Pavel Nedvedicky is a researcher at the Chair of Software Engineering (Prof. Stefan Wagner) within the Technical University of Munich's Informatics faculty. He focuses on enhancing safety in autonomous driving systems through scenario-based testing methodologies, system-theoretic analysis, and virtual simulation techniques. His work bridges academic research with industrial practice, particularly in addressing validation challenges for autonomous systems. Research Interests: Safety of ADAS/ADS systems Scenario-based testing frameworks and critical scenario identification System-Theoretic Process Analysis (STPA) DevOps integration in continuous testing He actively supervises student theses in these areas, emphasizing collaboration with industry partners. Current open topics include a survey on industrial adoption of scenario-based testing for autonomous driving systems. His research contributes to closing gaps between theoretical advancements and real-world deployment challenges in autonomous vehicle validation.
Eva Zimmermann is affiliated with the Chair of Software Engineering at the Technical University of Munich (TUM), led by Prof. Stefan Wagner. Her primary role involves research and teaching within the Informatics Heilbronn department. She focuses on Autonomous Driving, Automotive Safety (particularly STPA methodologies), and DevOps practices with an emphasis on Continuous Monitoring. Research interests include advancing safety frameworks for autonomous systems and integrating DevOps principles into software engineering workflows. She expresses openness to supervise bachelor's and master's theses in alignment with her research areas, including industry collaborations. Affiliated with the Bildungscampus 2 location in Heilbronn, her contact details are publicly available via e.zimmermann@tum.de.
Valeriy Vyatkin is a Professor at Aalto University's Department of Electrical Engineering and Automation within the School of Engineering. He also maintains an affiliation with Luleå University of Technology in Sweden. His research spans industrial automation, distributed control systems, and digital transformation of manufacturing processes. Vyatkin leads a significant research group focusing on next-generation industrial control architectures and has established himself as a leading authority in the IEC 61499 standard for distributed industrial automation systems. Professor Vyatkin's research interests center around industrial automation systems with particular emphasis on distributed control architectures, formal methods for verification of industrial control systems, and digital twin technologies. His work bridges theoretical computer science with practical industrial applications, developing methods for model checking, virtual commissioning, and formal verification of industrial automation systems. He has pioneered approaches for applying reinforcement learning to industrial process control, particularly in steel manufacturing and energy systems. His recent work explores the integration of generative AI with industrial control systems, focusing on rapid prototyping and code generation for IEC 61499 applications. The analysis of Professor Vyatkin's recent publications (2023-2025) reveals a strong research trajectory focused on advancing industrial automation through multiple complementary approaches. His work demonstrates a consistent emphasis on the IEC 61499 standard as a foundation for distributed control systems, with growing integration of AI techniques, particularly generative models and reinforcement learning. A notable trend is the progression from theoretical foundations toward practical implementation frameworks, with increasing attention to security, privacy, and human factors in industrial settings. His research group has expanded into new application domains including energy systems, horticulture, and nuclear instrumentation while maintaining core expertise in manufacturing automation. Professor Vyatkin has made significant contributions to the field through his editorial work, including serving as guest editor for special issues in IEEE Transactions on Industrial Informatics. His research has been supported by multiple grants from national and international funding agencies focusing on industrial digitalization and smart manufacturing initiatives. Professor Vyatkin actively supervises numerous PhD and Master's students, with a consistent research group of 8-10 students and postdoctoral researchers. His advising approach emphasizes both theoretical rigor and industrial relevance, with many students collaborating directly with industry partners. His research group has established collaborations with major industrial players in manufacturing, energy, and automation sectors across Europe. The research activities are centered around the Industrial Automation research group at Aalto University, which maintains strong connections with the international IEC 61499 community. The team operates a dedicated laboratory for industrial automation research with capabilities for virtual commissioning, digital twin development, and formal verification of control systems. The group participates in multiple European research projects focused on Industry 4.0 and 5.0 technologies, with particular emphasis on human-centric automation and secure industrial systems.
