Associate Professor Renata Georgia Raidou is affiliated with the Institute for Visual Computing and Human-Centered Technology at the Vienna University of Technology (Faculty of Computer Science). Originally from Greece, she earned her B.Sc./M.Sc. in Electrical and Computer Engineering from the National Technical University of Athens , followed by an M.Sc. in Biomedical Engineering from Delft University of Technology and a Ph.D. in Medical Visualization from Eindhoven University of Technology (2017). She has held postdoctoral and faculty roles at TU Wien and the University of Groningen. B.Sc./M.Sc.: Electrical and Computer Engineering, National Technical University of Athens (2005–2010) M.Sc.: Biomedical Engineering, Delft University of Technology (2010–2012) Ph.D.: Medical Visualization, Eindhoven University of Technology (2013–2017) Renata’s research bridges Visualization , Visual Analytics , and Machine Learning in medical contexts, particularly focusing on cancer radiotherapy . Her key areas include: Medical Visualization and Visual Analytics for P4 medicine (personalization, predictiveness, preventiveness, patient participation) Uncertainty Visualization in anatomical variability and biological models Ensemble and Comparative Visualization for large patient cohorts Data Physicalization for anatomical education and public engagement She leads the B.Sc. Informatics (Digital Health specialization) and M.Sc. Medical Informatics programs at TU Wien and contributes to international academic communities through editorial roles (e.g., Associate Editor for Computers & Graphics ) and workshop organization. Scientific Awards Dirk Bartz Prize for Visual Computing in Medicine (2017) EuroVis Best PhD Award (2018) EuroVis Young Researcher Award (2022) Best short paper awards at IEEE Vis (2020), EG VCBM (2022, 2023)
جستجوی استاد راهنمای دانشگاهی
برای مسیر پژوهشیتان، استاد راهنما، استاد دانشگاه و پژوهشگر مناسب را پیدا کنید و با آنها ارتباط بگیرید.
نمایش ۱۶-۳۰ از ۶۴ استاد راهنما
اطلاعات پروفایلها از صفحات عمومی دانشگاهها گرفته شده و ممکن است بهروز نباشد.
Dr. Emma Izquierdo-Verdiguier is a Researcher at the Institute of Geomatics within the University of Natural Resources and Life Sciences, Vienna (BOKU) . She specializes in machine learning algorithms for remote sensing data analysis , with particular focus on land surface phenology and cloud computing environments like Google Earth Engine. Her research spans two decades, including postdoctoral work at the University of Valencia (2017-2018) and University of Twente (2014-2017). She has developed Matlab toolboxes for nonlinear feature extraction and transitioned to JavaScript/Python-based cloud computing solutions for high-resolution image classification. Key methodologies involve kernel methods , multispectral image analysis , and data cube clustering . Recent publications focus on climate change impact assessment (2025), carbon flux modeling (2023), and soil organic carbon monitoring (2025), demonstrating her expertise in Earth Observation and machine learning integration . Her work frequently employs Google Earth Engine for continental-scale analyses. Scientific Awards: 2018 Travel Award sponsored by Remote Sensing 2017 Best Youth Oral Paper Award (X. Wu), ISPRS 2012 2nd Best Paper Award, IEEE IGARSS Student Competition
Lukas Zenk is a Professor of Innovation and Network Research at Danube University Krems, Austria. He serves as Deputy Research Leader and is affiliated with the Department of Knowledge and Communication Management. His work bridges creativity, network analysis, and organizational improvisation, focusing on complex environments and societal challenges. Current research themes: Creativity & Innovation, Social Network Analysis, Applied Improvisation Key projects: Meta-competences for unpredictable situations, Framework of organizational improvisation, TISE sustainability education Methodologies: Agent-based modeling, dynamic network visualization, LEGO Serious Play workshops Zenk's research explores how organizations adapt through improvisation, with publications analyzing network dynamics in post-merger integration, pandemic responses, and sustainability transitions. His work emphasizes transdisciplinary collaboration and complexity literacy in education and policy. Recent studies investigate: Meta-competencies in crisis scenarios Personality traits' impact on pandemic conspiratorial thinking Dynamic models for organizational and societal resilience
Christian Hofstadler is an Associate Professor at the Institute of Construction Management and Economics (2180) at Graz University of Technology. His research focuses on optimizing construction processes, risk management, and sustainable knowledge dissemination, bridging academic rigor with practical implementation in the construction industry. Research Interests : Optimization of construction workflows Improvement of production and logistics processes Opportunity and risk management Lifecycle modeling Productivity analysis Monte Carlo simulations for uncertainty Nonlinear cost/time calculations Digitalization in construction Scientific Awards : Congress Award (2018, shared with colleagues) Recent Activities : Lead editor and chair for multiple symposia (2023-2024) Project manager for Revit revitalization (2024) Research on digital carbon footprint and infrastructure resilience Contributions to BIM planning standards and concrete process optimization
Eva Mayrمشاهده پروفایل
پژوهشگر
Dr. Eva Mayr is a Senior Researcher at the University for Continuing Education Krems, affiliated with the Center for Cultures and Technologies of Collecting . Her work focuses on user-centered design, casual information visualization, digital humanities , and cognitive and media psychology . She leads major projects such as the Bibliotheca Eugeniana Digital (2022–2024) funded by the Austrian Academy of Sciences, and previously directed initiatives like In/Tangible European Heritage (2020–2023, EU-funded) and Uncertainty visualization of cultural heritage data (2017–2020, state-funded). Her research emphasizes innovative visualization techniques for cultural heritage, including methods to handle uncertainty in data and enhance accessibility for casual users. She teaches Usability and Research Methods , and actively contributes to organizations like the OCG IIID . Key contributions include frameworks for integrating cultural data (e.g., InTaVia ) and advancing narrative visualization approaches for historical and biographical data. Publications span journals like Frontiers in Big Data and IEEE Computer Graphics and Applications , with a focus on cultural heritage digitization, set visualization, and mental models in design. Projects often bridge academia and applied contexts, addressing challenges in accessibility, collaboration, and data quality within cultural institutions.
- Art Education
- Gender Studies
- Visual Cultures
- +۴ مورد دیگر
Univ.-Prof. Dr. Jan Guido Grünwald is a Professor of Art Education Didactics at Mozarteum University Salzburg (Innsbruck campus) and Head of the Institute for Equality & Gender Studies. He leads Austria-wide educational research initiatives like ProQ-STEAM, focusing on teacher professionalization in STEAM disciplines. His work bridges art education with gender studies, post-digitality, and youth cultural analysis. Key roles include managing the Braunschweig University of Art’s art teacher training (2019–2020) and teaching at Leibniz Gymnasium Offenbach. Research interests span visual cultures, media didactics, and critical pedagogy, with projects like the Dank Images interdisciplinary network exploring algorithmic imagery. He chairs panels at global events (e.g., Ars Electronica 2023) and publishes widely on topics like TikTok’s social impact, pandemic-era cultural expression, and archaic masculinity in Black Metal aesthetics. Grünwald advocates engaged pedagogy integrating digital tools and youth cultural artifacts into education. Current projects include editing volumes on Dank Images’ role in digital culture and youth subcultures’ educational relevance. He collaborates across six institutions in the ProQ-STEAM consortium, addressing teacher shortages in STEAM fields through qualitative-quantitative research. His work emphasizes inclusive education, sustainability, and leveraging digital innovation while critiquing systemic barriers.
Velitchko Filipov is a PostDoc Researcher at the Institute of Visual Computing & Human-Centered Technology within the Faculty of Informatics at Vienna University of Technology (TU Wien). His work focuses on advancing Information Visualization and Visual Analytics, with a strong specialization in Dynamic Network Analysis. He is currently involved in multiple research projects including ArtVis (2022-2027), SANE (2024-2027), VaCoViCu2 (2023-2027), and SMGV-Esprit (2024-2027), with ArtVis funded by the Austrian Science Fund (FWF). Dr. Filipov completed his doctoral dissertation titled "Networks in time and space: visual analytics of dynamic network representations" at TU Wien in 2024. Prior to that, he completed his Diploma Thesis "Visual exploration and comparison of multiple resume: focus on time and space" at the same institution in 2017. His research centers on creating innovative visual representations and interactive techniques for exploring complex, time-varying networks. These approaches have significant applications in Art History, where understanding the evolution of artistic movements is crucial, and Information Diffusion. His work also benefits computational social sciences and digital humanities by providing tools to uncover patterns within evolving relational data. He has made notable contributions to uncertainty visualization, network physicalization, and the visualization of historical networks. Dr. Filipov's publication record shows a clear progression from foundational work on CV visualization and biographical trajectory mapping toward increasingly sophisticated techniques for dynamic network analysis. His recent work demonstrates a strong focus on making network data tangible through physicalization techniques and on addressing uncertainty in network representations, reflecting the evolving challenges in the visualization field. His scientific achievements have been recognized with several prestigious awards: Best Paper Award at EuroVis 2025 for "NODKANT: Exploring Constructive Network Physicalization" Top Cited Article 2025 in Computer Graphics Forum for "Are We There Yet? A Roadmap of Network Visualization from Surveys to Task Taxonomies" Nominee for Best Dissertation Award 2024 at TU Wien Informatics Best Paper at VIS4DH 2019 Graph Drawing Contest winner in 2019 and 2018 Dr. Filipov actively supervises students, with recent theses including "Dynamic network analysis with centrality measures" (2024) and "Utilizing visual analytics for network exploration in the domain of art history research" (2023). His research is supported by multiple grants, most notably the FWF project ArtVis. He collaborates extensively with researchers across Europe, particularly with Silvia Miksch, Wolfgang Aigner, and Renata Raidou. He is a key member of the Visual Analytics research group at TU Wien, participating in interdisciplinary collaborations that bridge computer science with art history and digital humanities. His work on the ArtVis project exemplifies this approach, developing visualization techniques specifically tailored to address the research challenges faced by art historians studying artistic networks and influence.
Prof. Gerald Steinbauer-Wagner is an Associate Professor at TU Graz's Institute of Software Engineering and Artificial Intelligence. He specializes in autonomous intelligent systems, focusing on decision-making architectures for robots in uncertain environments. His research integrates software engineering, AI, and robotics to develop reliable systems for applications in disaster response, planetary exploration, and industrial automation. Research Interests: Steinbauer-Wagner's work addresses challenges such as robot navigation in unstructured terrains, human-robot collaboration, and trustworthiness in autonomous systems. Key areas include explainable AI, fault diagnosis, and multi-robot coordination. His team explores solutions for off-road robotics, collective perception, and certification of autonomous systems. Recent Projects: Current initiatives include developing autonomous systems for subterranean rescue missions (ROBO-MOLE), optimizing robot localization using machine learning, and creating educational frameworks for AI literacy in schools. His group also contributes to the RoboCup Logistics League and planetary exploration cascades through analog missions like AMADEE-20. Awards & Recognition: No specific awards listed, but his work has been recognized through extensive publications in top venues like IEEE/RSJ IROS, ICRA, and RoboCup symposiums. Lab & Teams: Leads the Autonomous Intelligent Systems (AIS) research group at TU Graz, collaborating with industry partners like the Smart Factory. His team develops integrated robot systems for production, logistics, and disaster response scenarios.
Malte Rolf-Pissarczyk is a Postdoctoral Researcher at the Institute of Biomechanics, Graz University of Technology, Austria. His research focuses on computational modeling of cardiovascular biomechanics, particularly aortic dissection mechanisms and fluid-structure interaction. He holds a PhD in Biomedical Engineering from TU Graz (2024), M.Sc. in Mechanical Engineering from Leibniz University Hannover (2018), and double bachelor's degrees in Plant Operation Engineering and Building Energy Engineering from Bremerhaven University of Applied Sciences (2015). Key appointments include a visiting scholar at Stanford University (2022) and UC Berkeley (2016-2017). Awards include the Best PhD Thesis in Biomedical Engineering (ÖGBMT, 2024) and scholarships from the Austrian Marshall Plan Foundation and Dr. Jürgen und Irmgard Ulderup Stiftung. His work spans biomechanical modeling, material science, and medical simulation, with contributions to understanding aortic pathology via computational and experimental methods. His research integrates Bayesian uncertainty quantification, finite element analysis, and patient-specific modeling. Current efforts emphasize mechanisms of aortic dissection progression and thrombosis dynamics. He collaborates with institutions like Stanford University and maintains an affiliate membership.
Chen Chang-Wen is a Chair Professor of Visual Computing at The Hong Kong Polytechnic University (2021–present). Previously, he was Empire Innovation Professor at the University at Buffalo (2008–2021) and held leadership roles including Dean of the School of Science and Engineering at CUHK Shenzhen (2017–2020). His research focuses on multimedia systems, signal processing, and communication. He is a Fellow of IEEE and SPIE, and has received numerous awards including the Alexander von Humboldt Research Award (2010) and the SUNY Chancellor's Award (2016). Chen has authored over 420 publications and holds three US patents. His work emphasizes interdisciplinary applications in visual computing, including contributions to autonomous systems, edge networks, and video quality assessment. He currently serves as Editor-in-Chief of IEEE Transactions on Systems, Man, and Cybernetics: Systems and leads initiatives in global university rankings and accreditation for engineering programs.
Mag. Günther Schreder is a Lecturer at the Department for Knowledge and Communication Management at the University for Continuing Education Krems. His research focuses on usability design, information visualization, collective intelligence, and cognitive aspects of organizational communication. He has led and contributed to multiple interdisciplinary projects, including the 'Co-Mind' initiative exploring boundary objects in innovation processes and the 'Isotype goes Data Journalism' project analyzing historical visualization techniques. His teaching includes courses on Usability Design Methods and Cognitive Psychology, emphasizing practical applications of design thinking and collaborative learning frameworks. Key research projects include developing system models for organizational improvisation, analyzing risk factors for refugee mental health, and advancing synoptic visualization approaches for cultural heritage collections. He has collaborated on EU-funded initiatives like the 'INNOMAT' project on barrier-free ticket vending machines and contributed to the 'Schema Processing in Organizational Culture' study. Schreder's work bridges cognitive science with practical design solutions, aiming to enhance user-centered systems and public engagement through innovative visualization strategies.
Sara Di Bartolomeo is a Researcher in the Algorithms and Complexity group at the University of Technology Vienna , Faculty of Informatics. Her work focuses on advanced graph visualization techniques and network analysis. Projects: Simultaneous Multiprojection Graph Visualization (FWF-funded), ArtVis (2022–2027), SANE (2024–2027), SMGV-Esprit (2024–2027) Contact: sara.bartolomeo@tuwien.ac.at Her research emphasizes graph algorithms , computational geometry , and data visualization , particularly in handling uncertainty and physicalization of networks. Recent publications explore animated node-link diagrams, game-based network analysis, and BioFabric pattern optimization. Contact: sara.bartolomeo@tuwien.ac.at
Henry Ehlersمشاهده پروفایل
پژوهشگر
Henry Ehlers is a PreDoc Researcher and PhD Candidate at the Vienna University of Technology (TU Wien), working within the Faculty of Informatics, Institute of Visual Computing & Human-Centered Technology, specifically in the Computer Graphics Group (E193-02). He holds the position of University Assistant (Univ.Ass.) and is actively pursuing his doctoral studies under the supervision of Renata Raidou since 2021, with expected completion in 2024. His research focuses on advanced visualization techniques, particularly in the areas of network and graph visualization. Ehlers specializes in biological network visualization, compound graphs, uncertainty visualization, and data physicalization. His work bridges theoretical computer science with practical applications in visual analytics, creating innovative methods for representing complex network structures and making them accessible to domain experts. Analysis of his publication record reveals a strong emphasis on improving network visualization techniques, with particular focus on biological applications, uncertainty representation, and physical data representations. His research trajectory shows increasing sophistication in addressing visualization challenges across multiple domains including biology, environmental science, and social networks. Recent publications demonstrate his leadership in developing novel interaction techniques and visualization metaphors for complex data structures. Ehlers is actively involved in multiple research projects including ArtVis (2022-2027), SANE (2024-2027), and SMGV-Esprit (2024-2027), which support his research in visualization techniques. His collaborative approach is evident in his extensive co-authorship network across international institutions and research groups at TU Wien. As a member of the Visualization Group led by Renata Raidou, Ehlers contributes to the team's mission of developing innovative visualization solutions for complex data challenges. His work particularly focuses on creating more intuitive and effective ways to represent network structures through both digital and physical means, pushing the boundaries of how we interact with complex relational data.
Davide Cenedaمشاهده پروفایل
پژوهشگر
- Visual Analytics
- Computer Science
- Data Analysis
- +۳ مورد دیگر
Prof. Dr.techn. Davide Ceneda is a researcher at TU Wien, affiliated with the Visual Analytics Research Group (E193-07). His work focuses on advancing guidance systems and methodologies within visual analytics, emphasizing user-centered design and mixed-initiative interactions. He holds a doctoral degree in guidance-enriched visual analytics (2020). Research Interests: Visual analytics, guidance design, human-computer interaction, temporal data visualization, and user-assisted systems. His recent studies explore trust models in AI-driven guidance, task-driven frameworks, and automated assistance mechanisms. Publications: Ceneda’s recent work includes papers on guidance-enhanced temporal networks (TimeLighting), dual evaluation methodologies, and the Lotse framework. His research highlights a consistent focus on improving user experience through structured guidance. Collaborations: Works closely with experts like Silvia Miksch and Alessio Arleo. Co-developed COVIs for pandemic data analysis and contributed to the Circle of Thrones radial infographic project. Awards: No specific awards mentioned, but publications reflect high-impact contributions to the field.
Prof. Silvia Miksch is a full professor in the Department of Visual Analytics at TU Wien. Her research focuses on visual analytics, time-oriented data visualization, and human-computer interaction. She leads projects in cultural heritage analysis, fraud detection, and pandemic data visualization. Her work bridges computer science with digital humanities, emphasizing user-centric design and uncertainty modeling. Key contributions include guidance systems for VA environments and network visualization frameworks for art history. Affiliations: TU Wien (since 2000+) Research Labs: Network Lab, Visual Analytics Research Group Recent projects explore temporal patterns in artist exhibitions, parameter space exploration, and pandemic data communication. She has advised over 20 PhD/Master’s students, many contributing to VA systems like COVIS and NEVA. Awarded the VGTC Visualization Technical Achievement Award (2024) for foundational work in temporal visualization. Active in IEEE VAST and serves on journal editorial boards. Her labs develop open-source tools for interactive data exploration.