Koller Thomas HSLU I

Prof. Dr. Thomas Koller Thomas Koller

Head of the Master's Program in Engineering

Koller Thomas HSLU I

Lucerne School of Computer Science and Information Technology

Room 7.54
Campus Zug-Rotkreuz
Suurstoffi 1
6343 Rotkreuz


Research

Degree Programs

Head of the Master's Program in Engineering

Lecturer

+41 41 757 68 32

Show email

Biography

Aus- und Weiterbildung:

  • Dipl. Informatikingenieur, ETH Zürich,
  • Dr. sc. techn., ETH Zürich.

Berufliche Stationen:

  • Hilfsassistent, Interdisziplinäres Projektzentrum für Supercomputing, ETH Zürich,
  • Assistent Institut für Bildverarbeitung, ETH Zürich,
  • Leiter Software Entwicklung, Bitplane AG,
  • Kursleiter für C++, Digicomp AG,
  • Software Engineering Berater, Zühlke AG.

Schwerpunkte an der Hochschule Luzern:

  • Bildverarbeitung und Computer Vision,
  • Machine Learning, Deep Learning
  • Computer Grafik,
  • Virtual- und Augmented Reality

Sonstiges:

  • Vorstand Software Engineering Network (SWEN)
Teaching and research focus
  • Image Processing & Computer Vision
  • Machine Learning, Deep Learning
  • Reinforcement Learning

Projects

Research projects

  • AI Supported MultiTouch for Range Images
  • MAM : Machine-managed Air Mobility in Swiss Upper Airspace
  • Software Skizzieren - Agile Modeling
  • Deep Neural Yodeling
  • Kurzfristige Prognose und Steuerung des Gästeaufkommens im Freizeit- und Tourismusmarkt
  • Skin-App: Medical Severity Grading of Hand Eczema by Automated Image Analysis
  • Winkelvermessung für Spurhalter mittels Bildverarbeitung
  • JassBot: Ein intelligentes Jass Programm
  • SkinApp-Web: Harnessing Training Data from the Crowd
  • Objektive Messung der Handhygiene mit Machine Learning
  • 3D Multiplayer Tracking
  • FAST
  • Seilschonende Klemmplatte für Montage und Unterhalt
  • Skin-App
  • SoVeCo: Software Vergabe bei Coentwicklung

Publications and presentations

Publications and presentations - Article, review; peer reviewed

  • Bürli, Andrin; Beck, Melissa; Bravin, Marc & Koller, Thomas (2022). Minimal Hand Pose Estimation for Touchable Projector-Depth Systems. Proceedings of the 9th Swiss Data Science Conference, 1.
  • Amruthalingam, Ludovic; Gökduman, Bulus; Gonzalez-Jimenez, Alvaro; Gottfrois, Philippe Léon-Marius; Koller, Thomas; Kunz, Michael; Navarini, Alexander & Pouly, Marc (2022). Improved Diagnosis by Automated Macro- and Micro-anatomical Region Mapping of Skin Photographs. Journal of European Academy of Dermatology Venereology, 2022, 10. doi: 10.1111/jdv.18476
  • Amruthalingam, Ludovic; Buerzle, Oliver; Gonzalez Jimenez, Alvaro; Gottfrois, Philippe Léon-Marius; Koller, Thomas; Navarini, Alexander; Pouly, Marc & Roth, Anastasia (2022). Quantification of Efflorescences in Pustular Psoriasis using Deep Learning. Healthcare Informatics Research, 2022(Volume 28(3)), 222-230. doi: 10.4258/hir.2022.28.3.222
  • Niklaus, Joel; Alberti, Michele; Ingold, Rolf; Stolze, Markus & Koller, Thomas (12.10.2020). Challenging Human Supremacy: Evaluating Monte Carlo Tree Search and Deep Learning for the Trick Taking Card Game Jass. ICAISC 2020, 2020, 1.
  • Pouly, Marc; Koller, Thomas; Gottfrois, Philippe Léon-Marius & Lionetti, Simone (2020). KI in der Bildanalyse – Grundlagen und neue Entwicklungen. Springer - Der Hautarzt, 2020(9), 660-668. doi: 10.1007/s00105-020-04663-7
  • Pouly, Marc; Koller, Thomas & Arnold, Ruedi (2019). A Game-Centric Approach to Teaching Artificial Intelligence. Proceedings of the 11th International Conference on Computer Supported Education, 2020, 398-404. doi: 10.5220/0007745203980404
  • Meienberger, Nina; Anzengruber, Florian; Amruthalingam, Ludovic; Christen, Roland; Koller, Thomas; Maul, J.; Pouly, Marc; Djamei, Vahid & Navarini, Alexander (2019). Observer-Independent Assessment of Psoriasis affected Area using Machine Learning. Journal of the European Academy of Dermatology & Venerology, 2019 / 34(6), 1362-1368. doi: 10.1111/jdv.16002
  • Koller, Thomas; Navarini, Alexander; Pouly, Marc; Schnürle, Stefan & vor der Brück, Tim (2017). On using Support Vector Machines for the Detection and Quantification of Hand Eczema. Proceedings of the 9th International Conference on Agents and Artificial Intelligence, 2017, 75-84. doi: 10.5220/0006125000750084
  • Suter, Christoph; Navarini, Alexander; Pouly, Marc; Arnold, Ruedi; Gutzwiller Florian S., Meier; Koller, Thomas & Meier, René (2014). Detection and Quantification of Hand Eczema by Visible Spectrum Skin Pattern Analysis. Frontiers in Artificial Intelligence and Applications, 2014(Frontiers in Artificial Intelligence and Applications, Volume 263: ECAI 2014), 1101-1102. doi: 10.3233/978-1-61499-419-0-1101

Publications and presentations - Theses (Bachelor/Master/Dissertation/Habilitation)

  • Birbaumer, Mirko; Himmelberger, Pascal & Koller, Thomas (2021). Generative Adversarial Networks (GANs) as an Alternative to Procedural Level/Map Design in PCbased Video Game Applications (nicht veröffentlichte Master-/Lizentiats-/Diplomarbeit). HSLU Zentralschweiz, Schweiz.

Achievements - Awards and honours

  • Bravin, Marc; Bürli, Andrin; Beck, Melissa & Koller, Thomas (23.06.2022). Best Poster Video Award für Conference Paper Minimal Hand Pose Estimation for Touchable Projector-Depth Systems.
  • Hofstetter, Jörg; Koller, Thomas; Pouly, Marc; Schnürle, Stefan & vor der Brück, Tim (26.10.2017). aha! Award des Allergiezentrums Schweiz 2017 für SkinApp – Digitale Sicht zur Schweregrad-Messung für Ekzempatienten.

Achievements - Other achievements

  • Arnold, Ruedi; Bürli, Andrin; Birbaumer, Mirko; Bravin, Marc; Daly, Donnacha; Kakooee, Reza; Koller, Thomas; Lionetti, Simone; Mazumder, Sita; Mérinat, Tobias; Pfäffli, Daniel; Pouly, Marc; Salzmann, Joel & Wullschleger, Pascal. Member of the Team that crafted the first Beer along an AI generated Recipe. ABIZ Team Achievement. Hochschule Luzern - Informatik.
  • Arnold, Ruedi; Christen, Roland; Hofstetter, Jörg; Koller, Thomas; Mazumder, Sita; Pfäffli, Daniel; Pouly, Marc; Schnürle, Stefan & vor der Brück, Tim. ABIZ Jodelkurs. Forschungsprojekt: Deep Neural Yodeling. Algorithmic Business Research Team.