Dr. Claus Horn

ZHAW Life Sciences und Facility Management
FS Autonomous Systems and Reinforcement Learning
Schloss 1
8820 Wädenswil

Persönliches Profil

Leitungsfunktion

Leitung Forschungsgruppe für Autonome Systeme und Reinforcement Learning

Tätigkeit an der ZHAW

Dozent (Institut für Computational Life Sciences)
Leiter Weiterbildung ICLS

Unterrichtete Fächer:
Machine Learning
Advanced Deep Learning

Lehrtätigkeit in der Weiterbildung

Arbeits- und Forschungsschwerpunkte, Spezialkenntnisse

Vorhersage- und Steuerungsmodelle basierend auf sequenziellen Daten mit Hilfe von Reinforcement Learning und Deep Learning; Neuronale Graphen Netze; Kausale Folgerung; Künstliche Intelligenz

Aus- und Fortbildung

2023 - CAS Management & Leadership
2021 - CAS Hochschuldidaktik
2006 - Dr. rer. nat. in Teilchenphysik
2007 - Diplom-Ökonom
2003 - Diplom-Physiker

Beruflicher Werdegang

Lead Data Scientist, Migros, Zürich
Cognitive Data Scientist, Swiss Re, Zürich
Researcher, CERN, Genf
Postdoc, Stanford University, Palo Alto, Kalifornien

Mitglied in Netzwerken

Projekte

Publikationen

Beiträge in wissenschaftlicher Zeitschrift, peer-reviewed

Garcia, Victor; Horn, Claus; Ott, Thomas,

2022.

The sciences of data – moving towards a comprehensive systems perspective.

Archives of Data Science, Series A.

8(2).

Verfügbar unter: https://doi.org/10.5445/IR/1000150241

Konferenzbeiträge, peer-reviewed

Horn, Claus; Nyfeler, Matthias; Müller, Georg; Schüpbach, Christof,

2022.

Drone radio signal detection with multi-timescale deep neural networks [Paper].

In:

Yurish, Sergey Y., Hrsg.,

Proceedings of the 4th International Conference on Advances in Signal Processing and Artificial Intelligence.

4th International Conference on Advances in Signal Processing and Artificial Intelligence (ASPAI), Corfu, Greece, 19-21 October 2022.

IFSA Publishing.

S. 140-143.

Verfügbar unter: https://doi.org/10.21256/zhaw-27185

Weitere Publikationen

Imstepf, Nicolas; Senn, Saskia; Fortin, Antonio; Russell, Benjamin; Horn, Claus,

2022.

A learned simulation environment to model student engagement and retention in automated online courses.

arXiv.

Verfügbar unter: https://doi.org/10.48550/arXiv.2212.14693
Amacker, Julian; Kleiven, Thomas; Grigore, Mihai; Albrecht, Patrick; Horn, Claus,

2022.

A learned simulation environment to model plant growth in indoor farming.

arXiv.

Verfügbar unter: https://doi.org/10.48550/arXiv.2212.03155

Publikationen vor Tätigkeit an der ZHAW

ATLAS Collaboration, „Combined search for the Standard Model Higgs boson in pp collisions at √s=7 TeV with the ATLAS detector“, Phys.Rev. D86 (2012) 032003.

ATLAS Collaboration, “Search for a light Higgs boson decaying to long-lived weakly-interacting particles in proton-proton collisions at √s = 7 TeV with the ATLAS detector“, Phys.Rev.Lett. 108 (2012) 251801

ATLAS Collaboration, „Search for displaced vertices arising from decays of new heavy particles in 7 TeV pp collisions at ATLAS“, Phys.Lett. B707 (2012) 478-496

ATLAS Collaboration, “Search for supersymmetry using final states with one lepton, jets, and missing transverse momentum with the ATLAS detector in s√=7 TeV pp”, Phys.Rev.Lett. 106 (2011) 131802

ATLAS Collaboration, “The ATLAS Simulation Infrastructure”, Eur.Phys.J. C70 (2010) 823-874

ATLAS Collaboration, “Performance of the ATLAS Trigger System in 2010”, Eur.Phys.J. C72 (2012) 1849

C. Horn, „A Bottom-Up Approach to SUSY Analysis“, J. Phys. G: Nucl. Part. Phys. 36 (2009) 105005.

ATLAS Collaboration, “Expected Performance of the ATLAS Experiment - Detector, Trigger and Physics”, SLAC-R-980, CERN-OPEN-2008-020.

C. Horn, “Search for gravitinos in R-parity violating supersymmetry at HERA”, Ph.D. Thesis, DESY (2006).

C. Horn, “Crystal Growth of the Organic Semiconductors Tetracene and PTCDA on Self-Assembled Monolayers absorbed on Al2O3 Substrates”, Master Thesis (2003).

For a more complete list see:
scholar.google.com/citations

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