Prof. Dr. Helmut Grabner

Prof. Dr. Helmut Grabner
ZHAW
School of Engineering
Forschungsschwerpunkt Data Analysis and Statistics
Technikumstrasse 81
8400 Winterthur
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
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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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Lechner, Verena; Weber, Wibke; Grabner, Helmut; Obrist, Dario,
2022.
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