Holger Hermanns

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About

Holger Hermanns is a leading figure in formal methods and probabilistic verification, with a career dedicated to advancing the theoretical and practical foundations of reliable and secure systems. His research spans probabilistic model checking, stochastic process algebras, and the verification of cyber-physical systems, where he has pioneered techniques for analyzing systems that exhibit random or nondeterministic behavior. A landmark contribution is his work on "Probabilistic CTL*: The Deductive Way" (2016), which provides a deductive framework for reasoning about probabilistic temporal logics, laying groundwork for automated verification tools. While his most-cited paper has garnered 9 citations, reflecting its specialized impact, his broader body of work—including foundational contributions to tools like the Modest Toolset—has shaped the field. More recently, Hermanns has ventured into adversarial machine learning, co-authoring "Eidos" (2024) and its expanded version (2025), which introduce efficient, imperceptible attacks on 3D point clouds, demonstrating his adaptability to emerging challenges in AI security. His achievements include leading the European Research Council’s Advanced Grant project on probabilistic verification, underscoring his sustained influence in making complex systems provably correct.