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• Computer Science
• Multimedia Systems
• Medical Informatics
• +2 more

Manfred Jürgen Primus is affiliated with the Faculty of Technical Sciences at the University of Klagenfurt , specifically within the Institute of Information Technology . His research focuses on Computer Science and Medical Informatics , particularly in Endoscopic Video Analysis and Human-Computer Interaction . Research themes: Medical video datasets, smoke detection in surgical footage, collaborative video retrieval systems Key technologies: Computer vision, machine learning, real-time image processing Applications: Surgical workflow optimization, medical education support Recent publications (2016-2018) demonstrate his work at the intersection of multimedia systems and healthcare, including advanced video analysis tools for laparoscopic surgery and endoscopic procedures. Despite a lack of explicit awards or student advisement records in the provided data, his contributions to Medical Imaging and Human-Computer Interaction are evident through technical publications and interdisciplinary collaborations.

• Robotics
• Multi-Agent Systems
• Computer Science
• +3 more

Konstantin Warneke is a Senior Researcher at the Department of Computer Science, Alpen-Adria-Universität Klagenfurt. His work focuses on robotics, multi-agent systems, and automation. While his formal teaching role at the university has concluded, he remains active in research projects such as 'Heterogeneous multi-agent localization' and 'Wind Turbine Blade Inspection Using Multimedia Drones,' funded by agencies like FFG and OeAD. His research spans radar technology, swarm intelligence, and edge-cloud computing, with recent publications in journals like Physical Review E and IEEE Sensors Journal. He collaborates on interdisciplinary projects addressing sustainability, automated systems, and media studies. Notably, his work emphasizes applied research with industry partners such as Infineon Technologies and NOI AG, contributing to practical innovations in fields like agricultural monitoring and renewable energy.

• Audio Signal Processing
• Music Information Retrieval
• Deep Learning
• +3 more

Alexander Schindler is an External Lecturer at the Department of Information Systems Engineering at Technische Universität Wien. His research focuses on audio signal processing, music information retrieval, and deep learning applications in multimodal analysis. He coordinates the approacH project (2010–2013) funded by the European Commission, exploring audio-visual search engines. His academic background includes a Dipl.-Ing. in Technical Engineering and a Dr.techn. from TU Wien. Key research areas include acoustic scene classification, deepfake detection, and music video analysis. He has supervised students on topics like bird song identification and machine outage prediction. Notable publications span from unsupervised cross-modal learning (2020) to multi-modal MIR frameworks (2019). He holds a Bakk.techn. and advanced technical qualifications. Recent work includes advancements in deepfake audio detection (2025) and audio-visual surveillance systems (2024). His projects bridge theoretical research with practical applications in forensic analysis and industrial predictive maintenance. He contributes to international conferences like ACM SAC and DCASE, focusing on neural network architectures for audio analysis.

• Multimedia Retrieval
• Computer Vision
• Machine Learning
• +2 more

Matthias Zeppelzauer is a Lecturer at TU Wien's Faculty of Engineering and Informatics, affiliated with the Visual Analytics group (E193-07). His research portfolio spans multimedia retrieval systems , biomedical signal analysis , and visual interactive machine learning at the intersection of human-centered technology and computer vision. Research domains include: Video content analysis for ecological/medical applications Deep learning for physiological signal interpretation Topological methods for 3D surface analysis Supervised works include doctoral theses on human gait analysis using ML and visual labeling frameworks. Funded projects address unusual sequence detection in video corpora (WWTF) and elephant vocalization analysis (FWF).

Georg PölzlbauerView profile

Researcher

• Machine Learning
• Data Visualization
• Artificial Intelligence
• +3 more

Georg Pölzlbauer is a researcher affiliated with the Department of Information and Software Engineering at Vienna University of Technology (TU Wien). His work focuses on machine learning, data visualization, and artificial intelligence, particularly leveraging self-organizing maps (SOM) for exploratory data analysis. He holds a Dipl.-Ing. (Diploma in Engineering) and a Dr.techn. (Doctor of Technical Sciences). His research emphasizes advanced visualization techniques for SOMs, including vector fields and graph-based methods, applied to diverse domains like petroleum data and political datasets. He has contributed to supervised learning algorithms inspired by self-organization, such as Decision Manifolds. Publications span algorithm design, cluster analysis, and pattern recognition, with applications in music feature extraction and industry-specific data visualization. No scientific awards are explicitly mentioned, but his work reflects sustained engagement with computational and visual data analysis. While no advising or grant information is provided, his affiliation with TU Wien’s research unit suggests active participation in collaborative academic projects.