Dr. Sebastian Neumaier is a Senior Researcher at the Institute of IT Security Research within the Department of Computer Science and Security at University of Applied Sciences St. Pölten . He focuses on open data ecosystems, knowledge graphs, and semantic web technologies. Research Interests : Open Data Quality and Governance Knowledge Graph Construction Data Security and Usage Control Semantic Web Standards Smart City Data Infrastructure Publication Trends (2015–2025) span open data quality assessment, knowledge graph applications, cybersecurity in data spaces, and semantic data labeling. Key subfields include license compliance, spatio-temporal data systems, and decentralized dataset exchange architectures. Education : PhD (2019) – Semantic Enrichment of Open Data Master's Thesis – Data Intelligence BSc – Computer Science Labs & Projects : Core contributor to ADEQUATe platform for open data quality Co-developer of DALICC as a service for license clearance Active in data space policy frameworks Participant in EU digital product passport initiatives
Justus Piater is a Professor of Computer Science at the University of Innsbruck, serving as the Head of the Digital Science Center and an ELLIS Fellow. His primary affiliation is the Department of Computer Science within the Faculty of Mathematics, Computer Science and Physics. He has held academic roles since 2002, including Assistant and Associate Professorships at Université de Liège before joining the University of Innsbruck in 2010. His research focuses on robot learning, perception, and manipulation, emphasizing how robots can learn to perceive and act with understanding. Notable projects include the EU-H2020 IMAGINE project and the Euregio International Project Network OLIVER. Education includes a Ph.D. in Computer Science from the University of Massachusetts Amherst (2001), complemented by earlier studies in Germany and Belgium. His service roles include Dean of the Faculty of Mathematics, Computer Science and Physics (2014–2017) and Vice Chair of the Department of Computer Science (2014–present). His research outputs span robotics, AI, and interdisciplinary education, with a strong emphasis on autonomous systems and cognitive development.
Fausto Giunchiglia is a Full Professor in the Faculty of Science at the University of Trento, Italy, where he has served since 1999. Previously, he was an Associate Professor at the Faculty of Economics, University of Trento (1992-1999), and held positions at Stanford University, University of Genoa, ITC-IRST, and University of Edinburgh. He is a Fellow of EurAI, AAIA, and ECCAI, and a member of the Academia Europaea. Education: PhD in Computer Engineering, University of Genoa, Faculty of Engineering (1987) Master in Computer Science, University of Genoa, Faculty of Engineering (1983) Laurea (Master) in Electronic Engineering (specialization in Computer Engineering), University of Genoa, Faculty of Engineering (1981) Professor Giunchiglia's research spans Artificial Intelligence with a focus on social computing, logics and formal methods, knowledge management and representation, agent-oriented software engineering, and semantics. His current research explores computational models of the mind and how the known is grounded in the unknown. He has made significant contributions to both theoretical foundations and practical applications of AI, with particular emphasis on enabling worldwide diversity-aware data-driven social innovation. Throughout his career, Giunchiglia has received numerous honors including being named an Honorary Professor at Jilin University, winning the IBM Shared University Research Grant, and receiving multiple innovation awards for EU-funded projects including WeNet, WhiteRabbit, InteropEHRate, and Smart Society. Professional Leadership: Member of the Panel "Computer Science and Informatics" of the European Research Council (ERC) Chair of the International Advisory board of SICSA (Scottish Informatics and Computer Science Alliance) Coordinator of the task-force for the Italian National Research Program in ICT Scientific Coordinator of the Italian Platform for the Future Internet Co-founder and first Head of the Department of Computer Science at University of Trento Vice-rector of the University of Trento in charge of ICT and innovation Giunchiglia has advised over 50 PhD and Master's students throughout his career and has been deeply involved in academic leadership, serving as President of IJCAI, President of KR, Inc., and on editorial boards of numerous prestigious journals including the Journal of Data Semantics and Journal of Artificial Intelligence Research. He leads the Knowdive research group and the DataScientia social innovation initiative at the University of Trento.
Kristof Meixner is a Postdoctoral Researcher at the Institute of Information Systems Engineering (E194) within the Faculty of Informatics at Technische Universität Wien. He completed his PhD in Computer Science in 2024 and holds a Master's degree in Business Informatics from the same institution. His academic journey includes significant teaching responsibilities and substantial research contributions in cyber-physical production systems engineering. Position: Postdoctoral Researcher, Institute of Information Systems Engineering (Dec 2024 - present) Previous Position: Researcher at Christian Doppler Laboratory for Security and Quality Improvement in Production Systems (Mar 2018 – Dec 2024) Teaching: Lecturer for Advanced Software Engineering, Software Engineering Project, and related courses since 2018 Service: Research Unit Representative in the Scientific Staff Council since 2017 Meixner's research focuses on model-based approaches for software product line engineering in cyber-physical production systems. His work addresses the integration of interdependent models for products, processes, and resources, with particular emphasis on variability management, change impact analysis, and digitalization of production systems. His research combines empirical methods with practical tool development to improve software engineering practices in industrial contexts. His publication portfolio shows a strong trend toward multi-disciplinary approaches that integrate software engineering with production systems engineering. The 2024 publications particularly emphasize risk management, multi-domain modeling, and the application of AI techniques to variability management problems. His work frequently appears in top-tier software engineering and production systems conferences including ETFA, SPLC, and CBI. 80+ peer-reviewed publications 754 citations h-index: 16 As an educator, Meixner has supervised numerous bachelor's and master's theses, demonstrating his commitment to mentoring the next generation of software engineers. His teaching spans both theoretical foundations and practical applications of software engineering principles, with a focus on production systems contexts. He has also contributed to diversity initiatives at TU Wien, serving as a representative on the Diversity Team for the Diversitas 2016 Award. Despite experiencing a spinal cord injury in 2000 that resulted in wheelchair dependency, Meixner has maintained an active research and teaching career, demonstrating both personal resilience and professional dedication to advancing software engineering practices.
Dietmar Winkler is a Lecturer at the Information Systems Engineering department of Vienna University of Technology. His research centers on quality assurance in software and systems engineering, particularly for cyber-physical production systems. Research focuses on model-based testing, risk analysis in production systems, and quality improvement across engineering lifecycles. Recent work emphasizes test-driven validation methods and multi-disciplinary engineering integration. Winkler has received recognition for work-life balance research contributions and leads projects in software quality for industrial automation systems.
Thomas Rausch is an External Researcher and former University Assistant at TU Wien's Distributed Systems Group (Faculty of Informatics). He holds a PhD in Computer Science (2021) and master's degree in Software Engineering from TU Wien (2016). His work focuses on edge computing, cloud engineering, and AI systems, with notable contributions to frameworks like LocalStack and CognitiveXR. Education: M.Sc. in Software Engineering & Internet Computing (2016), Ph.D. in Computer Science (2021 – TU Wien). Research Interests: Edge computing systems, distributed interactive systems, cognitive augmentation, and cloud-edge AI integration. He has pioneered privacy-preserving edge systems and serverless platforms for data-intensive workloads. Publications: Over 20 peer-reviewed articles on edge computing frameworks, privacy-aware systems, and large-scale AI operations. Recent work includes faas-sim (2023) and Mobility-Aware Serverless Adaptions (2022). Awards: SEC 2019 Best Demo Award, 2020 Netidee Grant, Finalist TU Wien Teaching Awards. Grants: Netidee Grant (2020), CPS/IoT Ecosystem collaboration (2019–present). Teams: Founded CognitiveXR (edge-AI platform) and co-founded LocalStack (serverless testing).
Henderik Proper is a Full Professor of Business Informatics at TU Wien's Faculty of Informatics, leading the Research Unit in Business Informatics. He holds roles as Head of Research Unit, Faculty Council Substitute Member, and Curriculum Commission Principal Member. His expertise spans enterprise architecture, digital transformation, and conceptual modeling. Education: Holds a PhD and has held academic positions at TU Wien and previously at the University of Nijmegen. Research focuses on enterprise modeling, AI-driven systems, and governance frameworks. He leads projects like INTEND (2024–2026) and MFP 4.2 (2022–2023), emphasizing digital twin integration and low-code applications. Publications: Over 50 peer-reviewed articles in top venues like Springer and IEEE, focusing on enterprise engineering, process mining, and AI applications. His work bridges theory and practice, addressing challenges in digital transformation and model-driven architectures. Grants: Active in EU-funded projects (INTEND) and national initiatives (MFP 4.2). Advises on doctoral theses and teaches courses like 'Enterprise & Process Engineering' and 'Ontology-Driven Conceptual Modeling'. Labs/Teams: Leads research groups on enterprise architecture and digital systems within TU Wien's Informatics department, collaborating internationally on standards like ArchiMate extensions.
Prof. Gerald Steinbauer-Wagner is an Associate Professor at TU Graz's Institute of Software Engineering and Artificial Intelligence. He specializes in autonomous intelligent systems, focusing on decision-making architectures for robots in uncertain environments. His research integrates software engineering, AI, and robotics to develop reliable systems for applications in disaster response, planetary exploration, and industrial automation. Research Interests: Steinbauer-Wagner's work addresses challenges such as robot navigation in unstructured terrains, human-robot collaboration, and trustworthiness in autonomous systems. Key areas include explainable AI, fault diagnosis, and multi-robot coordination. His team explores solutions for off-road robotics, collective perception, and certification of autonomous systems. Recent Projects: Current initiatives include developing autonomous systems for subterranean rescue missions (ROBO-MOLE), optimizing robot localization using machine learning, and creating educational frameworks for AI literacy in schools. His group also contributes to the RoboCup Logistics League and planetary exploration cascades through analog missions like AMADEE-20. Awards & Recognition: No specific awards listed, but his work has been recognized through extensive publications in top venues like IEEE/RSJ IROS, ICRA, and RoboCup symposiums. Lab & Teams: Leads the Autonomous Intelligent Systems (AIS) research group at TU Graz, collaborating with industry partners like the Smart Factory. His team develops integrated robot systems for production, logistics, and disaster response scenarios.
Stefan Emrich is affiliated with the Institute of Urban Design, Landscape Architecture, and Design at TU Wien. His research focuses on applying simulation models to urban planning, facility management, and crisis response. He holds a Dipl.-Ing. (Diplom-Ingenieur) and Dr.techn. (Doctor of Technical Sciences). Research Interests: Emrich specializes in agent-based modeling, discrete event simulation, and space utilization optimization. His work addresses pandemic planning, energy-efficient manufacturing, and sustainable building design. He has contributed to projects like the MoreSpace initiative for optimizing corporate real estate through computational tools. Projects & Collaboration: He co-led interdisciplinary efforts such as the INFO project on energy optimization in manufacturing (2013) and developed the MoreSpace simulation tool for space management. His recent work includes applying agent-based models to Austria's COVID-19 response strategy (2021). Labs & Teams: Emrich is part of TU Wien's Network Lab , collaborating on simulation-driven solutions for urban and industrial challenges. His research bridges engineering, architecture, and computational science to advance practical applications in resource management and crisis mitigation.
Viktoria Dorfer is a Professor at the University of Applied Sciences Hagenberg, affiliated with the Bioinformatics Center of Excellence and Medical Engineering/TIMed Center HEAL. She holds an ORCID iD (0000-0002-5332-5701) and has published 66 research outputs with an h-index of 9 and 676 citations. 2007–2012: Doctoral research on algorithmic approaches 2013–2016: FWF Translational Research on MS Amanda 2020–2022: PI for b-tastic project Research Interests: Spanning bioinformatics, mass spectrometry, and medical engineering, her work focuses on: Algorithm development for peptide identification Evolutionary algorithms in data analysis Mass spectrometry software platforms (AMANDA, Annika) Cross-linked peptide analysis Precision agriculture applications Medical device optimization 2024 Trends: Recent contributions include symbolic regression in livestock farming, enhanced rescoring platforms, and structural analysis of the C. elegans Box C/D complex. Awards: EuPA Bioinformatics Mass Spectrometry Award (2020) Leadership: Organized Austrian Proteomic Research Symposia (2017), served as reviewer/peer-reviewer for journals, and led interdisciplinary collaborations.
Matthias Meissnitzer serves as a Privatdozent (equivalent to Associate Professor) in the Department of Radiology at Paracelsus Medical University, Salzburg, Austria, with clinical and research activities based at Salzburger Landeskliniken (SALK) hospital. His academic position is evidenced by his Priv.-Doz. title and leadership of university-affiliated research projects. His research centers on advanced diagnostic imaging with distinct emphases: Application of multiparametric MRI for differentiating malignant versus benign testicular masses and breast lesions Patient-centered studies on gender preferences in breast ultrasound examinations Clinical characterization of soft tissue infections and bacterial skin pathologies Innovative 3D printing techniques for vascular modeling in surgical planning These interests reflect his dual clinical-academic role bridging radiology, oncology, and surgical disciplines. Analysis of his 63 research outputs (2008-2025) reveals evolving trends: early work focused on foundational radiological techniques, while recent publications (2023-2025) demonstrate intensified specialization in MRI-driven oncology diagnostics and patient experience optimization. His 2024 testicular lesion studies established MRI as a critical diagnostic tool, while 2023 vascular modeling research pioneered accessible 3D printing applications for surgical simulation. Meissnitzer secured research funding for the 2016 project "MRI as a Tool in the Detection of Early Stage Breast Cancer," which received significant academic attention with coverage in two news outlets and discussion by four Mendeley readers. His collaborative approach is evident across publications, consistently working with multidisciplinary teams including dermatologists, urologists, surgeons, and oncology specialists as reflected in co-authorship patterns.
Philipp Alexander Raith is a PreDoc Researcher and PhD student at the Distributed Systems Group of the Institute of Information Systems Engineering at Vienna University of Technology (TU Wien). His research focuses on edge intelligence, serverless edge computing, and AI operations, with a strong emphasis on resource optimization and infrastructure management across the edge-cloud continuum. BSc in Software Engineering (2018) from TU Wien MSc in Software Engineering & Internet Computing (2021) from TU Wien Research Interests encompass: Edge Intelligence Serverless Edge Computing AI/ML Operations Resource-aware Scheduling Distributed Systems Computing Continuum Publication Trends highlight his work in edge-cloud orchestration, neural feature compression, and quantum computing integration. Key areas include elasticity, serverless frameworks, and energy-aware architectures. Scientific Awards : UCC 2022 Best Paper Award SEC 2019 Best Demo Award 2020 Netidee Grant Winner Shortlisted for TU Wien Distinguished Young Alumnus Advising : Supervised multiple Master’s theses on edge-cloud autoscaling, AI workloads, mobile edge computing, and resource-aware offloading. Projects : Key contributor to AUTO-Cloud (2013–2025) and RAINBOW (2020–2022) projects.
Dr. Muhammad Asfand-e-yar is affiliated with TU Wien's Department of Software Technology and Interactive Systems, part of the E188 institute. His research focuses on applying semantic web technologies to legal and licensing challenges, particularly in software and e-commerce contexts. He holds a doctoral degree (Dr.techn.) and has conducted interdisciplinary work blending ontology engineering with legal informatics. Research Interests : Semantic Web applications, ontology development for legal domains, user-centered design of licensing agreements, and improving clarity of legal texts through computational methods. His work bridges software engineering and legal compliance, with a focus on making complex agreements accessible to end-users. Publications : His research trends emphasize semantic technologies' role in enhancing legal document comprehension, with contributions to ontology-based licensing frameworks and use-case integration in software development. Key areas include e-commerce license agreements, compliance models, and formal methods for legal knowledge representation. Affiliations & Labs : Member of TU Wien's Network Lab, contributing to interactive system design and software licensing research initiatives.
Simon Haller-Seeber is a Systems Engineer at the Department of Computer Science (Intelligent and Interactive Systems) at the University of Innsbruck, a role he has held since 2010. He also serves as a part-time Lecturer in Scientific Computing and Science Education. His academic background includes a Master's degree in Computer Science (2024) and a Bachelor's degree (2006), alongside professional certifications like Engineer Degree (2012) and Apprentice Instructor (2014). Research & Education: Focused on Free Software, System Automation, and Educational Robotics. He co-founded the STAIR-Lab and contributed to initiatives like ROSSINI workshops promoting youth robotics innovation. His work bridges robotics with pedagogy, emphasizing open-source tools and accessible education platforms. Publications: Recent works include web-based robotics IDEs (2025), AI-driven training frameworks (2023), and taxonomies for robotics action models (2019). His 2020 paper on recycling automation won the ROBOVIS Best Paper Award. Grants & Projects: Led EU-funded projects like IMAGINE (2018–2021) and participated in Squirrel/PaCMan (2014–2018). Co-organizes RoboCup Junior and the Computer Camp Malbun. Awards & Roles: Recognized for educational robotics contributions. Active in academic governance as former Senate member and board chair of 'brainity' and 'Natur Mensch Technik' associations.
Enes Bajrovic is a researcher affiliated with the Faculty of Computer Science, focusing on high-performance computing (HPC), big data processing, and performance portability. His work spans task-based parallelism, runtime systems, and optimization frameworks for heterogeneous architectures. He has contributed to major European projects like PEPPHER and AutoTune, which aim to advance HPC software tools and autotuning methodologies. His research emphasizes practical applications of parallel computing in domains such as mobile networks and scientific simulations. Education: Dipl.-Ing. Dr.techn., BSc in Computer Science His research interests include developing frameworks for compute- and data-intensive applications, leveraging technologies like Kubernetes, OpenCL, and Intel Xeon Phi coprocessors. He has authored numerous peer-reviewed publications on topics such as pipeline patterns, autotuning algorithms, and hybrid execution models. His work bridges theoretical advancements in parallel computing with real-world software engineering challenges. Bajrovic has collaborated on projects funded by the European Commission’s FP7 program, contributing to deliverables like runtime systems, tuning frameworks, and benchmarking tools. His research also addresses the integration of big data processing with HPC, particularly in telecommunications and distributed computing environments.
