Find Academic Supervisors

• Artificial Intelligence
• Nonmonotonic Reasoning
• Argumentation Frameworks
• +4 more

Stefan Woltran is a Full Professor in the Databases and Artificial Intelligence department at TU Wien. He serves as Vice Dean of Academic Affairs for the Informatics Master program and leads the Research Unit for Databases and Artificial Intelligence. His research focuses on logic-based AI, including Propositional Logic, Nonmonotonic Reasoning, Argumentation frameworks, Knowledge Representation, and Logic Programming. He coordinates the Double-Degree Program Logic and Computation. His research projects include analyzing formal properties of logic-based AI approaches, complexity analysis, and developing algorithms via logic and dynamic programming. Notable projects include the HYPAR and REVEAL-AI initiatives exploring abstract argumentation and AI problem-solving. He has contributed to over 150 publications since 2001, focusing on argumentation frameworks, computational complexity, and formal methods. Woltran teaches courses such as Abstract Argumentation, Formal Methods in Computer Science, and Theoretical Computer Science. His work integrates theoretical advancements with practical solver development, such as the ASPARTIX system for argumentation tasks. He actively participates in international conferences and competitions in computational argumentation, emphasizing the application of formal methods to real-world problems.

• Virtual Reality
• Augmented Reality
• Haptic Technology
• +5 more

Tobias Batik is a Researcher in the Department of Virtual and Augmented Reality at Technische Universität Wien . His work focuses on haptic devices for virtual reality and mixed metro map visualization, contributing to projects like Action-Origami Inspired Haptic Devices for Virtual Reality (2023) and Shiftly: A Novel Origami Shape-Shifting Haptic Device for Virtual Reality (2025). His research spans Human-Computer Interaction , Computer Graphics , and Interactive Systems , with a particular emphasis on origami-inspired design and shape-shifting interfaces. Recent publications highlight trends in Virtual Reality and Data Visualization , including metro map layout algorithms and user-specified motifs. Contact: tobias.batik@tuwien.ac.at .

Hsiang-Yun WuView profile

Research Fellow

• Information Visualization
• Visual Analytics
• Biological Network Visualization
• +13 more

Hsiang-Yun Wu is a Research Fellow at the Computer Graphics department of Vienna University of Technology (TU Wien), actively contributing to information visualization and visual analytics. Her work spans biological network visualization, graph drawing, schematic network maps, and data physicalization, with a focus on interactive techniques and human-centric design. Projects: ArtVis (2022–2027) , SANE (2024–2027) , SMGV-Esprit (2024–2027) , and HumAlgo (2018–2023) . Affiliations: Member of the Visualization Group at TU Wien. Her recent publications emphasize uncertainty visualization, network physicalization, and dynamic graph representations. Notably, she received the EuroVis 2019 Honorable Mention Award for optimizing stepwise animations. Wu supervises diploma theses in areas like metabolic pathway visualization and semantic-aware character animation. Key research trends include integrating biological data with urban-style schematic maps ( Metabopolis ), physicalization workflows for anatomical education ( Slice and Dice ), and mixed labeling strategies in 3D environments.

Silvia MikschView profile

Professor

• Visual Analytics
• Information Visualization
• Interaction Design
• +6 more

Silvia Miksch is a Full University Professor of Visual Analytics at TU Wien's Faculty of Informatics, leading the CVAST Center. She holds a PhD from the University of Vienna and has held roles including Head of the Department of Information and Knowledge Engineering at Danube University Krems. Her research focuses on Visual Analytics, Information Visualization, Temporal Data Analysis, and Medical Informatics. She has supervised numerous PhD and Master’s students, with notable advisees including Ignacio Baltazar Pérez Messina and Davide Ceneda. Her work bridges theory and practice, addressing challenges in Visual Analytics for healthcare, business intelligence, and digital humanities. Awards include the IEEE VGTC Technical Achievement Award (2023) and induction into the IEEE Visualization Academy (2020). She actively contributes to conferences like IEEE VIS and EuroVis as program chair and steering committee member. Her projects, such as 'VisuExplore' and 'DisCo', have received recognition for advancing visualization in medical and cultural domains. Key research areas include guidance-enriched systems, network visualization, and temporal reasoning. She explores applications in fraud detection, cultural heritage analysis, and pandemic data visualization. Her lab's tools, like 'Hermes' and 'COVIs', exemplify task-driven design for real-world data challenges.

János PachView profile

Professor

• Combinatorics
• Discrete and computational geometry
• Geometric graph theory
• +3 more

János Pach is a Hungarian academic currently holding the Chair of Combinatorial Geometry at École Polytechnique Fédérale de Lausanne (EPFL) since 2008. He has been a Research Advisor at the Rényi Institute of Mathematics, ELKH, since 1995, with additional roles as Professor of Computer Science at City College, City University of New York (2003–2008), and Research Professor at the Courant Institute of Mathematical Sciences (1986–2008). His work bridges combinatorics, discrete geometry, and computational complexity. Combinatorics Discrete and computational geometry Geometric graph theory Graph drawing Packing and covering Convexity He has received numerous accolades, including the ACM Fellowship (2011), Lester R. Ford Award (1990), Rényi Prize (1993), and the Gold Ring of the President of the Republic of Hungary (1983). His editorial roles include Editor-in-Chief of Discrete & Computational Geometry and editorial board memberships for over a dozen journals.

• Algorithms
• Graph Theory
• Dynamic Algorithms
• +4 more

Kathrin Hanauer is an Assistant Professor at the University of Vienna, where she is affiliated with the Research Group Theory and Applications of Algorithms and the Research Network Data Science. She conducts research in the design, analysis, and experimental evaluation of fast algorithms, with a focus on Algorithm Engineering connecting theoretical foundations with practical implementations. Her research interests include: Algorithm Engineering for practical algorithm implementation Dynamic algorithms for efficiently handling changing data Graph algorithms and network analysis Reachability problems on directed graphs Ranking problems, particularly the NP-hard Feedback Arc Set problem Network analysis, motif search, and subgraph counting Dr. Hanauer's recent publications demonstrate a strong focus on dynamic graph algorithms, with significant contributions to reachability queries, subgraph counting, and datacenter network optimization. Her work spans both theoretical algorithm design and practical implementation, often with C++ software projects. Notable contributions include the O'Reach algorithm for faster reachability queries in large graphs and several dynamic algorithms for subgraph counting and network analysis. Her scientific contributions: O'Reach: A novel approach to reachability queries in large graphs that outperforms previous methods Dynamic algorithms for four-vertex subgraph counting with efficient update operations Work on demand-aware link scheduling for reconfigurable datacenters Interdisciplinary research on normative reasoning with Aristotelian diagrams Dr. Hanauer actively supervises student research, with numerous completed theses focusing on dynamic graph algorithms, geometric algorithms, and reachability problems. Her lab maintains several software projects related to graph algorithms, including a modular algorithms library for dynamic graphs written in C++ and specialized implementations for reachability queries and subgraph counting.

• Combinatorial and Computational Geometry
• Graph Drawing
• Algorithms for Robotics

Irene Parada is an Assistant Professor and Serra Húnter Fellow at Universitat Politècnica de Catalunya (UPC BarcelonaTech), Spain. She is part of the Research Group on Discrete, Combinatorial and Computational Geometry. Previously, she held postdoctoral positions at Utrecht University, Technical University of Denmark, and TU Eindhoven. Her research focuses on Combinatorial and Computational Geometry, Graph Drawing, and Algorithms for Robotics. She has been recognized with the Margarita Salas postdoctoral fellowship and received Excellent Course Evaluations for her teaching roles. Education: PhD in Computer Science (2019) from Graz University of Technology, Austria (supervised by Oswin Aichholzer) Master's in Advanced Mathematics and Mathematical Engineering (2015) from UPC BarcelonaTech Bachelor's in Mathematical Engineering (2014) from Universidad Complutense de Madrid Research Interests: Irene's work spans geometric algorithms, graph visualization, and modular robotics. She explores computational challenges in geometric configurations, such as perfect matchings, graph embeddings, and reconfiguration problems. Her contributions include novel algorithms for dynamic planar graphs and efficient robot motion strategies. Key Achievements: Recipient of the Margarita Salas postdoctoral fellowship Best paper awards for 'On compatible matchings' and 'Saturated k-plane drawings with few edges' Excellent teaching evaluations for courses like Motion and Manipulation (Utrecht) and Data Structures (TU Eindhoven) Teaching & Mentorship: Irene has coordinated courses in Numerical Computing and Numerical Methods at UPC. She has also lectured on Motion and Manipulation, Algorithms, and Topological Data Analysis. Her roles included teaching assistantships in Discrete Mathematics and Linear Algebra at UPC. Labs & Collaborations: She collaborates with the Geometric Computing Group (Utrecht) and the Algorithms cluster (TU Eindhoven). Her work often involves interdisciplinary teams, addressing challenges in robotics, graph theory, and computational geometry.

• Parameterized Complexity
• Algorithms
• Computational Complexity
• +3 more

Sebastian Ordyniak is an Associate Professor in the Department of Algorithms and Complexity at TU Wien. His research focuses on parameterized complexity, algorithms, computational complexity, and applications in artificial intelligence and graph theory. He holds a PhD and the prestigious START Prize (2014–2022), a renowned Austrian award for outstanding researchers. Key projects include the ERC-funded 'Parameterized Complexity of Local Search' (2010–2014) and ongoing initiatives like 'Parameterized Analysis in Artificial Intelligence' (2021–2026). His work bridges theoretical foundations with practical applications, such as algorithmic fairness, machine learning interpretability, and graph drawing. Research highlights include contributions to SAT solving, backdoor analysis, and clustering algorithms. He has advised at least one student, Hossein Maleki, on practical algorithms for deletion to small components. His interdisciplinary approach integrates logic, computational geometry, and multi-agent systems.

Phuc Hung HoangView profile

Researcher

• Algorithms
• Computational Complexity
• Discrete Mathematics
• +6 more

Phuc Hung Hoang is a postdoctoral researcher in the Algorithms and Complexity Group at Technische Universität Wien (TU Wien) since November 2023, mentored by Robert Ganian. Prior to this, he worked as an Applied Scientist at Amazon EU (2021–2022) and earned his doctorate at ETH Zurich in 2022 under Bernd Gärtner and Emo Welzl. He holds a Master’s in Operational Research from the London School of Economics (2018) and a Chartered Accountant background from the National University of Singapore. His research bridges algorithmic design, discrete structures, and interdisciplinary applications. Key areas include graph algorithms, combinatorial optimization, computational complexity, reconfiguration problems, and efficient enumeration. His work often explores how structural properties of problems enable faster algorithms, with a focus on parameterized complexity, combinatorial games, and computational geometry. Recent publications highlight trends in reconfiguration problems , graph theory , and combinatorial optimization , including analyses of k-opt for TSP, degree-constrained spanning trees, and flip-based enumeration techniques. He secured the FWF ESPRIT Grant (2025–2028) as Principal Investigator for the project Structural Analysis of Combinatorial Reconfiguration . At TU Wien, he teaches courses like Efficient Algorithms and Hypercube Structures . He has supervised over 12 theses, including works on signotopes, lattice congruences, and graph safety. Beyond academia, he integrates humanistic and artistic perspectives through initiatives like Letter Earthlings and the Intercultural Science-Art Project .

Fabian KluteView profile

Research Fellow

• Graph drawing
• Automated cartography
• Map labeling
• +3 more

Fabian Klute is a Research Fellow at Universitat Politècnica de Catalunya, specializing in discrete and computational geometry. His research focuses on graph drawing, automated cartography, map labeling, and geometric computing, with emphasis on theoretical foundations and algorithm development. Klute's publications demonstrate consistent focus on geometric complexity, graph visualization, and combinatorial optimization. Recent works establish hardness results for segment folding and edge insertion problems, develop algorithms for geometric set diversity, and advance boundary labeling techniques. A significant research thread explores parameterized complexity in graph modification problems. His contributions in graph drawing include innovations in confluent drawings, book embeddings, and 1-planar extensions. Cartography-related research advances automated labeling and spatial representation for complex curve arrangements.

Velitchko FilipovView profile

Researcher

• Information Visualization
• Visual Analytics
• Dynamic Network Analysis
• +6 more

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.

Pach JánosView profile

Professor

• Combinatorics
• Discrete and computational geometry
• Geometric graph theory
• +3 more

János Pach is a distinguished academic holding the Chair of Combinatorial Geometry at the École Polytechnique Fédérale de Lausanne (EPFL) since 2008. He is also a long-term Research Advisor at the Rényi Institute of Mathematics in Budapest (since 1977). His roles include Professor of Computer Science at City College, CUNY (1992–2008) and Research Professor at the Courant Institute, NYU (1986–2008). He has held visiting positions at institutions such as Smith College, MSRI, and Hebrew University. Education: Ph.D. in Mathematics from Eötvös University (1983) with the Gold Ring of the President of Hungary, and Candidate’s Degree and Doctor of Sciences from the Hungarian Academy of Sciences (1983, 1995). Research focuses on combinatorics, discrete geometry, and geometric graph theory. He has authored 3 monographs, edited 9 volumes, and published over 270 articles. His editorial roles include Editor-in-Chief of Discrete & Computational Geometry and editorships at Combinatorica , Computational Geometry , and others. Awards include the ACM Fellow (2011), Academy Award (Hungarian Academy of Sciences, 1998), and Grünwald Medal (1982). His work has been recognized at international congresses, including an Invited Address at the 2014 ICM in Seoul. He has supervised numerous researchers and students, though specific names are not listed here. His contributions span theoretical and applied geometry, with a strong emphasis on collaborative academic leadership and international editorial work.

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.

• Computer Science
• Algorithm Engineering
• Computational Geometry
• +7 more

Martin Nöllenburg is a Full Professor in the Department of Algorithms and Complexity at TU Wien, Vienna University of Technology. He holds roles as Curriculum Coordinator for the Bachelor and Master’s programs in Theoretical Informatics and Algorithms and Complexity. His research focuses on algorithm engineering, computational geometry, graph algorithms, and information visualization. He leads projects such as 'Parameterized Graph Drawing' and 'Human-Centered Algorithm Engineering', funded by WWTF and FWF. His research interests span algorithm design, graph drawing, and visualization techniques for networks and biological systems. Recent work includes advancements in boundary labeling, graph bundling, and metro map visualization. He has supervised over 20 graduate students, producing impactful contributions to visualization and algorithmic research. Key contributions include the development of GDmetriX (a NetworkX extension for graph metrics) and studies on dynamic map labeling and combinatorial optimization. He actively participates in academic governance, serving on TU Wien’s Faculty Council and Curriculum Commission.

• Theoretical Computer Science
• Graph Algorithms
• Computational Geometry
• +3 more

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