Find Academic Supervisors

• Data Analysis
• Visual Analytics
• Cybersecurity
• +3 more

Stefanie Größbacher is a Junior Researcher at the Institute of Creative Media/Technologies within the University of Applied Sciences St. Pölten, Austria. She is affiliated with the Department of Media and Digital Technologies and actively contributes to the Media Computing Research Group . Her work focuses on innovative applications of digital technologies across diverse fields including healthcare, education, and cybersecurity. Größbacher holds a BSc and Dipl.-Ing. in engineering, and her research spans visual analytics , AI-driven systems , and user-centered design . She leads projects such as the Josef Ressel Center for Knowledge-Assisted Visual Analytics (industrial data analysis) and the FIVE Project (youth social media empowerment). She also collaborates on initiatives like Smart Companion (AI for autonomous living) and IoT4LAC (smart community solutions). Her technical contributions include designing museum apps , developing cybersecurity training games , and creating AI tools for content documentation . She has authored over 20 peer-reviewed publications since 2019, with a focus on usability testing, mixed reality education, and healthcare technology. Key Projects: Josef Ressel Center, FIVE, IoT4LAC, Smart Companion, MIRACLE Research Areas: Visual Analytics, Mixed Reality, Cybersecurity, Healthcare Technology Teaching Roles: Contributes to study programs in Creative Computing, Media Technology, and Digital Healthcare

• Agent-Based Modeling
• Epidemiological Simulation
• Machine Learning Applications
• +3 more

Dominik Brunmeir is a Researcher in the Data Science department at TU Wien's Faculty of Informatics. His work focuses on agent-based modeling, machine learning applications, and epidemiological simulation for public health policy analysis. He is involved in projects such as DynOptTestControl (2022–2026) and KLIPHA-COVID19 (2020–2021), contributing to pandemic response strategies and vaccination optimization algorithms. His research integrates computational methods with real-world challenges, including estimating herd immunity thresholds, evaluating contact-tracing policies, and modeling undetected infections during the SARS-CoV-2 outbreak. He has published extensively in journals like Scientific Reports , Medical Decision Making , and PLoS Computational Biology , emphasizing interdisciplinary approaches to public health and decision support systems. Key technical contributions include the development of agent-based templates for simulation efficiency, GANs for agent decision modeling, and transformer tools for medical decision-support knowledge systems. His work bridges theoretical modeling with practical applications in healthcare logistics and pandemic management.

• Algorithmics
• Computational Complexity
• Graph Theory
• +3 more

Jan Niclas Dreier is a PostDoc Researcher at TU Wien's Department of Algorithms and Complexity. His research focuses on theoretical computer science, particularly algorithmic meta-theorems, structural graph theory, and computational complexity. He is affiliated with projects such as REVEAL-AI and SLIM. His work addresses topics like monadic stability, SAT solving, and model checking on sparse graph classes. Research Interests : Dreier's primary areas include algorithm design, parameterized complexity, and logic in computer science. His contributions span model checking for graph classes, backdoor analysis in SAT solving, and combinatorial properties of monadic dependence. Recent work explores the interplay between structural graph theory and algorithmic efficiency, with applications to finite model theory and pseudorandom models. Teaching : He teaches courses such as Algorithmic Meta-Theorems , Algorithmics , and Bachelor Thesis in Computer Science . His courses emphasize theoretical foundations and practical algorithmic techniques. Projects : Active involvement in the REVEAL-AI project (2020–2024) and SLIM (2019–2024), focusing on algorithmic advancements in AI and structural graph analysis.

Philipp ErlerView profile

Researcher

• Surface Reconstruction
• Point Clouds
• Deep Learning
• +4 more

Philipp Erler is a PreDoc Researcher at the Computer Graphics department of Vienna University of Technology . His work focuses on surface reconstruction from point clouds, geometry processing, and deep learning applications in computer graphics. Research Highlights : LidarScout (2025): Direct out-of-core rendering of massive point clouds PPSurf (2024): Patch-based deep learning for surface reconstruction Points2Surf (2020): Implicit surface learning from raw point clouds without normals His research extends into virtual reality, physical simulations, and natural language processing. He has supervised four theses on topics including surface reconstruction optimization and differentiable rendering.

• Databases
• Artificial Intelligence
• Text Mining
• +2 more

Ingo Feinerer serves as an Associate Professor at Vienna University of Technology's Faculty of Informatics, specifically within the Institute of Information Systems Engineering (E192-02). His research bridges theoretical computer science and practical applications in database systems, artificial intelligence, and text mining, with significant contributions to configuration management and formal methods. His educational background includes: PhD Dissertation (2007): A formal treatment of UML class diagrams as an efficient method for configuration management Diploma Thesis (2005): Formal program verification: a comparison of selected tools and their theoretical foundations Feinerer's research focuses on database theory (particularly schema mapping and dependencies), AI-driven configuration systems using integer linear programming, and text mining infrastructure development in R. His work combines theoretical rigor with practical tool development, notably through the textcat and tm packages. The integration of formal methods in software engineering remains a consistent thread throughout his publications. Analysis of his 15 most recent publications reveals strong specialization in database constraints (40%), text mining applications (30%), and software configuration systems (30%), with increasing interdisciplinary work connecting computer science to digital humanities. His notable recognition includes: INiTS Award (2007) for technology commercialization potential Feinerer has supervised doctoral research including F. I. Chertes' work on schema mapping languages and diploma theses on UML semantics and probabilistic databases. He led major research projects HINT (2012-2017) and SEE (2012-2016) focusing on database technologies and information systems. His work demonstrates consistent funding through Austrian national research programs. As a core member of the Databases and Artificial Intelligence research group, he collaborates extensively on R package development for text analysis and contributes to international workshops on theoretical aspects of software engineering.

Christian FreudeView profile

Researcher

• Computer Graphics
• Rendering
• Monte Carlo Methods
• +3 more

Christian Freude is a PreDoc Researcher at the Department of Computer Graphics , Faculty of Informatics , Vienna University of Technology (TU Wien) , focusing on Visual Computing and Human-Centered Technology . His work bridges photorealistic rendering , Monte Carlo methods , and real-time simulation . Active in projects: Toward Optimal Path Guiding (2023–2027, WWTF-funded), ACD (2020–2028) Supervised PhD/Master's students : Lukas Lipp, Christian Jauernik, Johannes Lurf Research spans Monte Carlo denoising , radiative thermal transport , subsurface scattering , and point cloud rendering . His 2025 work on Inverse Simulation of Radiative Thermal Transport introduces novel methods for efficient heat distribution modeling. Key scientific awards include the OCG Förderpreis 2016 . Publications from 2015–2025 highlight advancements in rendering algorithms , stereoscopic film , and uncertainty visualization .

• Workforce Scheduling
• Time Management
• Operational Research
• +3 more

Johannes Gärtner is a Senior Lecturer at Vienna University of Technology, affiliated with the Artifact-based Computing and User Research department (E193-04). His work focuses on shift scheduling, working time policies, and the intersection of law with software development. Academic Rank: Senior Lecturer Department: Artifact-based Computing and User Research, E193-04 University: Vienna University of Technology Research interests include Workforce Scheduling , Time Management , Operational Research , Human-Computer Interaction , Data Analysis , and Software Engineering . He applies these to shiftwork optimization, risk modeling, and legal-compliant software design. His key projects include ARTIS (2017–2025), ARTE (2012–2017), and Softnet (2006–2011), focusing on work scheduling systems, risk assessment tools, and data quality frameworks. Publications emphasize AI-driven scheduling algorithms , injury risk estimation , and legal explainability in software . His supervisees include D. Cygan (2012), W. Schafhauser (2010), A. Höfer (2006), and N. Tawil (2003).

• Answer-Set Programming (ASP)
• Explainable AI
• Logic in Artificial Intelligence
• +3 more

Tobias Geibinger is a PreDoc Researcher at the Institute of Logic and Computation of Vienna University of Technology , supported by a DOC Fellowship from the Austrian Academy of Sciences. His work focuses on explainability in Answer-Set Programming (ASP), particularly for advanced language features and hybrid ASP systems. Education: BSc, Dipl.-Ing. (Master's equivalent) in Computer Science Projects: CD Laboratory for AI and Optimization (2017–2025), KIRAS-PrEMI (2019–2022), ARTIS (2017–2025) His research combines logic programming with constraint programming and hybrid methods to solve industrial scheduling problems. This includes automated test laboratory scheduling, photolithography job scheduling, and pandemic-era physician scheduling. Recent work investigates neurosymbolic integration and contrastive explanation frameworks. Selected publications analyze ASP optimization techniques for parallel machine scheduling, large-neighborhood search strategies, and nonmonotonic paraconsistent logics. These contributions align with broader trends in declarative AI and logic-based optimization. Scientific Recognition: ASAI Master Thesis Prize (2023)

• Human-Computer Interaction
• Gamification
• User Interface Design
• +7 more

Johannes Harms is a PostDoc Researcher at the Department of Business Informatics, Vienna University of Technology . His work bridges Human-Computer Interaction and Health Informatics , focusing on innovative user interface design , gamification in surveys, and mobile application development . Research Highlights : Design of gamified data collection tools, navigation in web forms, form-based UI metaphors, and location-based systems. Education : PhD in Business Informatics (2016) and Dipl.-Ing. in Informatics (2010), both from TU Wien. His research interests revolve around enhancing user experience in digital systems. He investigates gamification as a method to improve user engagement in online surveys, develops tools like SQT for quality assessment, and explores form-based interface metaphors to modernize traditional UIs. Additionally, he designs location-based smartphone games (e.g., Woody ) to promote physical activity and studies spatial databases for efficient data handling in healthcare and urban contexts. The articles reflect a trajectory from foundational work on web form navigation (2014–2015) to applied health informatics (2024). Key trends include gamification in user research, cross-device interaction design , and location-based systems . His supervised theses (2013–2015) demonstrate mentorship in software engineering and user experience for smart restaurants.

Bernhard KerblView profile

Researcher

• Computer Graphics
• Real-Time Rendering
• GPU Programming
• +4 more

Bernhard Kerbl is a Post-doctoral Researcher at the Computer Graphics Group (E193-02) within the Faculty of Informatics at Vienna University of Technology (TU Wien). He actively contributes to research in real-time rendering, GPU optimization, and 3D visualization. His work focuses on point cloud rendering, Gaussian splatting, and low-level graphics API development (particularly Vulkan). Core Research Areas: Real-time rendering, GPU programming, point cloud processing, 3D Gaussian splatting, task-based parallelism Projects: IVILPC (2023–2026), ACD (2020–2028), EVOCATION (2018–2022) Key Contributions: Developed real-time rendering techniques for massive datasets, pioneered GPU-based scene streaming architectures, and created novel methods for visual error prediction using machine learning. His work on Vulkan transition in academia received recognition, and he maintains active collaborations in GPU education. Scientific Achievements: Best Paper Award at EGPGV 2024 for "Fast Rendering of Parametric Objects on Modern GPUs" Recipient of Vienna Science and Technology Fund (WWTF) support for graphics research Technical Expertise: Specializes in CUDA, OpenGL/Vulkan APIs, and real-time systems. His work bridges academic research with practical implementations in virtual reality, augmented reality, and GPU education.

• Worst-Case Execution Time Analysis
• Real-Time Systems
• Testing of Embedded Systems
• +2 more

Raimund Kirner is an academic at the Institute of Computer Engineering (E191-01) at Technische Universität Wien , specializing in real-time and embedded systems. His career spans research in Worst-Case Execution Time (WCET) Analysis , Time-Triggered Communication , and Automated Testing for safety-critical systems. He has contributed to projects such as ALL-TIMES, COSTA, and HINT, focusing on timing predictability and composability in real-time systems. Key Research Areas : WCET Analysis, Real-Time Systems, Embedded Testing, Time-Predictable Computing Notable Collaborations : Peter Puschner, Andreas Prantl, Martina Zolda Recent Publications analyze cybersecurity in automotive networks, quantitative interface evaluation for time-triggered systems, and synchronization trade-offs. His work bridges theoretical timing models with practical compiler and hardware solutions for deterministic execution. Awards : Recipient of the Mobilitätsstipendium der Creditanstalt AG (2003) for outstanding dissertation. Advising includes supervising 11 theses from 2002–2014 on topics like Automated Load Balancing , WCET Estimation , and Compiler Timing Models .

Berry GérardView profile

Professor

• Models of computation
• Programming language design
• Synchronous programming
• +5 more

Berry Gérard is a distinguished Professor at Collège de France, holding the Chair in Algorithms, Machines, and Languages since 2012. He previously served as Director of Research at INRIA Sophia Antipolis and Chief Scientist at Esterel Technologies. His academic journey includes roles at École des Mines de Paris and École Polytechnique. Gérard specializes in models of computation, programming language design, and synchronous systems. He has contributed significantly to the development of the Esterel language for embedded systems and formal verification techniques. Education: Docteur d’Etat in Mathematics, Université Paris VII (Computer Science option), 1979 Ingénieur des Mines, Corps National des Ingénieurs des Mines, 1970 École Polytechnique, 1967 Research Interests: Focuses on computational models (e.g., lambda-calculus, synchronous concurrency), programming languages (Esterel, Hop/HipHop), circuit synthesis, and formal verification. His recent work explores diffuse programming and web orchestration. Key Awards: 2014: Médaille d'or du CNRS 2005: Member, Académie des technologies 1993: Member, Academia Europaea 1979: Bronze Medal of CNRS Professional Roles: President of the Council of Education and Research at École Polytechnique Member of the Scientific Council of IRCAM Former President of the INRIA Evaluation Committee Labs/Teams: Active in INRIA’s Indes project on diffuse programming and collaborates with IRCAM on real-time music systems.

Ivan BratkoView profile

Professor

• Computer Science
• Machine Learning

Ivan Bratko is a Full Professor at the Faculty of Computer and Information Science, University of Ljubljana, and has held leadership roles including Head of AI Lab (1986–present) and former Head of AI Department at Jožef Stefan Institute (1996–2004). His career spans over four decades, with research contributions in machine learning, qualitative modeling, and artificial intelligence applications. Developed the KARDIO expert system for cardiac arrhythmia diagnosis using deep qualitative knowledge Innovated ABML (Argument-Based Machine Learning) for faster, interpretable learning with expert annotations Created Q 2 learning methods that integrate qualitative constraints with quantitative prediction Contributed to minimax search analysis and decision tree pruning algorithms His work has earned prestigious awards, including the Zois award (2007) and Fellow of ECCAI (2000). He continues part-time research at Jožef Stefan Institute (since 1975) and authored influential textbooks like Prolog Programming for Artificial Intelligence .

Stephen Andrew BustinView profile

Professor

• Cancer biomarkers
• Molecular genetics
• Reverse transcription
• +5 more

Stephen Bustin is a Professor of Molecular Medicine at Anglia Ruskin University (ARU), UK, with a career spanning academia and industry. He previously held roles at Queen Mary University of London (2004–2012) and London Hospital Medical College (1995–2002). His work focuses on PCR technology standardization, molecular diagnostics, and SARS-CoV-2 testing, including the development of MIQE guidelines for qPCR/digital PCR. Education: PhD in Molecular Genetics from Trinity College, University of Dublin, Ireland. Research interests include improving reproducibility in molecular methods, early diagnosis of infectious diseases, and applications of PCR in clinical settings. He has pioneered a five-plex SARS-CoV-2 assay and sub-five-minute point-of-care diagnostics. His recent articles emphasize PCR standardization (MIQE 2.0), SARS-CoV-2 testing, Peyronie's disease mechanisms, and reproducibility challenges in biomedical research. Topics span molecular diagnostics, qPCR, and infectious disease surveillance. Scientific Awards: Fellow of the Society of Biology (2010), Elected Member of Academia Europaea (2023). He has testified as an expert witness in international trials (MMR vaccine-autism litigation, Lundy murders) and authored influential books including the "qPCR bible." His work addresses colorectal cancer prognostics, assay design, and transparency in molecular research.

Federico CapassoView profile

Professor

• Quantum Cascade Lasers
• Bandstructure Engineering
• Plasmonics
• +7 more

Federico Capasso is the Robert Wallace Professor of Applied Physics at Harvard University, where he has been a faculty member since 2003. He is renowned for inventing the quantum cascade laser at Bell Laboratories and pioneering bandstructure engineering in semiconductor devices. His research spans plasmonics, metasurfaces, nanophotonics, and Casimir forces , with applications in light sources, optical antennas, and MEMS technology. PhD in Physics, summa cum laude, University of Rome (1973) Leadership roles at Bell Labs: Head of multiple departments (1987–2000), Vice President (2000–2002) Research Interests: Quantum electronics, terahertz radiation generation, plasmonic interfaces, and flat optics. His group at Harvard demonstrated optical antennas, plasmonic collimators , and generalized laws of reflection/refraction via metasurfaces. Article Trends: Recent work focuses on metasurface optimization , integrated solitons , optical rotatum , and active mid-infrared ring resonators , reflecting advancements in flat optics and quantum electronics. Scientific Awards: 2016 Balzan Prize 2013 SPIE Gold Medal 2005 King Faisal Prize 2004 Edison Medal 1995–1998: National Academy memberships and fellowships Labs/Teams: Leads the Capasso Group at Harvard, which co-founded the startup Metalenz for metasurface commercialization.