Find Academic Supervisors

• Programming Languages
• Type Systems
• Object-Oriented Programming
• +3 more

Ao.Univ.Prof. Dipl.-Ing. Dr.techn. Franz Puntigam is an Associate Professor at the Department of Compilers and Languages within the Faculty of Informatics at Technische Universität Wien. His research focuses on programming paradigms, type systems, object-oriented programming, and concurrent programming. He teaches courses such as Programming Paradigms, Type Systems, and Scientific Research and Writing. Dr. Puntigam’s work explores foundational aspects of programming languages, emphasizing concurrency and type system design. His research includes studies on synchronization mechanisms, contextual execution environments, and design methodologies for robotic software systems. His publications span topics like token-based synchronization, dynamic process types, and aliasing effects in object-oriented languages. He supervises numerous diploma and master’s theses on advanced topics such as concurrency in Java, type systems for configuration languages, and actor-based programming. His contributions to education and research are further reflected in his involvement with projects like migrating business software from VB to Java/Unix.

Dominique SchröderView profile

Professor

• Privacy
• Distributed Trust
• Privacy-Preserving Technologies
• +7 more

Dominique Schröder is a Full Professor and Head of the Privacy Enhancing Technologies Research Unit at TU Wien. Previously, he held academic positions at Friedrich-Alexander University of Erlangen-Nuremberg and the University of Saarland. His research focuses on cryptography, privacy-preserving technologies, and decentralized systems. He obtained his Ph.D. from TU Darmstadt and his diploma from TU Braunschweig. Key research areas include privacy-preserving techniques, secure multiparty computation, cryptographic protocols, and low-entropy security. His work bridges theoretical cryptography with practical applications, particularly in blockchain, genomic data management, and decentralized systems. Education: Ph.D. in Cryptography, TU Darmstadt Diploma in Computer Science, TU Braunschweig Postdoc at University of Maryland (advisor: Jonathan Katz) Notable Contributions: Developed Group ORAM for privacy in outsourced records Advanced adaptor signatures and threshold cryptography Contributed to privacy-preserving genomic data systems like PROMISE His publications span top venues in cryptography (e.g., CRYPTO, EUROCRYPT) and address topics like secure computation resilience, functional credentials, and privacy metrics. He actively participates in academic committees and advises on privacy-enhancing technologies.

• Logic Programming
• Computational Complexity
• Nonmonotonic Reasoning
• +4 more

Mantas Simkus is an Assistant Professor at TU Wien's Institute of Logic and Computation, affiliated with the Database and Artificial Intelligence Group. He previously held an Associate Professor position at Umeå University (Sweden) within the Wallenberg AI, Autonomous Systems and Software Program (WASP). He leads the FWF-funded project 'KtoAPP: Compiling Knowledge into Applications' and contributes to the Cluster of Excellence 'Bilateral Artificial Intelligence'. His research focuses on logic-based data management, knowledge representation, and nonmonotonic reasoning, with applications in semantic web technologies and ontology engineering. Education: Bachelor's in Computer Science from Vilnius University. Research interests include logic programming, computational complexity, description logics, and their integration with databases. He explores techniques for efficient query answering, schema validation (e.g., SHACL), and reasoning under incomplete information. His work bridges theoretical foundations (e.g., complexity analysis, formal semantics) with practical systems (e.g., ontology-mediated query processing). Key projects include 'KtoAPP' (2018–2025), investigating automated knowledge compilation, and contributions to the 'SemDat' and 'OMEGA' initiatives. He teaches courses on deductive databases and semi-structured data at TU Wien. He actively participates in academic service: co-chair of RuleML+RR 2024, editorial board member of the Artificial Intelligence journal, and former co-chair of DL 2019. His research group collaborates on topics like graph databases, answer set programming, and hybrid knowledge representation systems.

• Computer Vision
• Assistive Technologies
• Healthcare Informatics
• +3 more

Irene Ballester Campos is a Researcher at TU Wien's Faculty of Informatics, affiliated with the Department of Computer Graphics and Algorithms. Her work focuses on applying computer vision and AI to develop assistive technologies for healthcare contexts, particularly in dementia care and clinical applications. She is involved in the visuAAL project (2020–2026) and previously contributed to the DIANA project (2020–2023). Her research emphasizes privacy-sensitive systems, 3D sensor technologies, and human-centered design for assistive applications. Key areas include dementia behavior monitoring through depth sensors, action recognition in privacy-sensitive scenarios, and ethical implications of assistive systems. She also explores clinical applications such as Parkinson's disease severity estimation through motion analysis. Publications highlight contributions to 3D human pose estimation, dynamic object tracking in robotics, and vision-based solutions for toileting assistance. Her work bridges computer science with healthcare, emphasizing practical deployment in real-life clinical settings.

• Cybersecurity
• Operational Technology (OT) Security
• Safety Engineering
• +3 more

Mukund Padmakarrao Bhole is a Researcher at TU Wien's Faculty of Informatics, Department of Automation Systems. His work focuses on cybersecurity and safety engineering in operational technology (OT) environments, with a particular emphasis on IT/OT integration challenges, IoT device security, and requirements engineering for Industry 4.0 systems. He is affiliated with the TÜV AUSTRIA Security in Industry Research Lab and has collaborated on multiple projects addressing threat analysis, vulnerability detection, and secure system design in industrial automation. Key research contributions include frameworks for fail-fast security evaluation, ontology-based vulnerability detection, and semi-automated requirements engineering methodologies. His work bridges theoretical cybersecurity advancements with practical industrial applications, emphasizing risk mitigation in safety-critical infrastructure. Bhole has published extensively in IEEE conferences and journals, focusing on operational technology security, IoT resilience, and industrial automation. Current research interests include enhancing OT cybersecurity through threat intelligence analysis, developing hybrid IT/OT security solutions, and advancing safety protocols for human-robot collaboration systems. His projects frequently involve collaboration with industry partners to ensure real-world applicability of academic findings.

• Formal Methods
• Systems Engineering
• Programming Semantics
• +3 more

Mark Jonathan Chimes is a Researcher in the Department of Formal Methods in Systems Engineering at Vienna University of Technology (TU Wien). He holds the role of PreDoc Researcher and is affiliated with the E192-04 institute. His work focuses on formal methods, programming semantics, and logic-based systems engineering. Chimes teaches the course 'Semantics of Programming Languages' (2025S) as a VU (lecture with exam). His research includes contributions to graph grammars and their applications in formal verification, as evidenced by his 2024 publication in the Conference on Logic for Programming, Artificial Intelligence, and Reasoning (LPAR). He can be contacted at mark.chimes@tuwien.ac.at and is located at Favoritenstrasse 9, Room HA0309.

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

Soroosh Dini-Mortezapoor is a PreDoc Researcher at the Vienna University of Technology within the Virtual and Augmented Reality department (E193-03). His research focuses on enhancing human-computer interaction through innovative haptic technologies, collaborative robotics, and immersive virtual environments. Role: Researcher (PreDoc) Contact: soroosh.mortezapoor@tuwien.ac.at Projects: ACD (2020–2028) series Research interests span Virtual Reality (VR) , Augmented Reality (AR) , haptic feedback systems , and robot-assisted 3D reconstruction . His work explores the integration of robotics with mixed reality environments, emphasizing safety, material simulation, and spatial mapping. Key contributions include: Development of Origami-inspired haptic devices Collaborative VR systems like CoboDeck Autonomous photogrammetry robots for MR environments As a supervisor, he guided S. B. Shankar in creating a robotic dummy user for VR applications. His research is supported by the ACD project (2020–2028) and published in IEEE VRW, SIGGRAPH Emerging Technologies, and other leading venues.

• Algorithms
• Graph Drawing
• Computational Geometry
• +3 more

Alexander Dobler is a PreDoc Researcher at the Algorithms and Complexity Department of Technische Universität Wien. His research focuses on algorithmic visualization, graph drawing, and combinatorial optimization. He contributes to optimizing layout algorithms for diagrams, treemaps, and storylines, with a particular emphasis on minimizing crossings and corners in geometric representations. Key projects include 'Engineering Linear Ordering Algorithms' (2020–2025) and participation in the PACE competition with solver 'Touiouidth'. His work bridges theoretical computer science with practical visualization challenges, addressing both discrete mathematics and computational geometry. Education: BSc, Dipl.-Ing. (engineering degree) Labs/Teams: Part of the Algorithms and Complexity group at TU Wien Grants: Involved in HumAlgo (2018–2023) and REVEAL-AI (2020–2024) His recent publications (2023–2025) address topics like cluster vertex splitting complexity, hoop diagrams for set visualization, and optimizing linear diagrams. He has supervised Marcel Holzmüller’s 2025 diploma thesis on expanding planar storyplan problems.

• Computational Social Choice
• Algorithmic Game Theory
• Formal Methods
• +6 more

Jie He is a PreDoc Researcher at the Department of Cyber-Physical Systems, Technische Universität Wien. His research spans computational social choice, algorithmic game theory, and formal methods in robotics and IoT systems. He works on multidisciplinary problems involving complexity analysis, fair division, and preference modeling. Current projects: EdgeAI (2022–2025), TAIGER (2023–2027), ADEX (2020–2024) Key collaborations: Research with R. Grosu, E. Bartocci, D. Nickovic Research interests focus on computational aspects of collective decision-making , including fair division, matching problems, and preference modeling. He works on both theoretical foundations (e.g., parameterized complexity) and practical applications (e.g., robotic-IoT systems). His publication history reveals deep expertise in computational complexity of social choice problems, with recent work on 3D stable roommates , fair division in graph-structured settings , and preference modeling through Euclidean and Manhattan geometries. As an advisor, he supervised diploma theses on: Optimization strategies for 5G transceivers Dynamic object detection in multi-agent systems His work appears in top conferences like ACM/IEEE DAC, ICSE, and various computational social choice venues.

• Data Science
• Information Security
• Privacy Enhancing Technologies
• +3 more

Johannes Heurix serves as a Research Fellow within the Data Science group (E194-04) at Vienna University of Technology's Faculty of Informatics. His interdisciplinary work bridges agricultural technology, information security, and semantic web applications, supported by major grants from the European Commission, Austrian Research Promotion Agency (FFG), and Vienna Business Agency. Current projects include Legume-cereal intercropping for sustainable agriculture (2022-2026) and PlusIQ agricultural photovoltaics (2022-2023). His research focuses on three interconnected domains: Sustainable Agriculture: Developing AI-driven digital twins for crop rotation optimization and pre-crop value modeling Privacy Engineering: Pioneering pseudonymization frameworks for healthcare data secondary use Smart Building Systems: Applying semantic web technologies to energy-efficient building design through the SEMERGY project Analysis of his 15 most recent publications reveals a strategic shift from foundational security research (2013-2016) toward agricultural data science (2023-2024), with 60% of recent work addressing climate-resilient farming solutions. Early publications established taxonomies for privacy technologies, while current outputs focus on AI applications for sustainable agriculture. Heurix has supervised diploma theses including Philipp Zimmermann's 2014 work on privacy technologies. His grant portfolio features: €2.1M Legume-cereal intercropping project (European Commission, 2022-2026) PlusIQ photovoltaics integration (FFG, 2022-2023) FarmIT digital agriculture initiative (Vienna Business Agency, 2021) He operates within TU Wien's Data Science research group and collaborates with the SEMERGY consortium, working alongside architects, agricultural scientists, and healthcare institutions to develop practical implementations of his research.

• Business Informatics
• Data Science
• Process Mining
• +3 more

Marco Huymajer serves as a PreDoc Researcher within the Business Informatics department (E194-03) at the Faculty of Informatics, Vienna University of Technology. He teaches core courses including Information Systems (192.170) and Programming and Algorithms (192.178) for the 2025W semester, operating from Room FB0102 at Erzherzog-Johann-Platz 1. His institutional role centers on bridging informatics and civil engineering through digital solutions for tunnel construction. His research focuses on Business Informatics applications in heavy construction, particularly Building Information Modeling (BIM), process mining, and data analytics for tunneling projects. He investigates algorithmic approaches for residual value prediction of heavy equipment, digital documentation systems, and interdisciplinary BIM integration during tunnel execution phases. This work addresses critical industry pain points in construction process optimization and data-driven decision-making. Analysis of his publication trends reveals a concentrated research trajectory since 2018, with accelerating output from 2022-2025 centered on practical BIM implementations in conventional tunneling. His work consistently targets the integration of data science with civil engineering workflows, demonstrating expertise in translating academic research into construction industry applications through the 'BIM im Tunnelbau' project framework. Funded by the 'BIM im Tunnelbau' research initiative (2020-2023), Huymajer operates without student supervision responsibilities as a PreDoc researcher. His collaborative network includes civil engineering specialists like Galler and Huemer, alongside data science experts including Filzmoser and Mazak, forming a cross-disciplinary team focused on digital transformation in tunnel construction. He actively contributes to the 'BIM im Tunnelbau' project team, which develops integrated information management systems for tunneling processes. This interdisciplinary group combines expertise from informatics, geotechnical engineering, and construction management to create practical digital solutions for the execution phase of NATM tunneling projects, with direct industry implementation pathways.

• Graph Data Management
• RDF and Semantic Web
• Database Theory
• +3 more

Maxime Jakubowski is a PostDoc Researcher at TU Wien's Faculty of Informatics, affiliated with the Databases and Artificial Intelligence research group. Based in Room HA0320 at Favoritenstrasse 9, he can be contacted at maxime.jakubowski@tuwien.ac.at and maintains an ORCID profile (0000-0002-7420-1337). His research centers on graph data management within the Semantic Web ecosystem, specializing in RDF validation through shape constraint languages like SHACL and ShEx. He investigates formal foundations, expressiveness boundaries, and practical implementations including SQL compilation and neighborhood-based graph description. Current projects include FRESH (2021–2026), KtoAPP (2018–2025), and TARGET (2024–2028), focusing on graph data theory and implementation. Recent publications (2021–2025) demonstrate consistent contributions to RDF validation standards, with 14 articles addressing shape language formalization, compilation techniques, and provenance tracking. His work bridges theoretical database concepts with industrial applications in knowledge graph validation. Dr. Jakubowski supervises bachelor theses and teaches courses including Management of Graph Data (192.161) and Project in Computer Science. His research collaborations span international projects and the Dagstuhl Seminar 24102 on Shapes in Graph Data. He is an active member of the Databases and Artificial Intelligence research group, contributing to TU Wien's leadership in graph data management and Semantic Web technologies through both theoretical research and practical tool development.

Peter KánView profile

Researcher

• Photorealistic rendering
• Augmented reality
• Virtual reality
• +5 more

Peter Kán serves as a Senior Scientist at TU Wien's Faculty of Informatics, Institute of Visual Computing and Human-Centered Technology. He manages the Mixed Reality Laboratory and teaches multiple courses including Mixed Reality Lab (193.169), PhD Seminar (193.083), and various Project courses in Computer Science and Visual Computing. PhD in Computer Science from TU Wien Research on High-Quality Real-Time Global Illumination in Augmented Reality His research spans photorealistic rendering, augmented and virtual reality systems, automatic 3D content generation, and embodied conversational agents. Current projects include RE:STOCK INDUSTRY (2024–2027), Circular Twin (2022–2025), and VR Tennis Trainer (2020–2022), funded by FFG and WWTF. His work integrates deep learning with real-time rendering for applications in industrial design, sports training, and accessibility solutions for deaf and hard-of-hearing users. Recent publications demonstrate strong focus on procedural building design, motion analysis, and accessibility interfaces. Key trends include embodied conversational agents with situation awareness, multi-objective optimization for industrial buildings, and haptic feedback systems. His research bridges computer graphics, human-computer interaction, and practical applications in architecture and healthcare. Peter Kán has received research funding from Austrian Research Promotion Agency (FFG) and Vienna Science and Technology Fund (WWTF) for projects including Conversational Agents (2023–2024) and Realistic Indoor Path Visualization (2016–2018). Supervised 10 theses including Tennis Motion Learning in VR (Sebernegg, 2025) and Embodied Conversational Agents (Rumpelnik, 2023) Manages Mixed Reality Laboratory focusing on photorealistic AR/VR systems Leads research teams on projects like Circular Twin and RE:STOCK INDUSTRY

Aleksei UdovenkoView profile

Researcher

• Symmetric Cryptography
• Cryptanalysis Techniques
• White-box Cryptography
• +4 more

Aleksei Udovenko is a post-doctoral researcher at the Laboratory of Algorithmics, Cryptology and Security (LACS) within the Security and Trust (SnT) interdisciplinary center and the Department of Computer Science (CSC) at the University of Luxembourg. His research focuses on symmetric cryptography, cryptanalysis techniques, and white-box cryptography, with notable contributions to projects like Equihash (a memory-hard proof-of-work scheme used in cryptocurrencies) and the SPARX family of lightweight block ciphers. Education: PhD in Cryptology under Prof. Alex Biryukov (2019), MSc from ITMO University (2013). Research Interests: Symmetric-key algorithms, cryptanalysis methodologies, white-box cryptography, blockchain technologies, and lightweight cryptographic primitives. He actively participates in information security competitions (CTFs) and collaborates on projects related to cryptocurrency protocols and hardware-software security. Recent Work: Authored/co-authored papers on cryptanalysis of ARX-based ciphers, LPN attacks in white-box settings, and secure obfuscation techniques. Notable publications include work on Equihash (NDSS 2016), SPARX (ASIACRYPT 2016), and advancements in meet-in-the-filter cryptanalysis techniques (SAC 2022, CHES 2023). Professional Affiliations: Member of the CryptoLUX research group, contributing to interdisciplinary projects at the University of Luxembourg. Involved in conferences such as CRYPTO, CHES, and FSE.

Monika HenzingerView profile

Professor

• Combinatorial algorithms
• Data structures
• Algorithmic game theory
• +1 more

Monika Henzinger is a Full Professor of Computer Science at the University of Vienna since 2009. Previously, she held faculty positions at the Ecole Polytechnique Federale de Lausanne (2005-2009) and the University of the Saarland (1999-2005). She has also worked as a Director of Research at Google Inc and as a Research Staff member at Digital Equipment Corporation . Education: Ph.D., Computer Science, Princeton University (1993) Diploma, Computer Science, University of the Saarland (1989) Her research focuses on combinatorial algorithms , data structures , algorithmic game theory , and web information retrieval , with significant contributions to dynamic graph algorithms and probabilistic verification. Her work addresses problems in sponsored search auctions, web mining, and formal verification of stochastic systems. Key trends in her publications include web algorithmics , dynamic graph processing , probabilistic verification , and online optimization . Her research has been recognized through prestigious grants like the ERC European Young Investigator Award and the NSF CAREER Award . Scientific Awards: ERC Advanced Grant (2013) Honorary Doctorate, Technical University Dortmund (2013) European Young Investigator Award (2004) NSF CAREER Award (1995) She has advised PhD students at EPFL and the University of Vienna , including Paul Dütting and Veronika Loitzenbauer . Her editorial roles include serving as Editor of EATCS Monographs in Theoretical Computer Science and on the ACM Research Highlights board. She has led projects such as the Doctoral School Computational Science and Dynamic Graph Algorithms in Directed Graphs .