Find Academic Supervisors

• Computer graphics
• Geometry processing
• Computer-aided geometric design
• +6 more

Leif Kobbelt is a Full Professor of Computer Science and Head of the Visual Computing Institute at RWTH Aachen University . He previously held academic positions at the Max-Planck-Institute for Computer Science, University of Erlangen-Nürnberg, and University of Wisconsin-Madison. Diploma in Computer Science (1992), Karlsruhe Institute of Technology PhD in Computer Science (1994), Karlsruhe Institute of Technology His research focuses on computer graphics and geometry processing , with specific interests in 3D reconstruction, quad mesh generation, real-time rendering, and geometric modeling algorithms. He has pioneered techniques for efficient mesh processing, anisotropic geodesic computation, and procedural facade visualization. Recent publications analyze nonlinear constraints in geometric modeling, quad layout optimization, and real-time rendering techniques. Key themes include mesh parameterization, multiresolution analysis, and computational geometry for interactive applications. Scientific recognitions include: 2014 Gottfried Wilhelm Leibniz Prize (Germany's most prestigious research award) 2013 ERC Advanced Grant (ACROSS project) 2008 Eurographics Fellow 2004 Eurographics Outstanding Technical Contribution Award 2000 Heinz-Maier-Leibnitz Award He leads major research initiatives like the excellence clusters UMIC (€40M) and AICES (€15M), and the ERC-funded ACROSS project (€2.5M, 2014-2018). He serves as principal investigator and reviewer for international journals and organizations.

• Visual Interfaces
• Interactive Data Exploration
• Human-Computer Interaction
• +3 more

Manuela Waldner is an Assistant Professor (tenure track) at TU Wien's Department of Computer Graphics and Visualization. She leads research in visual interfaces for exploring large-scale data, focusing on human-computer interaction and attention guidance in complex visualizations. Her work spans academic roles including Visualization Group membership and PhD Program Visual Heritage involvement. Research interests include: Interactive data exploration Guided visual attention mechanisms Emerging display environments (VR, multi-display systems) Publications emphasize practical applications of visualization techniques in domains like geographic data, medical imaging, and collaborative analytics. Notable projects include weBIGeo (geographic visualization) and Deskollage (visual information foraging). Awards include the Best Paper Award at EuroVA 2024 . Teaching roles include courses on Information Visualization , Computer Graphics , and Visual Computing . Active in academic service through program committees and editorial roles.

• Integrated Circuits
• Quantum Computing
• mm-Wave Transmission
• +3 more

Harald Pretl is a Professor at the Department of Integrated Circuits within the Institute for Integrated Circuits and Quantum Computing at Johannes Kepler University Linz (JKU). Holding the title Univ.-Prof., he maintains active research leadership with current projects extending through 2029 and 107 documented research outputs including patents, articles, and conference proceedings. His research spans integrated circuits, quantum computing, mm-wave transmission, biomedical sensing, and open-source EDA tools. He specializes in high-frequency circuit design, ultra-low-power biomedical sensors, and educational applications of open-source design methodologies for analog/mixed-signal IC development. Recent work demonstrates cross-disciplinary innovation bridging engineering, neuroscience, and artistic expression. Recent publications reveal strong emphasis on practical implementation challenges: THz transmitter efficiency, brain-computer interface applications, ADC performance metrics, and open-source layout automation. These works collectively advance wireless communication systems, biomedical instrumentation, and accessible semiconductor design education through open-toolchain development. Prof. Pretl has supervised 3 students and actively promotes open-source EDA adoption through educational initiatives. His funded projects include Sub-blocks generators for NSSAR ADC (2025-2029), Open Parasitic Extraction for KLayout, and United Micro Technology collaborations, demonstrating sustained industry engagement. He co-leads the JKU LIT - SAL Intelligent Wireless Systems Lab (IWS Lab) and contributes to the High-Performance Integrated Quantum Computing project. Current activities include 42 documented presentations such as 'Using Open-Source EDA Tools in Hands-On IC Design Education' (2025) and 'Recent Developments in Ultra-Low-Power Biomedical Sensing' (2025), reflecting his dual focus on research innovation and pedagogical advancement.

Thomas W. RepsView profile

Professor

• Programming languages
• Software engineering
• Static program analysis
• +5 more

Thomas W. Reps is a Professor in the Department of Computer Science at the University of Wisconsin, holding the position since 1985. He has served as President and Co-founder of GrammaTech, Inc. since 1988, and held visiting roles including Guest Professor at the University of Paris 7 (2007-08), Visiting Researcher at CNR in Pisa, Italy (2000-01), and Guest Professor at the University of Copenhagen (1993-94). He previously served as Associate Chairman of the Computer Sciences Department at Wisconsin (1990-93) and held postdoctoral roles at Cornell University and INRIA. Reps' research spans programming languages, software engineering, and computer security, with a focus on static program analysis, machine-code analysis, and program slicing. His work in model checking, software maintenance, and analysis techniques for information security has significantly impacted the field of computer science. 2017 ACM SIGPLAN Programming Languages Achievement Award 2015 WARF Named Professorship 2005 ACM Fellow 2000 Guggenheim Fellowship 1986 NSF Presidential Young Investigator Award Reps' publications highlight advancements in interprocedural dataflow analysis, weighted pushdown systems, and symbolic computation. His work bridges theoretical foundations with practical applications in software verification and security, creating tools that have shaped modern program analysis techniques. He has collaborated extensively with researchers like Somesh Jha, Mooly Sagiv, and Gogul Balakrishnan across institutions in Europe and the U.S.

• Natural Language Processing
• Machine Learning
• Data Mining
• +7 more

Pedro Henrique Luz de Araujo is a member of the Faculty of Computer Science affiliated with the Research Group Data Mining and Machine Learning . His work focuses on Natural Language Processing , Language Modeling , and Behavioral Learning , particularly in Brazilian legal text domains. He has contributed to advancements in named entity recognition , hate speech detection , and specification-driven AI systems . Active in 2022-2025 with publications in PLoS ONE and top NLP conferences Organized the KONVENS 2024 conference Research emphasizes LLM calibration , multimodal classification , and domain-specific datasets His recent publications show expertise in large language models (2025: persona effects; 2024: specification overfitting, text-guided image clustering), NER techniques (2024), and legal document processing (2023: multimodal classification; 2020: VICTOR dataset, LeNER-Br).

Jules WulmsView profile

Researcher

• Computational Geometry
• Algorithm Design
• Graph Theory
• +3 more

Jules Wulms is a researcher at the Institute of Logic and Computation, Vienna University of Technology (TU Wien), within the Faculty of Informatics. His work focuses on computational geometry, algorithm design, and visualization techniques. He has contributed to areas such as graph drawing, geometric algorithms, and dynamic data structures. Wulms' research emphasizes theoretical foundations with applications in spatial data analysis and information visualization. His academic contributions include studies on planar graph modifications, dynamic point labeling, and reconfiguration problems in modular robotics. Wulms collaborates frequently with institutions like TU Wien and international conferences, publishing in venues like the Journal of Computational Geometry and ACM Transactions on Spatial Algorithms and Systems. His doctoral thesis, available online, further details his foundational work in algorithmic complexity and geometric computing. Key themes in his publications include optimizing geometric structures (e.g., minimizing corners in grids), developing efficient algorithms for dynamic datasets, and exploring stability in kinetic frameworks. While no specific awards are listed, his extensive publication record highlights his impactful contributions to theoretical computer science and computational geometry.

Yifan HuView profile

Professor

• AI
• Machine Learning
• Natural Language Processing
• +4 more

Yifan Hu is a Professor of Practice at Northeastern University, specializing in AI/ML/NLP and Information Visualization. He held senior roles at Amazon (Senior Manager of Applied Science, 2023-2024) and Yahoo! Research (Senior Director, 2014-2023), leading teams in AI-driven projects. Earlier, he contributed to AT&T Labs, Wolfram Research, and Daresbury Laboratory. His research focuses on graph visualization, machine learning, and data science applications. Research interests include advanced visualization techniques (e.g., SmartGD framework), AI moderation systems, graph algorithms, and federated learning fairness. He has pioneered methods for graph layout optimization, dynamic data visualization, and adversarial NLP defenses. Notable achievements include winning the 2017 IEEE ICDM 10-Year Highest-Impact Paper Award for work on collaborative filtering. He currently teaches Data Mining (CS 6220) and Machine Learning (CS 6140) at Northeastern, emphasizing practical applications of AI. Labs/Projects: Actively develops visualization tools like SmartGD and DeepGD , exploring interdisciplinary applications in healthcare, cybersecurity, and large-scale data analysis. His work bridges theoretical advancements with industrial-scale implementations.

Silvia MikschView profile

Professor

• Visualization & Visual Analytics
• Information Visualization
• Interaction Design
• +8 more

Silvia Miksch is a Full Professor of Visual Analytics at the Vienna University of Technology (TU Wien), leading the Research Unit Visual Analytics (E193-07) and coordinating the Research Focus on Visual Computing and Human-Centered Technology. She holds a PhD from TU Wien and has held academic roles at institutions like Stanford University (FWF postdoc), Danube University Krems (2006–2010 as University Professor), and TU Wien. Her research focuses on visualization, visual analytics, interaction design, and temporal data analysis with applications in medical informatics, process engineering, and cultural heritage. Education: Master of Social and Economic Science (University of Vienna, 1987), PhD (TU Wien, 1990). Former roles include Chair of the Austrian Society for Artificial Intelligence (ÖGAI) and leadership in EU projects like VALCRI and KAVA-Time. She has authored over 200 publications and received awards such as the IEEE VGTC Visualization Technical Award (2023) and induction into the IEEE VGTC Visualization Academy (2020). Research interests include knowledge-assisted visual analytics, task-driven guidance systems, and spatiotemporal data exploration. She oversees the Laura Bassi Centre of Expertise 'CVAST' and advises numerous PhD and master’s students. Her work bridges theory and practice, with notable projects like the Marvel Cinematic Universe infographic (GD 2019 Best Creative Challenge) and Game of Thrones character networks (GD 2018 Third Prize). Key Awards: Best Paper Award at vis4dh 2019, IEEE VGTC Technical Award 2023 Editorial Roles: Associate Editor of Transactions on Visualization and Computer Graphics (2011–2015), Editorial Board of Journal of Biomedical Informatics (2012–2020) Leadership: Chair of EuroVis Steering Committee (2023–2027), Member of VIS Executive Committee (2015–2020)

Roman KernView profile

Associate Professor

• Natural Language Processing
• Machine Learning
• Data Science
• +7 more

Assoc. Prof. Roman Kern is affiliated with the Institute of Machine Learning and Neural Computation at Graz University of Technology and serves as Chief Scientific Officer at Know-Center Research GmbH , a competence center for Big Data analytics. His research bridges natural language processing, data science, and machine learning with a focus on causal inference and discovery, applied to scientific publication mining, intelligent transportation systems, and smart production. Research Interests : Causal inference, NLP, data science, trustworthy AI, knowledge discovery, and interdisciplinary applications. Projects : VanillaFlow (sustainable electrolytes for batteries), REWAI (causal discovery in textile manufacturing), and EPN-2024-RI (planetary science infrastructure). Teaching : Courses include Knowledge Discovery, Natural Language Processing, and Introduction to Scientific Working at TU Graz. His recent publications analyze causal relationships in semiconductor manufacturing, differential privacy, and LLM applications in healthcare and environmental monitoring. Roman Kern actively mentors students through thesis topics on causality, LLMs, and data privacy frameworks, while leading applied research projects with industry partners.

• Textile Interfaces
• Human-Computer Interaction
• Tangible Media
• +2 more

Kathrin Probst is Professor at University of Applied Sciences Upper Austria, Hagenberg Campus, focusing on human-computer interaction and tangible interfaces. Her research develops smart textiles, sustainable fashion technologies, and novel interaction paradigms through projects like BAMBI and Active Office. Work explores the materiality of interaction, with recent investigations into textile signifiers, traceability systems for fashion, and biodesign approaches. Research demonstrates strong experimental design focus and attention to material properties. Publications advance understanding of textile-based interfaces, ergonomic workplace design, and unconventional interaction methods. Work contributes to both technical implementation and design theory. Awards include: ACM Europe Council Best Paper Award (2018) UIST Best Paper Award (2018) Organizes the Expanded conference on interactive surfaces. Research collaborations include University of Calgary and National University of Singapore.

Gabriele TraugottView profile

Senior Lecturer

• Human-Computer Interaction
• Tangible Interfaces
• Textile Technology
• +2 more

Gabriele Traugott is Senior Lecturer at University of Applied Sciences Upper Austria, Hagenberg Campus, specializing in human-computer interaction and digital media. She researches tangible interfaces, smart textiles, and workplace technology through projects like BAMBI (Biodiversity Monitoring) and Active Office. Research explores the intersection of physical materials and digital interaction, with focus on textile interfaces, ergonomic workplace design, and sustainable technology. Recent work develops traceability systems for fashion and participatory data physicalization techniques. Publications advance understanding of haptic interfaces, sensor technologies, and unconventional interaction paradigms. Work demonstrates strong design focus and experimental prototyping approach. Awards include: ACM Europe Council Best Paper Award (2018) UIST Best Paper Award (2018) Leads technology education initiatives and organizes academic workshops. Research collaborations include National University of Singapore and University of Calgary.

• Cultural Heritage
• Document Analysis
• Medical Data Analysis
• +5 more

Florian Kleber is a senior scientist at the Computer Vision Lab within the Institute of Visual Computing and Human-Centered Technology at Vienna University of Technology (TU Wien), Austria. His research spans two primary domains: document analysis for cultural heritage preservation and medical data analysis. He has been actively involved in lecturing at TU Wien, particularly in Document Analysis courses, and has served as a substitute member of the Curriculum Commission for Informatics. Dr. Kleber's research focuses on the intersection of computer vision and practical applications. His work in cultural heritage includes multi-spectral acquisition and restoration of ancient manuscripts, development of tools for historical document analysis, and work on writer identification and retrieval systems. In medical data analysis, he has specialized in flow cytometry analysis, particularly for minimal residual disease assessment in acute lymphoblastic leukemia. His research demonstrates a consistent pattern of applying advanced computer vision techniques to solve domain-specific challenges in both humanities and medical fields. His recent publications reveal a strong trend toward synthetic data generation for training document analysis systems, self-supervised learning approaches for writer retrieval, and explainable AI techniques for medical data analysis. The publications show increasing sophistication in transformer-based architectures applied to both document analysis and medical imaging domains. His work bridges theoretical computer vision advances with practical applications in cultural heritage institutions and medical settings. Dr. Kleber has supervised multiple diploma theses at TU Wien, including work on automated analysis of herbarium collections, transparency techniques for neural networks, synthetic data for document analysis, and physical layout analysis of newspaper images. He has been involved in numerous research projects including the Vienna City Library poster collection analysis, digitization of museum holdings in Lower Austria, and the AutoFlow project for medical data analysis. His laboratory work centers around the Computer Vision Lab (E193-01) at TU Wien, where he collaborates on projects involving document image analysis, cultural heritage preservation, and medical data processing. His team has developed tools for manuscript analysis, document reconstruction, and flow cytometry data interpretation, often in collaboration with cultural institutions and medical facilities.

Renata RaidouView profile

Associate Professor

• Medical Visualization
• Visual Analytics
• Uncertainty Visualization
• +3 more

Renata Raidou is an Associate Professor in Biomedical Visualization and Visual Analytics at the Research Unit of Computer Graphics, Institute of Visual Computing & Human-Centered Technology, TU Wien, Austria. She previously held positions at the University of Groningen and TU Wien as a postdoc. Her research focuses on medical visualization, uncertainty visualization, and data physicalization for healthcare applications. Raidou has received prestigious awards including the Dirk Bartz Prize (2017) and EuroVis Young Researcher Award (2022). She coordinates TU Wien's BSc in Digital Health and MSc in Medical Informatics. Education: PhD in Medical Visualization (Eindhoven University of Technology, 2017), MSc in Biomedical Engineering (TU Delft), Diploma in Electrical and Computer Engineering (NTUA). Professional Roles: Editorial Board member of Computer & Graphics , Steering Committee member of EG VCBM, and member of EASAC's AI in Healthcare working group. Research Interests: Medical visualization strategies for P4 medicine, anatomical edutainment through physicalization, and uncertainty-aware visual analytics in radiotherapy. Her work bridges visual computing, machine learning, and medical applications, emphasizing clinical decision support and public health education. Awards: Over 10 awards including Best Paper recognitions at IEEE Vis and EuroVis, and the EuroVis Best PhD Award. Her contributions span visualizing anatomical variability, ensemble data exploration, and interactive medical training tools. Grants & Projects: Leads the Health Virtual Twins project (2024–2028) for personalized stroke management. Active in interdisciplinary collaborations, including the Shonan Meeting on Formalizing Biological Visualization. Labs/Teams: Head of the Visualization Group at TU Wien, developing tools like Vologram (holographic medical data physicalization) and Slice and Dice anatomical crafts. Collaborates on edutainment systems and AI-driven healthcare visualization.

Renata Georgia RaidouView profile

Associate Professor

• Medical Visualization
• Visual Analytics
• Uncertainty Visualization
• +4 more

Renata Georgia Raidou is an Associate Professor in Biomedical Visualization and Visual Analytics at TU Wien's Institute of Visual Computing & Human-Centered Technology. She leads the Research Unit of Computer Graphics and serves as Curriculum Coordinator for the Bachelor in Informatics (Specialization Digital Health) and Master in Medical Informatics programs. She holds prestigious awards including the EuroVis Young Researcher Award (2022), Best PhD Award (2018), and Dirk Bartz Prize (2017). Her research focuses on medical applications of Visual Analytics, with emphasis on uncertainty visualization, comparative visualization, and anatomical edutainment through physicalizations. She explores how visual tools can enhance decision-making in precision medicine, particularly in radiotherapy and cancer treatment. Her work bridges visualization, machine learning, and image processing to address clinical challenges. Raidou's recent projects include developing predictive visual analytics systems for radiotherapy planning and creating tactile physicalizations for anatomy education. She actively contributes to the field through editorial roles (Associate Editor of Computer & Graphics ) and policy advising via EASAC's 'AI in Healthcare' initiatives. Key Projects: Health Virtual Twins for Stroke Management, PREVIS for Radiotherapy Decision Support, Pelvis Runner for Anatomical Variability Analysis Teaching: Courses on Medical Visualization, Data Analytics in Health Sciences, and Visual Computing Grants: European Commission-funded projects (2024–2028) Her lab develops interdisciplinary tools for clinicians, researchers, and educators, emphasizing both technical innovation and real-world impact.

Martin IlcikView profile

Researcher

• Procedural Modeling
• Shape Grammars
• Layout Generation
• +6 more

Martin Ilcik is a Researcher at the Department of Computer Graphics within the Faculty of Informatics at Vienna University of Technology (TU Wien). His work focuses on procedural modeling, shape grammars, and related computer graphics techniques. He serves as a Scientist in the Rendering and Modeling workgroup and has been actively involved in research projects since 2008, including GameWorld, PAMINA, Wohnen 4.0, AgroEco, and currently Room Imageer and GreenFDT projects. Ilcik's research interests prominently feature procedural modeling techniques, with specializations in shape grammars, layout generation, semantic modeling, 3D reconstruction, and music generation. His work bridges computer science with practical applications in architecture, urban planning, and creative arts. He has made significant contributions to layer-based procedural design of building facades and collaborative modeling systems. His publication record spans from 2007 to 2024, with a strong focus on procedural modeling techniques. The research trajectory shows evolution from flow visualization to sophisticated procedural modeling systems, with increasing emphasis on shape grammars, collaborative design, and applications in architecture and music generation. His work demonstrates consistent innovation in making procedural modeling more intuitive and accessible. VC CultTech Hackathon winner category 'Vienna State Opera challenge' (2017) INiTS Award 2016 Ilcik has supervised student research, including Lukas Eibensteiner's 2021 Diploma Thesis on polyphonic music composition with grammars. He has been instrumental in organizing the Central European Seminar on Computer Graphics (CESCG) since 2008, which has grown into an important annual event for undergraduate students in computer graphics, vision, and visual computing across Central Europe. His community work includes creating educational resources and organizing EXPO events and Academy Videos through CESCG. He leads research in the Rendering and Modeling workgroup at TU Wien's Computer Graphics department, focusing on developing innovative procedural modeling techniques with applications in architecture, urban planning, and creative domains. His current projects (Room Imageer and GreenFDT) continue his longstanding interest in practical applications of procedural modeling techniques.