collisions at sqrt(s)=7 TeV,” Phys.Lett., vol. B695, pp. 424–443, 2011, doi.org/10.1016/j.physletb.2010.11.058.

[16] S. Chatrchyan et al., “Alignment of the CMS Silicon Tracker during Commissioning with Cosmic Rays,” JINST, vol. 5, p. T03009, 2010, doi.org/10.1088/1748-0221/5/03/T03009.

[17] W. Adam et al., “Alignment of the CMS Silicon Strip Tracker during standalone Commissioning,” JINST, vol. 4, p. T07001, 2009, doi.org/10.1088/1748-0221/4/07/T07001.

[18] W. Adam et al., “The CMS tracker operation and performance at the Magnet Test and Cosmic Challenge,” JINST, vol. 3, p. P07006, 2008, doi.org/10.1088/1748-0221/3/07/P07006.

[19] R. Adolphi et al., “The CMS experiment at the CERN LHC,” JINST, vol. 3, p. S08004, 2008, doi.org/10.1088/1748-0221/3/08/S08004.

[20] G. L. Bayatian et al., “CMS technical design report, volume II: Physics performance,” J. Phys., vol. G34, pp. 995–1579, 2007, doi.org/10.1088/0954-3899/34/6/S01.

[21] V. Karimaki, T. Lampen, and F.-P. Schilling, “Track-based alignment of composite detector structures,” IEEE Trans. Nucl. Sci., vol. 53, pp. 3830–3833, 2006, doi.org/10.1109/TNS.2006.884384.

[22] A. Aktas et al., “Measurement and QCD analysis of the diffractive deep- inelastic scattering cross-section at HERA,” Eur. Phys. J., vol. C48, pp. 715–748, 2006, doi.org/10.1140/epjc/s10052-006-0035-3.

[23] A. Aktas et al., “Diffractive deep-inelastic scattering with a leading proton at HERA,” Eur. Phys. J., vol. C48, pp. 749–766, 2006, doi.org/10.1140/epjc/s10052-006-0046-0.

[24] C. Adloff et al., “Measurement of inclusive jet cross-sections in photoproduction at HERA,” Eur. Phys. J., vol. C29, pp. 497–513, 2003, doi.org/10.1140/epjc/s2003-01262-9.

[25] A. Aktas et al., “Diffractive photoproduction of J/ψ mesons with large momentum transfer at HERA,” Phys. Lett., vol. B568, pp. 205–218, 2003, doi.org/10.1016/j.physletb.2003.06.056.

[26] C. Adloff et al., “Search for odderon-induced contributions to exclusive pi0 photoproduction at HERA,” Phys. Lett., vol. B544, pp. 35–43, 2002, doi.org/10.1016/S0370-2693(02)02479-6.

[27] C. Adloff et al., “A measurement of the t dependence of the helicity structure of diffractive rho meson electroproduction at HERA,” Phys. Lett., vol. B539, pp. 25–39, 2002, doi.org/10.1016/S0370-2693(02)02035-X.

[28] C. Adloff et al., “Energy flow and rapidity gaps between jets in photoproduction at HERA,” Eur. Phys. J., vol. C24, pp. 517–527, 2002, doi.org/10.1007/s10052-002-0988-9.

[29] C. Adloff et al., “Diffractive jet production in deep inelastic e⁺p collisions at HERA,” Eur. Phys. J., vol. C20, pp. 29–49, 2001, doi.org/10.1007/s100520100634.

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