Find Academic Supervisors

• Cryptography
• Computer Security
• Data Compression
• +3 more

Stefano Trevisani is a PreDoc Researcher at the Security and Privacy department of Technische Universität Wien (E192-06). His research focuses on cryptography, computer security, and mathematical logic. Key areas include arithmetization-oriented hashing, compression functions, and algebraic structures like branching interval algebra. Cryptography Computer Security Data Compression Algebra Computational Complexity Trevisani’s publications highlight innovations in secure hashing algorithms (e.g., Arion permutation) and theoretical advancements in branching algebra fragments. His work bridges applied cryptographic protocols with foundational mathematical logic. He contributes to the SFB SPyCoDe project (2023–2026), focusing on secure systems and cryptographic efficiency. Contact: stefano.trevisani@tuwien.ac.at .

• High Performance Computing
• MPI Programming
• Parallel Algorithms
• +2 more

Ioannis Vardas is a Researcher in Parallel Computing at TU Wien's Faculty of Informatics. His work focuses on optimizing high-performance computing systems through advanced process mapping, MPI programming, and performance analysis tools. Key research areas: Topology-aware process mapping for HPC MPI library development and optimization Performance profiling of parallel applications Resource allocation in hierarchical architectures Energy-efficient parallel computing He contributes to projects improving MPI performance tools and develops methods for efficient resource utilization in supercomputing environments.

• Algorithms
• Constraint Programming
• SAT Solving
• +2 more

Florentina Voboril is a Research Fellow in the Algorithms and Complexity group at Technische Universität Wien. Her research explores how Large Language Models can solve Constraint Programming instances efficiently, with additional focus on SAT-solving and algorithm design. She investigates applications of AI in combinatorial optimization problems and develops innovative approaches to algorithmic challenges. Voboril has developed methods for SAT-based local improvement in string problems and generates streamlining constraints using LLMs. Her work bridges theoretical computer science with practical applications in computational biology and AI-assisted programming.

• Distributed Systems
• Formal Verification
• Fault-Tolerant Algorithms
• +2 more

Dr. Josef Widder is an Affiliated Researcher and Privatdozent at Technische Universität Wien's Embedded Computing Systems department. His research develops formal methods for verifying fault-tolerant distributed systems, with contributions to model checking and concurrent system verification. Core research areas include parameterized verification techniques, Byzantine fault tolerance, and synchronization in distributed algorithms. Recent work focuses on efficient model checking approaches for synchronous systems and counter abstraction methods. Supervision activities include doctoral students working on SMT-driven verification techniques and symbolic verification of distributed algorithms. Recognized through dissertation awards for contributions to distributed computing theory.

• Optimization
• Scheduling Algorithms
• Artificial Intelligence
• +2 more

Dr. Felix Winter is a PostDoc Researcher in the Databases and Artificial Intelligence group at Vienna University of Technology. He teaches courses including Bachelor Thesis supervision, Project in Computer Science, and Database Systems. His research focuses on optimization algorithms for industrial scheduling problems, including oven scheduling, artificial teeth production scheduling, employee task distribution, and paint shop scheduling. Methodologies include hybrid approaches combining exact methods with metaheuristics. Recent publications demonstrate consistent application of operations research techniques to manufacturing contexts, with emphasis on developing practical solutions for complex scheduling challenges in automotive supply chains and dental production environments. Dr. Winter supervises student research projects including diploma theses on optimization topics. Current projects include the CD Laboratory for Artificial Intelligence and Optimization for Planning and Scheduling (2017-2025).

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.

Frank SommerView profile

Research Fellow

• Parameterized algorithms
• Algorithm engineering
• Graph algorithms
• +2 more

Frank Sommer is a Humboldt fellow (Feodor Lynen scholarship for Postdocs) at Vienna University of Technology since June 2024. He is affiliated with the Institute of Logic and Computation, where he conducts research in theoretical computer science and algorithms. Previously, he held postdoc positions at Friedrich Schiller University Jena (May 2023-May 2024) and Philipps University Marburg (November 2022-May 2023). Dr. Sommer earned his PhD in Mathematics from Philipps-University Marburg (2017-2022), following a Master's degree (2015-2017) and Bachelor's degree (2012-2015), both in Mathematics from Friedrich Schiller University Jena. His research focuses on parameterized algorithms , algorithm engineering , and graph algorithms , with applications to hard problems in Data Science and Machine Learning. He has made significant contributions to the theoretical foundations of graph problems, particularly in network analysis, community detection, and subgraph optimization. His methodology combines theoretical analysis with practical implementation, emphasizing both computational complexity and real-world applicability. Dr. Sommer's publication record shows a strong emphasis on parameterized complexity, kernelization techniques, and practical algorithm implementations. His work spans from theoretical foundations to practical applications in network analysis, machine learning, and data science, with particular expertise in graph-theoretic problems and their computational aspects. Scientific Awards: Humboldt fellow (Feodor Lynen scholarship for Postdocs) Dr. Sommer collaborates extensively with researchers including Christian Komusiewicz, Niels Grüttemeier, and Tomohiro Koana. His work is supported by the Humboldt Foundation and has been published in top-tier computer science venues including Algorithmica, Journal of Graph Algorithms and Applications, and proceedings of major conferences like ESA and ISAAC. He is part of the Algorithms and Complexity Group within the Institute of Logic and Computation at TU Vienna, contributing to research on fundamental algorithmic problems with applications across various domains. His current research explores the intersection of theoretical computer science with practical challenges in data science and machine learning.

• Materials Science
• Educational Technology
• Machine Learning
• +3 more

Martin Antenreiter is a Professor and Chair of Information Technology. His research spans materials science, educational technology, and machine learning. Key projects include fracture analysis in materials and development of online proctoring systems. He has contributed to 18 publications and 10 professional activities. Education: Dipl.-Ing. (Master of Engineering) and Dr.mont. (Doctor of Engineering Sciences). Research interests focus on interdisciplinary applications of IT in education and materials engineering. Recent collaborations involve international conferences like i-KNOW and Hybrid Modeling Summer School. Advising: Supervised 3 academic works. No scientific awards explicitly mentioned. Active in conferences and workshops, emphasizing practical IT solutions for education and materials research.

• Machine Learning
• Reinforcement Learning
• Algorithms
• +3 more

Peter Auer is a Professor and Chair of Information Technology at Montanuniversität Leoben. His research focuses on machine learning, reinforcement learning, and algorithm design with applications in network optimization, materials science, and industrial processes. He has authored 132 publications and supervised 23 works. Recent activities include invited talks on 'Mathematische Grundlagen der AI' (May 2025) and visiting the Fraunhofer-Institut für Nachrichtentechnik (August 2022). His educational background includes Dipl.-Ing. (Diplom-Ingenieur) and Dr.techn. (Doctor of Technical Sciences) degrees. Research interests span multi-armed bandits, reinforcement learning theory, and practical implementations in domains like cognitive radio networks and crystal growth simulations. He actively participates in academic collaborations, including the 'MINT@Leoben' outreach program (2021-2022) and international conferences. His work bridges theoretical computer science with real-world engineering challenges.

Horst EidenbergerView profile

Associate Professor

• Multimedia Information Retrieval
• Virtual and Augmented Reality
• Machine Learning
• +6 more

Horst Eidenberger is an Associate Professor at the Technische Universität Wien (TU Wien), affiliated with the Institute for Visual Computing and Human-Centered Technology within the Faculty of Informatics. He holds part-time status at the university. His research focuses on computational perception of audiovisual media, forensic biometrics, multimedia systems, machine learning, and virtual/augmented reality. He leads projects like the Virtual Jumpcube and Vreeclimber hybrid systems, integrating sensory stimuli in VR environments. Eidenberger supervises numerous student theses, covering topics from AI political agents to plant detection with machine learning. He teaches courses on deep learning, VR design, and multimedia retrieval. His work bridges technical innovation with practical applications, including cybersecurity, healthcare, and immersive storytelling. Roles: Associate Professor, Expert Witness in IT/Sigproc, VR Project Lead. Research Interests: Biometric media analysis, hybrid VR systems, optical music recognition, and machine learning. Projects: Vreeclimber climbing wall, Virtual Jumpcube, DeepOMR, and forensic biometrics. Publications span over 50 peer-reviewed articles, emphasizing multimedia retrieval, VR systems, and cognitive modeling. His Handbook of Multimedia Information Retrieval (2012) remains a foundational text. Eidenberger actively mentors students and contributes to interdisciplinary collaborations in AI, HCI, and digital media.

• Computer Architecture
• Compilers
• Programming Languages
• +4 more

Andreas Krall is an Associate Professor in the Department of Software Technology at TU Wien's Faculty of Informatics. He holds roles as Curriculum Coordinator for the Bachelor Informatics and Bachelor Software and Information Engineering programs, and serves as a Substitute Member of the Curriculum Commission for Informatics. His research focuses on compiler design, architecture description languages (e.g., VADL), and formal methods for ensuring correctness in compiler-processor co-design. Key research areas include computer architecture, compiler verification, embedded systems, and the development of tools for processor simulation and optimization. Krall has led projects such as 'Correct Compilers for Correct Processors' (2010–2015) and contributed to the CACAO JVM project. He has published extensively on topics like instruction selection, abstract state machines (CASM), and SSA-based optimizations. Notable awards include the Heinz Zemanek Preis (1987). His work spans over 30 years, with contributions to both academic research and industry-relevant tools like the VADL architecture description framework. Krall has advised numerous students in topics ranging from compiler backends to garbage collection algorithms.

Stefan NeumannView profile

Assistant Professor

• Machine Learning
• Social Network Analysis
• Graph Algorithms
• +4 more

Stefan Neumann is an Assistant Professor at TU Wien, funded by a WWTF VRG grant, and an associate faculty member at the Complexity Science Hub. His research focuses on algorithms for data science and social network analysis, including opinion dynamics, graph algorithms, and scalable algorithms with provable guarantees. He coordinates the Machine Learning curriculum for the Master's program at TU Wien. Education: Ph.D. from the University of Vienna (advised by Monika Henzinger), postdoc at Brown University with Eli Upfal, and WASP assistant professor at KTH Royal Institute of Technology. He won the Heinz Zemanek Award and an Award of Excellence from the Austrian federal government. Research interests include: Foundations of data science: Practical algorithms with theoretical guarantees Social network analysis: Impact of timeline algorithms on polarization Graph algorithms and dynamic data structures Projects include Towards Trustworthy Recommendation Systems for Online Social Networks (2023–2031, funded by Vienna Science and Technology Fund). Teaching: Courses on machine learning, algorithms, and research writing. Advises PhD students like Sebastian Lüderssen and manages a team of student assistants. Labs/Teams: Active in TU Wien's Machine Learning Research Unit and collaborates with the Complexity Science Hub on interdisciplinary projects.

• 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.

• Knowledge Representation
• Description Logics
• Computational Logic
• +3 more

Magdalena Ortiz is a Full Professor and Head of the Knowledge-Based Systems Research Unit at TU Wien, specializing in Knowledge Representation and Reasoning with a focus on Description Logics (DLs). Her work emphasizes integrating DLs with database systems, particularly in query languages and reasoning algorithms. She leads research in semantic technologies, ontology-mediated query answering, and formal methods for data validation (e.g., SHACL). Research interests include expressive query languages, computational complexity of DL reasoning, and applications in graph databases and cloud security. She has extensive experience in EU-funded projects (e.g., FRESH, KtoAPP) and serves editorial roles in AI conferences/journals. Her teaching includes advanced courses on Description Logics, Logic, and Ontology Engineering. Notable contributions include advancements in SHACL validation, Datalog rewritings for ontology-mediated queries, and reasoning with closed predicates. She advises multiple PhD students and collaborates internationally on topics like temporal equilibrium logic and OBDA systems.

• Automated Software Verification
• Formal Methods
• Model Checking
• +7 more

Georg Weissenbacher is a Full Professor in the Institute of Logic and Computation at TU Wien, leading the Formal Methods in Systems Engineering group. His research focuses on automated software verification, formal methods, and concurrency bug analysis. He holds a DPhil from Oxford and has held positions at Princeton and ETH Zurich. Education: TU Wien (since 2010), Postdoctoral Researcher at Princeton University (2010–2012), PhD from Oxford University (2008–2010), Research Assistant at ETH Zürich (2005–2010), Master's at TU Graz (until 2003). Research Interests: Automated software verification, formal methods, model checking, concurrency bug detection, logic and automated reasoning, symbolic simulation, and test case generation. His work addresses challenges like Heisenbugs in concurrent systems and robustness verification of neural networks. Grants & Projects: Lead projects such as AutoTest (Vienna Science Fund), LogiCS-Scholarships (2017–2025), and contributions to the National Research Network 'Rigorous Systems Engineering' (FWF). Active in the FWF-funded doctoral college 'Automated Reasoning' (2025). Advising: Supervised over 20 PhD and master's students, including notable works on Heisenbugs, mutation testing, and neural network verification. Current advisees include Thomas Hader and Sarah Sallinger. Labs & Teams: FORSYTE Group at TU Wien, collaborating on formal methods and automated reasoning. Engaged in international conferences like CAV and FMCAD as program chair/co-chair.