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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.

• Visual Analytics
• Human-Computer Interaction (HCI)
• Information Visualization
• +4 more

Wolfgang Aigner is a Professor at TU Wien's Faculty of Informatics, affiliated with the Institute of Visual Computing and Human-Centered Technology. His work focuses on Visual Analytics, Human-Computer Interaction (HCI), and Information Visualization. He leads projects like KAVA-Time and HypoVis, emphasizing time-oriented data analysis and user-centered design. Education: Holds a Dr.techn. (PhD) and Privatdoz. (Privatdozent) in Computer Science. Research Interests: Includes visualization onboarding methods, temporal data analysis, knowledge-assisted VA, and interactive systems for medical and enterprise data. Notable contributions include TimeBench and Radial Sets frameworks. Awards: Honored with IEEE VAST 2012 Mention, Karl Ritter von Ghega Awards (2010, 2008), and multiple Sparkling Science grants. Courses Taught: Bachelor Thesis, Information Visualization, Project courses in Computer Science, Visual Computing, and Medical Informatics. Projects: Active in EU-funded initiatives like ArtVis, DoRIAH, and VIENA (Visual Enterprise Network Analytics). Supervises PhD students in onboarding methods and VA applications. Labs: Involved in the Visual Computing lab, focusing on HCI and interactive visual systems.

• Computer Security
• Computer Architecture
• Machine Learning Applications
• +3 more

Mai Al-Zubi is a Visiting Scientist at TU Wien's Faculty of Informatics, affiliated with the Formal Methods in Systems Engineering research group (E192-04). She holds a Master's degree and focuses on cybersecurity, computer architecture, and machine learning applications in systems engineering. Her work integrates formal methods with practical security challenges like Spectre detection through statistical and machine learning approaches. Research Interests: Cybersecurity and system security Micro-architectural side-channel analysis Machine learning for hardware-software co-design security Statistical profiling of computing systems Publications include a 2024 paper at the DATE conference on systematic evaluation of Spectre detection techniques. She contributed to the 'DK - Logic' research project (2014–2023).

Cynthia Kenia Arcanjo MarcelinoView profile

Researcher

• Serverless Computing
• Edge-Cloud-Space Continuum
• Internet of Things
• +3 more

Cynthia Kenia Arcanjo Marcelino is a PhD student and Research Scientist at the Distributed Systems Group (DSG) within the Faculty of Informatics at TU Wien. She holds a Bachelor's and Master's degree in Software Engineering & Internet Computing from TU Wien. Her research focuses on serverless computing, edge-cloud-space continuum architectures, and IoT applications. She has industry experience in large-scale distributed systems and cloud solutions. Education: Bachelor of Science in Software Engineering & Internet Computing, TU Wien Master of Science in Software Engineering & Internet Computing, TU Wien Research Interests: Serverless Computing Edge-Cloud-Space Continuum IoT Edge Intelligence Distributed Systems Her work emphasizes scalable serverless architectures and efficient scheduling strategies for distributed environments. Awards & Grants: 2024 IoT Conference Best Paper Award Netidee Project Grant (2024) Advising & Projects: Supervising master's and bachelor's theses on topics like WebAssembly runtime optimization and stateful serverless functions. Active in projects RapidREC and TEADAL focusing on edge-cloud continuum challenges. Labs & Teams: Core member of TU Wien's Distributed Systems Group, collaborating on edge-cloud infrastructure research and open-source tools like CWASI and HyperDrive.

• Distributed Systems
• Mobile Edge Computing (MEC)
• Resource Management
• +3 more

An Du is a Visiting Scientist at TU Wien's Distributed Systems research group (E194-02), affiliated with the Institute of Information Systems Engineering. His research focuses on Mobile Edge Computing (MEC), hierarchical collaborative computing frameworks, and resource management in distributed systems. He collaborates with Northeastern University, China, and has contributed to optimizing service placement and task scheduling in MEC environments. His work addresses challenges in real-time processing and resource allocation across cloud-edge-device hierarchies, aiming to minimize system costs while ensuring performance stability. Funded by grants from the National Natural Science Foundation of China and others, his research emphasizes long-term system efficiency and cross-node resource utilization. Key projects include the development of an online optimization framework for MEC systems, leveraging Lagrangian relaxation techniques to enhance computational efficiency. His findings have been published in IEEE Transactions on Services Computing and presented at international conferences.

• Distributed Systems
• Consensus Algorithms
• Dynamic Networks
• +1 more

Stephan Felber is a PreDoc Researcher at the Embedded Computing Systems group (Institute E191-02) within the Faculty of Informatics at Vienna University of Technology, holding a Bachelor of Science and Diplom-Ingenieur degree. His research expertise spans: Distributed Systems Consensus Algorithms Dynamic Networks Fault Tolerance His recent publications demonstrate deep theoretical contributions to distributed computing, particularly analyzing consensus impossibility in lossy snapshot models and characterizing message adversaries in directed dynamic networks, establishing foundational limits for fault-tolerant distributed systems. At TU Wien, he teaches core computer engineering courses including Advanced Multiprocessor Programming (191.022, VU), Computer Engineering Practical (191.005, PR), and multiple project-based courses (191.006-191.009, PR). As an integral member of the Embedded Computing Systems research group, he advances theoretical frameworks for reliable distributed computation in challenging network environments.

• Asynchronous Logic
• Real-Time Systems
• VLSI Design
• +3 more

Markus Ferringer is a Lecturer in the Department of Computer Engineering at Vienna University of Technology. He specializes in asynchronous logic, real-time systems, and fault-tolerant hardware design, with a focus on VLSI implementation and distributed systems. Research Interests: His work explores the integration of asynchronous circuits into real-time systems, emphasizing fault tolerance and reliability. Key areas include self-timed logic, time-triggered protocols, and distributed clock generation. Publications: Markus has published extensively on asynchronous hardware design, interfacing techniques, and process variation impacts. His research spans conferences and workshops such as DSN-W, DDECS, EUROCON, and Austrochip. Projects: He contributed to the ARTS project (2007–2011) supported by the Austrian Research Promotion Agency (FFG) and the THETA project (2004–2008).

• Theoretical Computer Science
• Algorithms
• Complexity Theory
• +2 more

Alexander Firbas serves as a Researcher at the Institute of Logic and Computation within Vienna University of Technology's Faculty of Informatics, specializing in theoretical computer science with emphasis on graph algorithms and computational complexity. His academic background includes a Diploma Engineer (Dipl.-Ing.) and Bachelor of Science (BSc), with his 2023 Diploma Thesis establishing foundational work on vertex splitting for hereditary graph properties. Current doctoral research extends into parameterized complexity and geometric graph representations. Firbas investigates structural graph properties through computational lenses, focusing on tractability boundaries for problems involving vertex splitting, cluster modifications, and geometric thickness. His methodology integrates fine-grained complexity analysis with algorithmic design for NP-hard graph problems. Recent publications demonstrate consistent exploration of graph modification paradigms, evolving from hereditary property establishment (2023) to cluster vertex splitting (2024) and geometric thickness tractability (2025), reflecting deepening specialization in parameterized approaches to graph-theoretic challenges. He contributes to the multi-year 'Parameterized Graph Drawing' project (2023–2027) while teaching Algorithmic Geometry and Graph Algorithms seminars. His advising activities include supervising master's theses within the Algorithms and Complexity research framework. As an active member of the Algorithms and Complexity research group, Firbas collaborates on theoretical projects examining computational boundaries in graph theory, with ongoing work targeting degree-constrained spanning trees and geometric embedding problems.

• Human-Computer Interaction
• User Experience
• Interaction Design
• +3 more

Ruadhan James Flynn is a PreDoc Researcher (Projektassistent) at the Vienna University of Technology , affiliated with the Faculty of Informatics and the Human-Computer Interaction department (E193-05). His research focuses on areas related to human-computer interaction, user experience, and usability engineering. Contact him at ruadhan.flynn@tuwien.ac.at .

Pantelis FrangoudisView profile

Researcher

• Mobile/Wireless Networking
• Edge Computing
• Network Softwarization
• +4 more

Pantelis Frangoudis is a PostDoctoral Researcher at the Distributed Systems Group of the Vienna University of Technology since 2019. His academic journey includes a Ph.D. in Computer Science (2012), M.Sc. (2005), and B.Sc. (2003) from the Department of Informatics, Athens University of Economics and Business (AUEB) , Greece. His research spans Edge Computing , IoT , Network Softwarization , Federated Learning , and Wireless Networking , focusing on adaptive systems and security. Education B.Sc. in Computer Science (2003), AUEB M.Sc. in Computer Science (2005), AUEB Ph.D. in Computer Science (2012), AUEB His research explores Edge Computing Continuum systems, with emphasis on QoS-aware orchestration , serverless edge deployment , and self-adaptive IoT services . Recent work addresses federated learning for 6G , WebAssembly for edge serverless , and dynamic resource allocation in heterogeneous environments. Key projects include AloTwin (2023–2025), INTEND (2024–2026), and EDENSPACE (2019–2022). His publications (2025–2020) cover machine learning for 5G/6G , MEC application orchestration , and IoT security , with a focus on distributed systems and edge-cloud collaboration . Scientific Awards ERCIM Alain Bensoussan Post-Doctoral Fellowship He has supervised multiple diploma theses at TU Vienna, including topics like serverless edge computing , traffic light AI optimization , and vertical farming IoT systems . His collaborations with institutions like EURECOM (France) and IRISA/INRIA (France) reflect a global academic footprint.

• Virtual Reality
• Augmented Reality
• Haptics
• +3 more

Mohammad Ghazanfari is a PreDoc Researcher at Vienna University of Technology (Vienna UT), affiliated with the School of Informatics. His work focuses on virtual and augmented reality systems, particularly encounter-type haptics, collaborative architectural design, and robotic interfaces. Current projects include the ACD (2020–2028) initiative, developing AR safety monitoring and stiffness simulation with origami-based haptic devices. Research intersects virtual reality, robotics, and human-centered design, with applications in architectural prototyping and immersive user experiences. His publications demonstrate expertise in haptics, reinforcement learning, and multi-agent systems. Recent articles emphasize walkable VR collaboration, tactile feedback optimization, and real-time safety protocols in mixed reality environments.

• Machine Learning
• Enterprise Architecture
• Conceptual Modeling
• +3 more

Philipp-Lorenz Glaser is a PreDoc Researcher at the Department of Business Informatics, Technische Universität Wien. His research focuses on conceptual modeling, enterprise architecture, machine learning applications, and knowledge graph construction. Role: PreDoc Researcher (E194-03) Contact: philipp-lorenz.glaser@tuwien.ac.at His work explores methods for encoding semantic information in conceptual models to improve machine learning applications, with a focus on FAIR datasets and hybrid modeling approaches. Key themes include: Enterprise architecture modeling practices Graph-based data representation Integration of textual and graphical modeling Development of modeling tools (e.g., Sprotty-based solutions)