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Vaandrager’s PhD thesis shaped the research field that investigates general formats for structural operational semantics. During his PhD studies,he obtained several other high impact results on concurrency theory, not included in his thesis, such as Petri net models for process algebras (with Van Glabbeek), an algorithm for branching bisimulation (with Groote), and logical characterizations of branching bisimulation equivalence (with De Nicola).As a postdoctoral fellow at MIT, his attention shifted to assertional frameworks for the description and analysis of computing systems. At MIT he wrote three influential papers with Lynch (2nd most cited paper Information& Computation 1995) on the classification of forward and backward simulation proof techniques. The collaboration with Lynch was continued after he left MIT. Together with Lynch, Segala (Verona) and Kaynar (CMU), he further developed the highly influential I/O automata system modeling framework (15 papers, most cited paper Information & Computation 2003 ).At Radboud University, he became interested in model checking of timed automata. Within the EU AMETIST project (which he coordinated) and other EU projects, he worked with Larsen’s team (Aalborg) on various extensions that have been implemented in the Uppaal tool, such as minimal cost reachability, symmetry reduction, parametric and distributed model checking (25 papers). In part due to these efforts, Uppaal is now routinely used for industrial case studies and has thousands of users, both in academia and industry. He has been and is involved in more than 25 EU and national projects devoted to the application of formal methods to areas such as security and network protocols, embedded software, scheduling, performance analysis, and legacy software. Since 2010, his research has shifted to active automata learning. Vaandrager’s team is internationally leading is this fast growing area, with publications in high impact venues (e.g. CONCUR,FM, iFM, CAV, Machine Learning, FMSD, CACM) both on theoretical advances and on applications in software engineering, for instance in areas such as network protocols, banking cards and legacy software. Vaandrager’s team collaborates with several other leading researchers, e.g. the teams of Steffen &Howar (Dortmund), Jonsson (Uppsala), Bloem (Graz) and Silva (University College London). Recently, Vaandrager’s team developed the L# algorithm,a new and fast approach for active automata learning.
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ICGIpp.157-180, (2023)
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CoRR (2023): 33-49
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Theoretical Computer Science (2022): 37-55
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