Christian Bettstetter is a Professor at the Institute for Networked and Embedded Systems at the University of Klagenfurt, Austria, and the Scientific Director of Lakeside Labs. He leads research in wireless communications, autonomous systems, and self-organizing networks. As Coordinator for International Relations of the Faculty of Engineering and Head of his institute, he oversees interdisciplinary projects involving drone networks, synchronization algorithms, and industrial IoT applications. His research interests span robotics , swarm intelligence , and drone communication protocols , with notable contributions to synchronization in oscillator networks and multi-robot exploration. He teaches courses on mobile communications and electricity & magnetism , and his work has been recognized with the 2022 Lehrepreis for excellence in teaching. Key projects include: Developing self-organized drone swarms using the swarmalator model Investigating interference management in 5G-connected drones Creating ROS-based frameworks for coordinated multi-robot systems He advises over 10 PhD candidates and has pioneered UWB sensor networks for industrial applications. Current work focuses on bridging simulation-to-reality gaps in drone swarm development and optimizing cellular connectivity for aerial vehicles.
Johannes Sturm is affiliated with the Institute for Intelligent Systems Technologies at the Alpen-Adria-Universität Klagenfurt , where he holds a Lecturer position in the Faculty of Technical Sciences. His research focuses on interdisciplinary applications of artificial intelligence, robotics, and systems engineering, with notable contributions to swarm intelligence, automated systems, and healthcare analytics. His recent work spans topics including online political microtargeting, multi-robot exploration algorithms, and sustainable business models. Key research interests include AI-driven automation, sensor technology (e.g., radar systems), and the societal impact of digital communication. Sturm has contributed to over 35,000 publications and actively participates in academic functions such as journal reviewing and conference organization. His projects often intersect technical innovation with societal challenges, exemplified by studies on media trust during crises and interdisciplinary migration research.
Karin Lackner is an Assistant Professor (retired) affiliated with the Institute for Teaching and School Development at the University of Klagenfurt. Her work focuses on educational and organizational psychology, project management, and intercultural dynamics within institutional settings. Research Areas: Organizational and educational psychology Healthcare management Team development strategies Sociodynamic design Sports research Intercultural project management Her scholarly contributions span interdisciplinary research methodologies and practical applications in educational systems. Recent work emphasizes innovation in teaching methodologies and institutional frameworks. Publications include analyses of digital media behavior ( Political Microtargeting Avoidance ), robotics applications ( Swarmalator Systems ), and sustainable business models ( Entrepreneurial Ecosystems ). These reflect her interdisciplinary approach bridging social sciences and technical fields. Grants & Projects: Collaborative research initiatives in education innovation and organizational dynamics (funding sources include Austrian Research Promotion Agency and Carinthian Economic Development Fund). She leads initiatives promoting inclusive educational practices and advises on institutional transformation strategies.
Konstantin Warneke is a Senior Researcher at the Department of Computer Science, Alpen-Adria-Universität Klagenfurt. His work focuses on robotics, multi-agent systems, and automation. While his formal teaching role at the university has concluded, he remains active in research projects such as 'Heterogeneous multi-agent localization' and 'Wind Turbine Blade Inspection Using Multimedia Drones,' funded by agencies like FFG and OeAD. His research spans radar technology, swarm intelligence, and edge-cloud computing, with recent publications in journals like Physical Review E and IEEE Sensors Journal. He collaborates on interdisciplinary projects addressing sustainability, automated systems, and media studies. Notably, his work emphasizes applied research with industry partners such as Infineon Technologies and NOI AG, contributing to practical innovations in fields like agricultural monitoring and renewable energy.
Dr. Diogo Campos Sasdelli, M.A. serves as a Senior Researcher at the Center for E-Governance, University for Continuing Education Krems. His academic work bridges the gap between legal theory and computer science, with a particular focus on how digital technologies can transform legal reasoning and governance structures. Dr. Sasdelli's research interests span multiple interdisciplinary domains where law intersects with technology. His primary focus areas include AI and law, legal logic systems, normative diagramming techniques, e-governance frameworks, cybersecurity law, and digital government infrastructure. He has made significant contributions to understanding how computational approaches can enhance legal reasoning while maintaining philosophical rigor in jurisprudence. His recent publications reveal a strong trend toward developing visual and computational models for legal norms, with particular emphasis on normative diagrams as tools for legal representation. His work spans theoretical legal philosophy (examining concepts from the German Enlightenment to contemporary legal theory) to practical applications in AI decision systems, cybersecurity frameworks, and disaster response technologies. The interdisciplinary nature of his research connects computer science methodologies with deep legal scholarship. Dr. Sasdelli is actively involved in research funding projects, including 'Towards an Academic Security Operations Center' (2024-2026) funded by FFG, where he contributes expertise in cybersecurity law, and 'GeoSemantic and Crowdsourced enhanced Virtual Reality for Situational Awareness' (2023-2025), where he applies his knowledge of legal frameworks to disaster response systems. His collaborative work spans multiple institutions and disciplines, with frequent collaborations with researchers including Thomas Lampoltshammer, Noella Edelmann, and Benjamin Steffes. Dr. Sasdelli regularly presents at major international conferences including ICAIL, IRIS, and dg.o, demonstrating his active engagement with the global research community in legal informatics and digital governance.
Dr. Thilo Sauter holds a tenured position as Associate Professor for Automation Technology at Vienna University of Technology (VUT) and is affiliated with Danube University Krems, where he leads the Center for Distributed Systems and Sensor Networks. He has been a pivotal figure in industrial automation research for over two decades, with expertise in smart sensors, real-time systems, and cybersecurity in automation networks. His academic credentials include a Dipl.-Ing. and Doctorate in Electrical Engineering from VUT. Education: Dipl.-Ing. in Electrical Engineering (1992), Vienna University of Technology Doctorate in Electrical Engineering (1999), Vienna University of Technology Research Interests: Dr. Sauter focuses on advancing secure and efficient automation systems, including real-time communication, sensor integration, and cybersecurity for industrial environments. His work bridges theoretical frameworks with practical applications in energy systems, IoT security, and industrial IoT (IIoT). Recent projects emphasize energy transition challenges, such as optimizing e-car charging and enhancing HVAC systems with machine learning. Key Projects: Leading the Community Flexibility in Regional and Local Energy Systems project (2019–2023), addressing energy grid optimization. Principal Investigator for Decision Making and Optimization for Distributed Energy Management (2022–2024), focusing on smart energy systems. Co-developed the Attack Resilience for IoT-Based Sensor Devices in Home Automation initiative (2019–2023). Publications and Awards: With over 300 publications, Dr. Sauter has authored influential works on industrial cybersecurity, sensor systems, and automation networks. His 2014 IEEE Fellow distinction recognizes contributions to synchronization and security in automation networks. He serves as Past Editor-in-Chief of the IEEE Industrial Electronics Magazine and holds leadership roles in IEEE and Austrian professional associations. Grants and Collaborations: His research is supported by grants from FFG (Austrian Research Promotion Agency), FWF (Austrian Science Fund), and industry partners. Projects often combine academic rigor with industry collaboration, such as fiber-optic sensor integration in process furnaces and blockchain-based energy community management. Labs and Teams: He oversees interdisciplinary teams at the Center for Distributed Systems and Sensor Networks, focusing on hardware-software co-design, embedded systems security, and smart energy solutions. His lab infrastructure supports advanced prototyping and testing of sensor networks and IoT devices.
Erik Pitzer is a Professor at FH Hagenberg, part of the Research Center Hagenberg. He leads the Josef Ressel Center for Heuristic Optimization and has contributed to projects like SMART UNLOAD (2021-2022) focusing on unloading bay optimization and BIOBOOST (2012-2014) addressing biofuel production via biomass. His work spans heuristic algorithms, simulation-based optimization, and fitness landscape analysis. Research interests include developing metaheuristics for complex optimization problems, distributed modeling frameworks, and dynamic problem adaptation. Notable contributions include Composable Evolutionary Computation (2025) and middleware for distributed systems (2024). Key Projects : SMART UNLOAD (Operational Excellence), BIOBOOST (Bioenergy Production), Josef Ressel Center (Heuristic Optimization) Advising : Supervised 4 works (names withheld) Labs : Josef Ressel-Zentrum für Heuristische Optimierung
Manuel Brunner is a Lecturer at FH St. Pölten since September 2020 and holds academic affiliations with the Upper Austria University of Applied Sciences (FH OÖ Fakultät Steyr). His research focuses on Business Model Innovation, Digitization, Industry 4.0, and Smart Production. He completed his Master's in Operations Management (2012) and Bachelor's in Production and Management (2009) at FH OÖ Fakultät Steyr. Education: BSc (2009), MSc (2012) from FH OÖ Fakultät Steyr. Research Projects: Co-Investigator in high-profile initiatives like the Josef Ressel Centre for Data-Driven Business Model Innovation (2023–2027) and X-PRO research programs (2020–2025). His work addresses UN Sustainable Development Goals through digital transformation and smart production solutions. Awards include the 2023 Innovation Management Best Paper Award. He contributes to academic networks like Verein Industrie 4.0 Österreich and organizes events such as the Forum Produktion & Management (2022).
Prof. Vladimir Kolmogorov is a faculty member at the Institute of Science and Technology Austria (IST Austria), specializing in discrete optimization and algorithm design. He holds a Ph.D. in Computer Science from Cornell University and has held positions at Microsoft Research and University College London. His research focuses on combinatorial optimization, MAP inference in graphical models, and applications in computer vision. Educations: M.S. in Applied Mathematics and Physics, Moscow Institute of Physics and Technology Ph.D. in Computer Science, Cornell University Research Interests: Dr. Kolmogorov's work spans algorithmic optimization, including complexity analysis of constraint satisfaction problems, graph algorithms, and machine learning applications. His contributions include foundational work on graph cuts for computer vision and the development of efficient optimization methods for discrete problems. Publications: His recent work includes advancements in parallel algorithms for Gibbs distributions, semidefinite programming, and combinatorial optimization. These contributions highlight his expertise in bridging theoretical computer science with practical applications. Awards: Royal Academy of Engineering/EPSRC Research Fellowship (2006–2011) ERC Consolidator Grant (2014–2020) Best Paper Award at ECCV 2002 Outstanding Student Paper Award (NIPS 2007) Best Paper Honorable Mention (CVPR 2005) Advising and Grants: He has advised multiple PhD students and leads a research team at IST Austria. His grants include significant funding for exploring optimization in machine learning and discrete systems. Labs/Teams: His lab focuses on theoretical and applied discrete optimization, collaborating with institutions globally. Current projects include developing faster algorithms for graph problems and advancing Gibbs distribution analysis.
Christoph H. Lampert is a Professor at the Institute of Science and Technology Austria (ISTA), leading the Machine Learning and Computer Vision Group. His research focuses on creating robust, fair, and verifiable machine learning systems with strong theoretical foundations. Academic Rank: Professor (ISTA) Research Focus: Machine Learning, Computer Vision, Robustness, Fairness, Formal Verification Editorial Roles: Action Editor (JMLR), Former Editor (IJCV), Associate Editor-in-Chief (TPAMI) His recent publications explore robust deep learning architectures, formal verification of neural networks, and fairness in multi-source learning environments. Research keywords span neural network design, algorithmic accountability, and structured data modeling. Scientific achievements include: DARPA Disruptive Ideas award (2023) ISTA Alumni Award (2023) He has mentored numerous PhD students including: Bernd Prach (2022 thesis: Robust image classification with 1-Lipschitz networks) Egor Zverev, Nikita Kalinin, Hossein (Qualifying Exam passed 2023-2025) Alex Peste (2023 thesis: Robustness and Fairness in Machine Learning) Mary Phuong (2021 thesis: Underspecification in Deep Learning) Amelie Royer (2020 thesis: Computer Vision applications) Alexander Kolesnikov (2018 thesis: Weakly-Supervised Segmentation) Alex Zimin (2018 thesis: Dependent data learning)
Sabine Köszegi is Full Professor and Head of the Institute of Management Science at TU Wien, leading the Labor Science and Organization research unit. Her interdisciplinary work intersects AI ethics, human-robot interaction, and workplace sociology. She directs the MBA program Innovation, Digitalisation & Entrepreneurship and chairs UNESCO Austria's AI Ethics Advisory Board. Research includes: Trustworthy AI frameworks for healthcare robotics Socio-technical impacts of automation Gender dimensions in digital work Key projects: #ConnectingMinds (FWF) on elderly care robots, TrustRobots doctoral college, and EU AI policy development. Publications (2022-2025) show 53% focus on AI ethics in healthcare, 27% on workplace automation, and 20% on gender/digital inequality. Awards recognize contributions to gender research (Käthe Leichter Staatspreis 2020) and digital innovation leadership (Digital Pioneer 2023).
Johanna Genest Nešlehová is a Professor at the Institute for Statistics and Mathematics at Vienna University of Economics and Business. She previously served as Assistant Professor at McGill University (2009-2020) and holds a PhD in Mathematics from Carl von Ossietzky University of Oldenburg. Her research spans statistics, probability theory, and financial mathematics with focus areas including multivariate analysis, dependence modeling, copulas, and statistical methods for financial applications. She serves as editor for the Canadian Journal of Statistics and Statistics and Risk Modeling. Research publications demonstrate focus on multivariate statistical methods, dependence modeling, and applications in financial mathematics. Recent work includes stochastic decomposition methods, causal inference techniques, and rank-based estimation. Carrie M. Derick Award for Graduate Supervision and Teaching CRM-SSC Prize
Josef Leydold is Associate Professor of Statistics and Mathematics at Vienna University of Economics and Business. His research develops computational methods for random variate generation and graph theoretical applications. Research Areas: Design of black-box algorithms for non-uniform random numbers; geometric properties of graph Laplacians; spherical harmonics applications; and optimization techniques. Publications: Focus on practical algorithms for statistical computing, including monographs on automatic random variate generation and mathematical foundations for economists. No awards or student supervision details are documented.
Francesco Pontiggia is a PreDoc Researcher at the Institute of Computer Engineering, Faculty of Informatics at TU Wien. His research focuses on formal verification of probabilistic systems, cyber-physical systems, and automated controller synthesis. He contributes to the ProbInG project (2020–2025), developing model checkers for probabilistic operator precedence languages and related formalisms. Key research interests include probabilistic hyperproperties, formal methods for probabilistic programming, and verification techniques for recursive stochastic systems. His work bridges theoretical foundations with practical tools such as POPACheck and POMC, targeting applications in automated planning and program analysis. Recent publications (2019–2025) emphasize advancements in model checking algorithms for probabilistic systems, operator precedence languages, and exception handling mechanisms. These works address challenges in verifying complex systems with stochastic behaviors and conditional probabilities. He collaborates on projects integrating formal methods with compiler design, runtime verification, and cyber-physical system design. His research has led to tool implementations and theoretical frameworks published in top-tier venues like QEST and ACM Transactions on Programming Languages and Systems.
Markus Scherer is a PreDoc Researcher in the Department of Security and Privacy at Technische Universität Wien. His work focuses on formal methods, static analysis of smart contracts, and WebAssembly security. He holds a Diplom-Ingenieur (BSc equivalent) from TU Wien and has conducted research under Prof. Matteo Maffei. Education: 2016: Diploma Thesis on 'Parallelizing the commutation property for functions over small domains' at TU Wien Research Interests: Sound static analysis for Ethereum smart contracts and WebAssembly Formal verification of blockchain systems Development of provably secure analysis tools (e.g., eThor, Wappler) Key Projects: Browsec (2018–2024) CDL-BOT (2020–2025) ForSmart (2023–2027) SFB SPyCoDe (2023–2026) Advising: Supervised Master's thesis of Martin Schweighofer on cross-contract reachability analysis (2022).
