Speaker
Ezio Bartocci
Professor at TU Wien, Vienna, Austria
Bio
Ezio Bartocci is a Full Professor at TU Wien and his work lies at the intersection of formal methods, quantitative reasoning, and AI-driven cyber-physical systems. He leads the Trustworthy Cyber-Physical Systems (TrustCPS) Research Group (https://trustcps.eu), where his research seeks to reconcile learning, autonomy, and uncertainty with formal methods, enabling cyber-physical systems that are not only intelligent, but also provably safe, energy-aware, and sustainable. His work is supported by a broad portfolio of competitive European, national, and industry-funded projects, in which he regularly serves as (co-)principal investigator, scientific coordinator, or work-package leader. He has contributed to numerous EU, FWF, FFG, WWTF, and industrial initiatives addressing quantitative verification, performance analysis under uncertainty and runtime monitoring. These projects span topics such as frequency-aware testing, probabilistic programming, reinforcement learning with normative guarantees, explainable AI, and trustworthy autonomous CPS, consistently bridging theory and practice by translating formal models into deployable methods for complex real-world systems. Prior to joining TU Wien, he was a Postdoctoral Researcher at Stony Brook University, where he worked on computational models of cardiac dynamics. This interdisciplinary experience continues to shape his view of cyber-physical systems as living, interacting entities, in which computation, physics, and learning co-exist. He joined TU Wien in 2012 and was promoted to Full Professor in 2020. Beyond his research contributions, Ezio Bartocci currently serves as Chair of the Doctoral College on Trustworthy Autonomous Cyber-Physical Systems, Vice-Chair of the Marie Skłodowska-Curie COFUND doctoral programme LogiCS@TU Wien, and Research Focus Coordinator for Computer Engineering at TU Wien. His work has received several distinctions, including Best Paper Awards at EMSOFT 2025, QEST 2022, and RV 2011, the Radhia Cousot Young Researcher Award 2022, and the EASST Best Software Science Award at ETAPS 2022.