Cornelia Lex is an Associate Professor at Graz University of Technology's Institute for Vehicle Engineering. Her work focuses on vehicle dynamics, tire-road interaction, and human-machine interaction in automated driving systems. She employs advanced modeling and control strategies for tire mechanics, friction estimation, and safety-enhancing driver assistance technologies. Academic Affiliation: Graz University of Technology Research Areas: Vehicle dynamics, tire modeling, friction estimation, automated driving Contact: cornelia.lex@tugraz.at Her research spans tire wear emissions, sensor fusion for vehicle state estimation, and environmental impact analysis of transportation systems. Recent publications address tire wear particle distribution, online tire modeling, and water detection systems for automated driving. She leads projects funded by the Austrian Society of Automotive Engineers (ÖVK) and contributes to multidisciplinary development of driving simulators and driver assistance systems.
Gabriele Kotsis is a Full Professor at the Institute of Telecooperation, Johannes Kepler University Linz, with extensive contributions to Artificial Intelligence research. Her institutional presence spans multiple departments through interdisciplinary projects while maintaining her primary affiliation with JKU's engineering-focused research units. Her research expertise encompasses: Natural Language Processing and Neural Machine Translation systems Reinforcement Learning applications for Smart Grid optimization Mobile Computing and Multimedia Intelligence frameworks Big Data Analytics and Database Systems innovation Human-centered AI development methodologies Recent publications (2024-2025) reveal a strategic focus on practical AI implementations addressing multilingual communication barriers and energy efficiency challenges. Her work consistently bridges theoretical AI advances with real-world applications across multiple domains. Professor Kotsis maintains an active supervision record with thesis guidance and leads multiple funded research initiatives. Her current portfolio includes: 'Enhancing Neural Machine Translation' project (2025-2026) for Southeast Asian languages 'INTES' regulatory compliance ecosystem (2023-2026) 'Human-centered Artificial Intelligence' initiative (2022-2026) Through her leadership in international conferences (iiWAS, MoMM, DEXA) and editorial roles for major proceedings, she maintains significant influence in the global computer science research community while advancing JKU's research profile.
Chen Xihui, Ph.D., is a Researcher at the Institute of Creative\Media/Technologies within the Department of Media and Digital Technologies at the University of Applied Sciences St. Pölten. His work focuses on media computing and digital technologies, with specialized expertise in cybersecurity frameworks. Primary research domains include: Federated learning systems and their security vulnerabilities Robustness of recommendation algorithms against adversarial attacks Privacy-preserving machine learning architectures Competitive data poisoning mitigation strategies Recent scholarly work demonstrates concentrated focus on security challenges in federated recommendation systems, particularly examining attack vectors and defensive mechanisms in distributed learning environments.
Dorian Achim Prill is a Researcher at the School of Information Technology and Systems Management, Salzburg University of Applied Sciences, specializing in digitization and digital transformation within Industry 4.0 contexts. He serves as Deputy Project Manager for DIH-West-Neu (2024-2028) and contributes to multiple funded research initiatives including Retailization 4.0 and RetailLab4.0, focusing on practical implementations of digital technologies in production and retail environments. His research integrates Machine Learning and Data Science with industrial maintenance systems, developing intelligent frameworks for predictive maintenance scheduling and service choreography. Key interests include Publish-subscribe architectures, Learning Systems for production optimization, and Planning Frameworks that bridge theoretical models with real-world manufacturing applications. His work emphasizes data-driven process monitoring and cloud-based intelligence for industrial IoT ecosystems. Recent publications demonstrate a clear trajectory toward applied machine learning in maintenance engineering, with increasing focus on smart factory implementations and service-oriented architectures. The research consistently connects broad computer science principles with specific industrial subfields like friction coefficient measurement for vehicle safety and retail digitalization. Prill actively participates in externally funded projects totaling 11 initiatives since 2017, securing grants for Digital Innovation Hubs and living labs. His collaborative approach involves interdisciplinary teams across academia and industry, particularly evident in RetailLab4.0's living lab environment and FriCamMod's vehicle safety research. He has shared expertise through invited lectures on data-driven maintenance planning and marine maintenance intelligence. He operates within dynamic project teams including RetailLab4.0's retail digitalization consortium and FriCamMod's vehicle safety collaboration, working closely with principal investigators like S. Kranzer and R. Zniva. Current projects emphasize scalable digital transformation frameworks for both manufacturing and retail sectors through the DIH-West-Neu initiative.
