Probabilistic model checking Professors and Supervisors

Radu CalinescuView profile

Professor

Max Planck Institute for Security and PrivacyGermany

Radu Calinescu is Professor of Computer Science at the University of York, UK, where he serves as Principal Investigator for the UKRI Trustworthy Autonomous Systems Node in Resilience and leads the Trustworthy Adaptive and Autonomous Systems and Processes (TASP) Research Team. His academic career includes previous positions as Lecturer in Computer Science at Aston University (2009-2012), Senior Researcher at the University of Oxford (2008-2009), and part-time Lecturer at Oxford (2005-2009). Professor Calinescu's research focuses on formal modelling, analysis, verification and controller synthesis for autonomous and self-adaptive systems, with particular emphasis on parametric and probabilistic model checking, automated and model-driven software engineering. His work applies these approaches to robotic, cyber-physical, embedded and service-based systems, with a strong commitment to using formal methods at runtime to enhance the resilience and safety of critical autonomous systems. His extensive publication record spans top-tier journals including IEEE Transactions on Software Engineering, Journal of Systems and Software, and Automated Software Engineering. His research demonstrates consistent focus on verification techniques for adaptive systems, with increasing attention to safety-critical applications in recent years. His work bridges theoretical formal methods with practical applications in robotics and autonomous systems. British Computer Society Distinguished Dissertation Award for his DPhil thesis on Autonomic-Independent Loop Parallelisation Principal Investigator for multiple major projects including Continual Verification and Assurance of Robotic Systems under Uncertainty (ORCA Hub/EPSRC), Safety of AI Techniques (AAIP/Lloyd's Register Foundation), and CSI:Cobot Program Committee Co-Chair for major conferences including SEFM 2021, SEAMS 2020, and SERENE 2019 Professor Calinescu actively supervises numerous PhD students and postdoctoral researchers, with current team members including Faisal Alhwikem, Xinwei Fang, Mario Gleirscher, James Harbin, and Colin Paterson. His research group is based at the Ron Cooke Hub in York, a purpose-built facility housing world-class research groups and startups. His former students have gone on to academic positions at institutions worldwide and industry roles at major technology companies.

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Antonio FilieriView profile

Visiting Associate Professor

Max Planck Institute for Security and PrivacyGermany

Antonio Filieri is a Senior Applied Scientist at Amazon Web Services (AWS) and holds a Visiting Associate Professor position at the Department of Computing, Imperial College London. Previously, he was a tenured Associate Professor at Imperial College London (2022-2024) and Assistant Professor (2016-2022), and served as Assistant Professor at the University of Stuttgart between 2013 and 2015. His academic career spans over a decade with significant contributions to software engineering research. Dr. Filieri's research focuses on formal mathematical methods for software design, verification, self-adaptation, and security. His primary research areas include static analysis, privacy, and automated test generation for security; exact and approximate methods for probabilistic program analysis; control theory for adaptive software; quantitative verification and model checking; and runtime-efficient and incremental verification. His work bridges theoretical foundations with practical applications in industry settings, particularly in cloud computing and security domains. His recent publications demonstrate a strong focus on probabilistic methods for software analysis, security testing, and performance modeling. The research trends show increasing integration of formal methods with machine learning techniques, particularly in test oracle generation and neural network analysis. There's also a clear emphasis on scalability and practical applicability of verification techniques to real-world systems like serverless computing and microservices architectures. Dr. Filieri has received numerous prestigious awards for his contributions: Best Student Paper Award (2025) for 'Robust Probabilistic Model Checking with Continuous Reward Domains' ACM Distinguished Paper Award (2023) for 'Sibyl: Improving Software Engineering Tools with SMT Selection' Best Paper Award (2022) for 'Enhancing Performance Modeling of Serverless Functions via Static Analysis' Best Artifact Award (2017) for 'Self-adaptive video encoder: comparison of multiple adaptation strategies made simple' Most Influential Paper Award (awarded at SEAMS 2025) for 'Software Engineering Meets Control Theory' ACM SigSoft Distinguished Paper Award (2011) for 'Run-time Efficient Probabilistic Model Checking' Dr. Filieri has advised several PhD students including Donato Clun (2024), Runan Wang (2024), and Xiaotong Ji (expected 2025). His advising focuses on probabilistic program analysis, automated testing, and security verification. His research has been supported by significant grants from both academic and industry sources, enabling collaborations across multiple institutions and contributing to advancements in software engineering practices. While specific lab information isn't prominently featured in the provided materials, Dr. Filieri's work suggests strong connections with research groups focused on formal methods, software verification, and adaptive systems at both Imperial College London and AWS. His research often involves interdisciplinary collaboration between theoretical computer science and practical software engineering challenges.

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Antonio Salmerón CerdánView profile

Professor

University of AlmeríaSpain

Antonio Salmerón Cerdán is a Professor in the Mathematics Department at the University of Almería, where he has established himself as a leading researcher in probabilistic artificial intelligence and Bayesian networks. With over 25 years of academic experience, he leads the 'Análisis de datos' research group and serves as Principal Investigator for multiple nationally and internationally funded projects, including the current 'Hacia una Inteligencia Artificial Probabilística Confiable (TOPAI-UAL)' project (2023-2026). His research expertise spans theoretical and applied aspects of probabilistic graphical models, with particular focus on Bayesian networks, causal inference, and their applications across diverse domains. His work demonstrates a consistent trajectory from foundational theoretical contributions to practical implementations in software engineering, genomics, sports analytics, and trustworthy autonomous systems. Professor Salmerón's publication portfolio reveals a strong emphasis on methodological innovations in probabilistic reasoning, with recent work exploring divide-and-conquer approaches for causal computation, noise-robust classification methods, and the integration of observational and randomized data sources. His research shows increasing interdisciplinary reach, connecting computer science methodologies with applications in plant genomics, software maintenance, and healthcare. Journal Publications: 105 articles in high-impact venues including Ecological Informatics (Q1), International Journal of Approximate Reasoning (Q2), and ACM Transactions Research Funding: Principal Investigator for 9 major projects since 2001 totaling over €800,000 in funding Thesis Supervision: Director of 7 doctoral theses on probabilistic graphical models and their applications Metrics: h-index 22 (Web of Science), i10 index 59 His research program demonstrates a unique combination of theoretical rigor in probabilistic reasoning with practical applications across diverse scientific domains, positioning him at the forefront of reliable probabilistic AI development.

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Marie-Christine ROUSSETView profile

Professor

ENSAE ParisFrance

Marie-Christine ROUSSET is a Professor of Computer Science at the University of Grenoble Alpes (UGA) in France, where she is a member of the LIG (Laboratoire d'Informatique de Grenoble) in the SLIDE group. Previously affiliated with Paris-Saclay (LRI), she has established herself as a leading researcher in Knowledge Representation and Information Integration. She holds the distinguished position of Senior member of the Institut Universitaire de France (IUF) (2011-2016, renewed for 2016-2021) and serves as co-responsible for the chair Explainable and Responsible AI within MIAI Grenoble Alpes. Her research focuses on ontology-based data access, logic-based mediation between distributed data sources, query rewriting using views, data linkage, and distributed reasoning for the Semantic Web. She skillfully combines artificial intelligence and database techniques to address complex information integration challenges, with applications spanning biomedical informatics, educational technology, and trustworthy AI. Her work demonstrates consistent innovation from foundational research to practical implementations, as evidenced by her co-authorship of the book 'Web Data Management' published by Cambridge University Press. Professor ROUSSET's recent publications (2019-2022) reveal a growing emphasis on data privacy, RDF graph anonymization, and interactive ontology engineering, while maintaining her strong contributions to semantic web technologies and knowledge representation. Her research shows increasing attention to trustworthy AI concerns, aligning with her leadership roles in relevant projects. Scientific Recognition Senior member of Institut Universitaire de France (IUF) (2011-2016, renewed for 2016-2021) Junior member of Institut Universitaire de France (IUF) from 1997 to 2002 Chevalier de l'Ordre National du Merite (July 11, 2011) EurAI Fellow (nominated ECCAI Fellow in 2005) Best Paper Award at AAAI'96 for 'Verification of Knowledge Bases based on Containment Checking' Professor ROUSSET maintains an active role in the scientific community through editorial work and organizational leadership. She serves on the Editorial Board of Communications of the ACM (CACM) and has held significant roles including PC chair of EGC 2019, Workshops co-Chair of WWW 2018, and Area Chair of IJCAI 2017. Her consistent service on program committees of major international conferences demonstrates her standing in the field. Her laboratory, the SLIDE group within LIG, focuses on semantic web technologies, knowledge representation, and data integration. The group maintains strong connections with the international research community and participates in collaborative projects addressing cutting-edge challenges in artificial intelligence and data management, with particular emphasis on trustworthy and explainable AI systems.

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Olivier SerreView profile

Professor

ENSAE ParisFrance

Olivier Serre is a CNRS Research Director working at the Institute for Research in Fundamental Computer Science (IRIF), a joint research unit of CNRS and University of Paris. Since September 2021, he serves as Deputy Scientific Director at the Institute for Information Sciences and Technologies (INS2I) at CNRS. His research focuses on theoretical computer science with particular emphasis on automata theory and formal verification frameworks. Dr. Serre completed his education at ENS Cachan (1999-2003) and earned his PhD in Computer Science from Paris-Diderot University (now University of Paris) in 2004. Following a postdoctoral position at RWTH Aachen, he joined LIAFA (now IRIF) as a research fellow in 2005 and became a CNRS Research Director in 2016. His academic journey reflects deep engagement with foundational theoretical problems and their practical verification applications. His research centers on automata theory and formal languages, with particular expertise in games and logic, infinite structures, and verification of higher-order functional programs. Dr. Serre has made significant contributions to collapsible pushdown systems, recursion schemes, and parity games, bridging theoretical foundations with practical applications in program verification. His work demonstrates exceptional depth in developing decision procedures for complex verification problems previously considered intractable. Dr. Serre's extensive publication record in premier theoretical venues shows consistent contribution to advancing the state of the art. His research trajectory reveals a clear evolution from foundational automata theory toward increasingly sophisticated systems involving higher-order computation and imperfect information, with notable breakthroughs in establishing decidability results for complex verification problems.

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Hiroshi UnnoView profile

Professor

IMDEA Software InstituteSpain

Hiroshi Unno is a Professor at Tohoku University 's Research Institute of Electrical Communication and a Visiting Professor at the National Institute of Informatics. He has served on program committees for major conferences like POPL , PLDI , ICFP , and CAV . Dr. Unno's research focuses on Programming Languages Software Verification Artificial Intelligence Higher-Order Model Checking Refinement Type Systems Temporal Logic His recent work (2023-2025) includes advancements in algebraic effects , probabilistic program verification , and prophecy-based type systems . Key contributions appear in POPL , PLDI , and ICFP journals. Scientific awards include Distinguished Paper Award at POPL 2024 Distinguished Paper Award at POPL 2023 PPL 2014 Best Paper Award He leads development of tools like RCaml , Thrust , and EffCaml for refinement type checking. Current projects involve Kakenhi grants 20H04162 and 25H00446 . Dr. Unno actively contributes to academic communities through Program Committee roles at AAAI, CAV, and SAS Editorial work for IPSJ Transactions Organizing PPL Summer School (2022)

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Alexandra SilvaView profile

Professor

IMDEA Software InstituteSpain

Alexandra Silva is a Professor of Computer Science in the Department of Computer Science at Cornell University's College of Engineering. She joined Cornell as faculty in 2021 after previously serving as a Royal Society Wolfson Fellow and Professor of Algebra, Semantics, and Computation at University College London. Her research spans programming languages, formal verification, and theoretical computer science, with particular focus on Kleene Algebra with Tests (KAT), probabilistic programming, and automata theory. She has held numerous leadership roles in major programming languages conferences including POPL, PLDI, and ICFP. Dr. Silva completed her PhD at Centrum Wiskunde & Informatica (CWI) in Amsterdam under the supervision of Jan Rutten and Marcello Bonsangue, with her thesis entitled "Kleene coalgebra" defended in December 2010. Prior to her PhD, she was an undergraduate student at University of Minho in Portugal, where she completed a 5-year Mathematics and Computer Science degree in May 2006. Her research focuses on the modular development of specification languages and algorithms for models of computations, often from the unifying perspective offered by coalgebra. She has made significant contributions to Kleene Algebra with Tests, probabilistic programming semantics, network verification, and automata learning. Her work bridges theoretical foundations with practical verification tools, particularly in the domain of Software-Defined Networking where her NetKAT framework has gained significant attention. Analysis of her recent publications reveals a strong trend toward unifying frameworks for program verification, particularly through her development of Outcome Logic which provides foundations for both correctness and incorrectness reasoning. Her work increasingly integrates probabilistic and concurrent aspects of programming languages, with applications to network verification and security. The NetKAT ecosystem remains a central theme, with extensions to infinite state verification, symbolic execution, and learning-based approaches. Distinguished paper award for Guarded Kleene algebra with tests: verification of uninterpreted programs in nearly linear time (POPL 2020) Dr. Silva advises a large research group with numerous PhD students, postdocs, and undergraduate researchers. Her group has produced significant work in programming languages theory, verification, and applications to networking. She has secured substantial research funding through various grants that support her work on formal methods for network verification and probabilistic programming. Her mentoring approach emphasizes both theoretical depth and practical impact, with many of her students moving to prestigious academic and industry positions. Her research group, spanning both Cornell University and University College London, focuses on developing theoretical foundations for programming languages with practical applications in network verification, probabilistic systems, and program analysis. The group maintains active collaborations with researchers at CWI, University of Oxford, and other leading institutions in programming languages and formal methods.

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Gul AghaView profile

Professor

Menlo CollegeUnited States

Gul Agha is a distinguished Professor of Computer Science at the University of Illinois at Urbana-Champaign and Director of the Open Systems Laboratory. His career spans over three decades of pioneering research in concurrent and distributed computing systems. Professor Agha's research focuses on the actor model of computation, formal methods, and statistical model checking. His work bridges theoretical foundations with practical applications in distributed systems, programming languages, and verification techniques. He has made seminal contributions to understanding concurrent computation through his development of the actor model framework. His publication record shows consistent contributions from the 1980s through the present, with recent work focusing on verification of safety-critical systems, serverless computing optimization, and advanced techniques for distributed actor systems. The trend in his research demonstrates a progression from theoretical foundations to practical applications in modern computing environments including cloud infrastructure and IoT systems. His scientific achievements have been recognized with numerous prestigious awards: Fellow of the IEEE (2002) IEEE Computer Society Meritorious Service Award Golden Core Member of the IEEE Computer Society International Lecturer for the ACM (1992-1997) ACM Fellow (2018) for research in concurrent programming and formal methods Professor Agha has supervised numerous graduate students and postdoctoral researchers through the Open Systems Laboratory. His laboratory has secured substantial research funding for projects in distributed systems, formal verification, and wireless sensor networks. His work on the actor model has influenced both academic research and industry practices in concurrent and distributed computing. As Director of the Open Systems Laboratory, Professor Agha leads a research group focused on advancing the state of the art in distributed and concurrent systems. The laboratory serves as an intellectual hub for theoretical and practical research in open distributed systems, with projects spanning from foundational theory to real-world implementations in areas like structural health monitoring and cloud computing.

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Lars GrunskeView profile

Professor

Max Planck Institute for Security and PrivacyGermany

Lars Grunske is a Professor in the Department of Computer Science at Humboldt University of Berlin, Germany. His academic career spans multiple institutions across Germany, Australia, and internationally, with a strong focus on research and conference participation in software engineering. His educational background includes a PhD in computer science from the University of Potsdam (Hasso-Plattner-Institute for Software Systems Engineering) in 2004. Professor Grunske's research interests center on modeling and verification of systems and software, with particular emphasis on automated analysis techniques. His work primarily focuses on probabilistic and timed model checking and model-based dependability evaluation of complex software intensive systems. He has made significant contributions to software testing, program repair, formal methods, and the application of machine learning techniques to software engineering problems. His publication record shows consistent contributions to top software engineering conferences over the past decade, with recent work exploring the intersection of AI/ML with traditional software engineering challenges. His research demonstrates an evolution from foundational model checking techniques toward more practical applications in software testing and repair. Boeing Postdoctoral Research Fellow Professor Grunske actively mentors through conference activities including chairing mentoring circles at ICSE 2021. He serves on numerous program committees for major software engineering conferences including ASE, ICSE, ESEC/FSE, and others, demonstrating his standing in the academic community. His involvement spans multiple roles from committee member to track chair and award committee positions. He maintains an active research laboratory focused on software verification and testing, as indicated by his departmental affiliation and research website.

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