Prof. Dr. Helmut Grabner

Personal profile

Position at the ZHAW

Professor of Data Analytics and Machine Learning
Delegate Entrepreneurship School of Engineering

www.zhaw.ch/de/engineering/entrepreneurship/

www.zhaw.ch/idp

Expertise and research interests

Machine Learning
Deep Learning
Computer Vision
Entrepreneurship

Computer Vision meets Art: webcamaze.engineering.zhaw.ch

Educational background

1999-2008: Graz University of Technology, PhD
2020-2021: Certificate of Advanced Studies in Higher & Professional Education

Professional milestones

2008-2014: Post-Doc Researcher at ETH Zurich
2012-2015: CTO & co-founder upicto GmbH
2015-2019: Lead Computer Vision Eng, CTO Office at Logitech

Membership of networks

• CV
• LinkedIn
• My old homepage at ETH Zurich

Projects

• Visual Interestingness / Project leader / Project ongoing
• Watching the World / Project leader / Project ongoing
• Deep Learning Klassifikation zur Identifikation von Neophyten am Beispiel des Erdmandelgrases / Project leader / Project ongoing
• Surgical Proficiency – Data-driven transformation of surgical education for proficiency-based performance / Deputy project leader / Project ongoing
• Target Recognition using Artificial Intelligence (TRAI) / Team member / Project ongoing
• Machine Learning-Aided Startup Investing (MALASI) / Project leader / Project completed
• To be liked or not to be liked – what makes a photo interesting? / Project co-leader / Project completed
• Towards Explainable Artificial Intelligence and Machine Learning in Credit Risk Management / Team member / Project completed
• Artificial Intelligence to improve venture capital decision making / Project leader / Project completed
• UNY id – Person identification based on motion and behavior / Project leader / Project completed
• Intelligent Viticulture / Project co-leader / Project completed
• Apalion KISS / Project leader / Project completed

Publications

• Schmid, N.; Bruderer, S.; Paruzzo, F.; Fischetti, G.; Toscano, G.; Graf, D.; Fey, M.; Henrici, A.; Ziebart, V.; Heitmann, B.; Grabner, H.; Wegner, J.D.; Sigel, R.K.O.; Wilhelm, D.,

  2023.

  Deconvolution of 1D NMR spectra : a deep learning-based approach.

  Journal of Magnetic Resonance.

  347(107357).

  Available from: https://doi.org/10.1016/j.jmr.2022.107357

• Te, Yiea-Funk; Wieland, Michèle; Frey, Martin; Pyatigorskaya, Asya; Schiffer, Penny; Grabner, Helmut,

  2023.

  Making it into a successful series a funding : an analysis of Crunchbase and LinkedIn data.

  The Journal of Finance and Data Science.

  9(100099).

  Available from: https://doi.org/10.1016/j.jfds.2023.100099

• Stadelmann, Thilo; Keuzenkamp, Julian; Grabner, Helmut; Würsch, Christoph,

  2021.

  The AI-Atlas : didactics for teaching AI and machine learning on-site, online, and hybrid.

  Education Sciences.

  11(7), pp. 318.

  Available from: https://doi.org/10.3390/educsci11070318

• Schmid, Nicolas; Bruderer, Simon; Fischetti, Giulia; Paruzzo, Federico; Toscano, Giuseppe; Graf, Dominik; Fey, Michael; Ziebart, Volker; Henrici, Andreas; Grabner, Helmut; Wegner, Jan Dirk; Sigel, Roland K.O.; Heitmann, Björn; Wilhelm, Dirk,

  2023.

  Deconvolution of NMR spectra : a deep learning-based approach [poster].

  In:

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

  ZHAW Zürcher Hochschule für Angewandte Wissenschaften.

  Available from: https://doi.org/10.21256/zhaw-27429

• Te, Yiea-Funk; Wieland, Michèle; Frey, Martin; Grabner, Helmut,

  2023.

  Mitigating discriminatory biases in success prediction models for venture capitals [paper].

  In:

  2023 10th IEEE Swiss Conference on Data Science (SDS).

  10th IEEE Swiss Conference on Data Science (SDS), Zurich, Switzerland, 22-23 June 2023.

  IEEE.

  pp. 26-33.

  Available from: https://doi.org/10.1109/SDS57534.2023.00011

• Schmid, Nicolas; Bruderer, Simon; Fischetti, Giulia; Paruzzo, Federico; Toscano, Giuseppe; Graf, Dominik; Fey, Michael; Henrici, Andreas; Grabner, Helmut; Wegner, Jan Dirk; Sigel, Roland K. O.; Heitmann, Björn; Wilhelm, Dirk,

  2022.

  Deconvolution of NMR spectra : a deep learning-based approach [poster].

  In:

  Prisner, Thomas, ed.,

  EUROMAR 2022 Abstractbook.

  European Conference on Magnetic Resonance (EUROMAR), Utrecht, The Netherlands, 10-14 July 2022.

  ZHAW Zürcher Hochschule für Angewandte Wissenschaften.

  pp. 242.

  Available from: https://doi.org/10.21256/zhaw-27336

• Koller, Thomas; Grabner, Helmut,

  2022.

  Who wants to be a click-millionaire? : on the influence of thumbnails and captions [paper].

  In:

  2022 26th International Conference on Pattern Recognition (ICPR).

  26th International Conference on Pattern Recognition (ICPR), Montréal, Canada, 21-25 August 2022.

  IEEE.

  pp. 629-635.

  Available from: https://doi.org/10.1109/ICPR56361.2022.9956202

• Weber, Maurice; Renggli, Cedric; Grabner, Helmut; Zhang, Ce,

  2020.

  Observer dependent lossy image compression [paper].

  In:

  42nd German Conference on Pattern Recognition (DAGM-GCPR), virtual, 28 September - 1 October 2020.

  Available from: https://doi.org/10.48550/arXiv.1910.03472

• Inan, Berkay; Cernak, Milos; Grabner, Helmut; Tukuljac, Helena Peic; Pena, Rodrigo C. G.; Ricaud, Benjamin,

  2019.

  Evaluating audiovisual source separation in the context of video conferencing [paper].

  In:

  Proceedings Interspeech 2019.

  Interspeech 2019, Graz, Austria, 15-19 September 2019.

  International Speech Communication Association (ISCA).

  pp. 4579-4583.

  Available from: https://doi.org/10.21437/Interspeech.2019-2671

• Bödi, Linda Helen; Grabner, Helmut,

  2020.

  Learning to ignore : fair and task independent representations.

  ZHAW Zürcher Hochschule für Angewandte Wissenschaften.

  Available from: https://doi.org/10.21256/zhaw-21602

• Lechner, Verena; Weber, Wibke; Grabner, Helmut; Obrist, Dario,

  2022.

  What makes an image worth a like on Instagram? : a computer vision and visual communication approach to the use of images in corporate and science communication of universities.

  In:

  SACM Annual Conference / SGKM Jahrestagung 2022, Zürich, Schweiz, 21.-22. April 2022.

Publications before appointment at the ZHAW

TEST OF TIME AWARD: Koenderink Prize ( www.thecvf.com ) At the European Conference on Computer Vision (ECCV) 2018 in Munich the paper "H. Grabner, Ch. Leistner, and H. Bischof. Semi-supervised On-line Boosting for Robust Tracking" was awarded the prestigious Koenderink Prize, given to `fundamental contributions in computer vision that stood the test of time'.

Google Scholar: scholar.google.com/citations

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