FH-Prof. Priv.-Doz. Dipl.-Ing. Mag. Dr. Matthias Zeppelzauer

  • Head of
    Media Computing Research Group
    Institute of Creative\Media/Technologies
  • Department of Media and Digital Technologies
Location: A - Campus-Platz 1
M: +43/676/847 228 652

Study programmes

  • Data Science and Business Analytics (BA)
  • Data Intelligence (MA)
  • Creative Computing (BA)
  • Media Technology (BA)


  • Computer Science and Security
  • Media and Digital Technologies

Research Vision

“Performing innovative human-centered research on AI across disciplines to serve the social good.”

Matthias Zeppelzauer is a professor for computer vision, multimedia retrieval and machine learning with a special focus on human-centered approaches. In his research he focuses on the development of methods for the retrieval of semantically meaningful information from different types of media including visual and acoustic data, 3D data, (medical) time series data, textual data as well as multimodal data, e.g. from social media platforms. Cross-sectional topics in his research represent interactive machine learning (human in the loop learning) and explainable machine learning. He holds habilitation from TU Wien and has co-authored more than 90 publications.
Full List of Publications

Research Interests

  • Human-Centered and Trustworthy AI
  • Computer Vision and Image Understanding
  • Content-based Audio, Image and Video Retrieval
  • Multimodal Media Retrieval and Learning
  • Environmental Sound Recognition
  • Social Media Analysis
  • Pattern Mining

IMREA - Intelligent Multimodal Real Estate Assessment

Multimodal information extraction and machine learning techniques for the extraction of real estate related attributes and parameters from heterogeneous input data


Evaluation of the accuracy of non-invasive hip joint centre estimation methods for clinical gait analysis in children and adolescents

Plant Monitoring AI

Leveraging machine learning and predictive analytics for early detection of plant stress for the benefit of sustainability in farming

Trading Cultures

An ethnography of international trade fairs for television programs, music and books

ImmBild - Location Assessment by Computer Vision

Location is key – especially when it comes to real estate value. “ImmBild” aims at developing a new method for estimating property value using computer vision of satellite data.

InfraBase - Automatic Building Footprint Segmentation

The project deals with the fully automatic analysis of satellite imagery. The goal is to extract a pixel-accurate segmentation of building roofs to generate a rich meta-data layer.

SoniTalk - an Open Protocol for Data-over-Sound

While interconnectedness amongst our devices increases rapidly, SoniTalk aims at developing an open protocol for ultrasonic device communication that fully preserves the privacy of the user.

ImmoAge - Visual Age Prediction of Real Estate

Year of construction, architectural period and architectural style have a significant impact on property prices. New methods of classifying and evaluating real estate have been developed on the basis ...

Pitoti 3D

Italy’s petroglyphs were carved into rock faces by prehistoric cultures. This project sets out to investigate and document the 3D nature of these petroglyphs for the first time.

Selected Publications

Matt, M., Zeppelzauer, M., & Waldner, M. (2024). cVIL: Class-Centric Visual Interactive Labeling. Proceedings of the 15th International EuroVis Workshop on Visual Analytics (EuroVA). 15th International EuroVis Workshop on Visual Analytics (EuroVA), Odense, Denmark.
Slijepcevic, D., Horst, F., Lapuschkin, S., Horsak, B., Raberger, A.-M., Kranzl, A., Samek, W., Breitender, C., Schöllhorn, W., & Zeppelzauer, M. (2022). Explaining Machine Learning Models for Clinical Gait Analysis. ACM Transactions on Computing for Healthcare, 3(2), 14:1-14:27.
Baumhauer, T., Schöttele, P., & Zeppelzauer, M. (2022). Machine Unlearning: Linear Filtration for Logit-based Classifiers. Journal on Machine Learning, 111(1), 3203–3226.
Beckmann, Rafael, Blaga, C., El-Assady, M., Zeppelzauer, M., & Bernard, J. (2022). Interactive Visual Explanation of Incremental Data Labeling. EuroVis Workshop on Visual Analytics (EuroVA), 6.
Baumhauer, T., Slijepcevic, D., & Zeppelzauer, M. (2022). Bounded logit attention: Learning to explain image classifiers. NeurIPS 2022 Workshop: All Things Attention: Bridging Different Perspectives on Attention, New Orleans, USA.
Slijepčević, D., Henzl, M., Klausner, L. D., Dam, T., Kieseberg, P., & Zeppelzauer, M. (2021). k‑Anonymity in Practice: How Generalisation and Suppression Affect Machine Learning Classifiers. Computers & Security, 111, 19.
Kirchknopf, A., Slijepcevic, D., & Zeppelzauer, M. (2021). Multimodal Detection of Information Disorder from Social Media. International Conference on Content-Based Multimedia Indexing (CBMI), 4.
Bernard, J., Hutter, M., Zeppelzauer, M., Sedlmair, M., & Munzner, T. (2021). ProSeCo: Visual analysis of class separation measures and dataset characteristics. Computers & Graphics, 96, 48–60.
Bernard, Jürgen, Hutter, M., Sedlmair, M., Zeppelzauer, Matthias, & Munzner, Tamara. (2021). A Taxonomy of Property Measures to Unify Active Learning and Human-centered Approaches to Data Labeling. ACM Transactions on Interactive Intelligent Systems (TiiS), 11(3–4), 1–42.
Zielinski, B., Lipinski, M., Juda, M., Zeppelzauer, Matthias, & Dlotko, Pawel. (2021). Persistence Codebooks for Topological Data Analysis. Journal of Artificial Intelligence Review, 54, 1969–2009.
Horsak, B., Slijepcevic, D., Raberger, A.-M., Schwab, C., Worisch, M., & Zeppelzauer, M. (2020). GaitRec, a large-scale ground reaction force dataset of healthy and impaired gait. Scientific Data, 7:143(1), 1–8.
Bernard, Jürgen, Hutter, M., Sedlmair, M., Zeppelzauer, Matthias, & Munzner, Tamara. (2019). A taxonomy of property measures to support the explainability of the interactive data labeling process. ACM Transactions on Interactive Intelligent Systems (TiiS), Submitted.
Zielinski, B., Lipinski, Michal, Juda, M., Zeppelzauer, M., & Dlotko, Pawel. (2019). Persistence Bag-of-Words for Topological Data Analysis. Proceedings of the International Joint Conference on Artificial Intelligence 2019, 6.
Wagner, M., Slijepcevic, D., Horsak, B., Rind, A., Zeppelzauer, M., & Aigner, W. (2018). KAVAGait: Knowledge-Assisted Visual Analytics for Clinical Gait Analysis. IEEE Transactions on Visualization and Computer Graphics (TVCG), 25(3), 1528–1542.
Slijepcevic, D., Zeppelzauer, M., Raberger, A.-M., Schwab, C., Schuller, M., Baca, A., Breiteneder, C., & Horsak, B. (2018). Automatic Classification of Functional Gait Disorders. IEEE Journal of Biomedical and Health Informatics, 5(22), 1653–1661.
Zeppelzauer, M., Despotovic, M., Sakeena, M., Koch, D., & Döller, M. (2018). Automatic Prediction of Building Age from Photographs. Proceedings of the ACM International Conference on Multimedia Retrieval (ICMR "18), 126–134.
Bernard, J., Zeppelzauer, M., Sedlmair, M., & Aigner, W. (2018). VIAL – A Unified Process for Visual-Interactive Labeling. The Visual Computer, 34(1189), 16.
Bernard, J., Zeppelzauer, M., Lehmann, M., Müller, M., & Sedlmair, M. (2018). Towards User-Centered Active Learning Algorithms. Computer Graphics Forum, 37, 121–132.
Zeppelzauer, M., Zielinski, B., Juda, M., & Seidl, M. (2018). A Study on Topological Descriptors for the Analysis of 3D Surface Texture. Journal on Computer Vision and Image Understanding (CVIU), 167, 74–88.
Bernard, Jürgen, Hutter, M., Zeppelzauer, M., Fellner, D., & Sedlmair, M. (2017). Comparing Visual-Interactive Labeling with Active Learning: An Experimental Study. IEEE Transactions on Visualization and Computer Graphics (TVCG), 24(1).
Zeppelzauer, M., & Schopfhauser, D. (2016). Multimodal classification of events in social media. Image and Vision Computing.
Zaharieva, M., Del Fabro, M., & Zeppelzauer, M. (2015). Cross-Platform Social Event Detection. IEEE Multimedia, 22(3), 14.
Salvador, A., Zeppelzauer, M., Manchón-Vizuente, D., Calafell, A., & Giró-i-Nieto, X. (2015, April 28). Cultural Event Recognition with Visual ConvNets and Temporal Models. Proceedings of the CVPR Workshop ChaLearn Looking at People 2015. Computer Vision and Pattern Recognition (CVPR), Boston, Massachusetts, United States.
Zaharieva, M., Zeppelzauer, M., Del Fabro, M., & Schopfhauser, D. (2015, March 24). Social Event Mining in Large Photo Collections. Proceedings of the International Conference on Multimedia Retrieval. ACM International Conference on Multimedia Retrieval, Shanghai, China.
Stöger, A., Heimann, G., Zeppelzauer, M., Ganswindt, A., Hensman, S., & Charlton, B. (2012). Visualizing Sound Emission of Elephant Vocalizations: Evidence for Two Rumble Production Types. Plos One, 7(11:e48907).
Mitrović, D., Zeppelzauer, M., & Breiteneder, C. (2010). Features for Content-Based Audio Retrieval. In Advances in Computers (Vol. 78, pp. 71–150). Burlington: Academic Press.

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