Andrea Lattuada leads the Principled Systems Group at the Max Planck Institute for Software Systems. He co-founded the Verus project for verifying Rust programs and holds a PhD from ETH Zürich. His research develops tools for verifying systems software correctness, focusing on Rust-based verification frameworks and distributed systems reliability. He explores the intersection of formal methods and practical system design. Publications demonstrate advancements in automated verification techniques for concurrent systems and language design. Recent work establishes foundations for scalable system verification. Awards include distinguished paper awards at PLDI, SOSP, and OSDI conferences. He mentors PhD students and collaborates with VMware Research and Microsoft Research. He teaches Formal Verification of Systems Software at Saarland University and leads the Rust Verification Workshop.
Ognjen Savkovic is an Assistant Professor (RTD-a) at the KRDB Research Center for Knowledge and Data, Faculty of Engineering, Free University of Bozen-Bolzano, Italy. He is based at the NOI Techpark in Bolzano and is actively involved in research on Knowledge Graphs, Semantic Web, and data quality. His work bridges formal logic and machine learning to enhance data management systems. His research interests include Knowledge Graphs, Semantic Web, Database Management, Data Quality, Artificial Intelligence, and Logic Reasoning. He focuses on schema validation (e.g., SHACL), property graph schemas (PG-Schema), and integrating machine learning with declarative languages like Datalog for industrial applications such as welding quality monitoring and cloud resource configuration. His recent publications show a strong trend in semantic technologies for industrial applications, particularly in collaboration with Bosch and Siemens. His work spans theoretical foundations of schema languages and practical implementations in smart manufacturing and cloud systems. He has published in top venues including WWW, ISWC, CIKM, and SIGMOD. Scientific Awards: No specific awards mentioned. Ognjen Savkovic advises students and collaborates on research projects, though specific students are not listed. His research involves significant grant-funded collaborations, particularly in EU-level industrial AI and semantic technology initiatives. He has contributed to projects involving Siemens and Bosch, focusing on semantic diagnostics and scalable data science solutions. He is a key member of the KRDB Research Center, contributing to a vibrant research team working on knowledge representation, reasoning, and industrial applications of semantic technologies.
Grace Li Zhang is an Assistant Professor (Tenure Track) in Hardware for Artificial Intelligence at TU Darmstadt since 2022. Previously, she served as Group Leader on Heterogeneous Computing at TU Munich (2018–2022) and earned her Dr.-Ing. in Electrical and Computer Engineering (summa cum laude) from TU Munich (2014–2018). Her research focuses on AI hardware-software co-design, including hardware accelerators for AI algorithms, neuromorphic computing, and emerging memory technologies like RRAM and FeFET. She explores circuit design methodologies, explainability of AI systems, and energy-efficient architectures. Recent work emphasizes leveraging large language models (LLMs) for automated hardware design, verification, and code generation. Her projects address challenges in optical neural networks, in-memory computing, and robustness against hardware non-idealities. Zhang’s contributions span 60+ peer-reviewed articles, with a strong focus on practical implementations for real-world applications. She leads the TU Darmstadt Hardware for AI group, collaborating with industry partners on next-generation computing systems. Her work bridges theoretical innovations with tangible hardware solutions, targeting efficiency, scalability, and security in AI infrastructure.
Engelbert Hubbers is a Lecturer at Radboud University, affiliated with the Digital Security Group within the Institute for Computing and Information Sciences (iCIS). His primary role involves teaching responsibilities across multiple courses such as Mathematical Structures, Formal Reasoning, and Logic and Applications. His research interests focus on formal methods, electronic voting systems, and discrete mathematics, with a particular emphasis on cybersecurity applications like Java Card security and e-passport systems. Engelbert has contributed to significant projects such as the RIES internet voting system and the KOA remote voting system, emphasizing formal verification and secure protocol design. He has held roles in academic governance, including membership in the Exam Committee and Program Committee of iCIS. His work bridges theoretical computer science with practical applications in secure voting technologies and embedded systems. Publications span topics from formal logic in education to cryptographic protocols, reflecting his transition from foundational research (e.g., polynomial automorphisms) to applied security. His teaching includes coordinating courses on formal reasoning, discrete mathematics, and semantics, demonstrating a commitment to both education and cybersecurity innovation.
Andrei Popescu is a Senior Lecturer (Associate Professor level) in the Department of Computer Science at the University of Sheffield, where he conducts research in formal methods, proof assistants, and information flow security. He previously held academic positions at Middlesex University and TU Munich. University: University of Sheffield Department: Department of Computer Science Previous Affiliations: Middlesex University, TU Munich His research focuses on the logical foundations and practical applications of proof assistants, particularly Isabelle/HOL. He has made foundational contributions to inductive and coinductive datatypes, syntax with bindings, higher-order logic, and the formal verification of secure systems. His work bridges theoretical logic with real-world systems such as conference management (CoCon) and social media platforms (CoSMeDis). The recent publications highlight a strong trend in formalizing deep logical results (e.g., Gödel’s incompleteness theorems), advancing datatype theory, verifying complex security properties, and applying formal methods to practical systems. His work consistently appears in top-tier venues such as POPL, CAV, ITP, and CSF. Distinguished Paper Award at POPL 2025 Distinguished Paper Award at POPL 2024 Distinguished Paper Award at POPL 2023 RS 3 Best Paper Award for 2012–2013 He has advised PhD students including Lorenzo Gheri and has been actively involved in organizing major academic events such as the Midlands Graduate School, CPP, ITP, and TABLEAUX conferences. He has served on numerous program committees including POPL, ITP, CSF, and CAV, and has led research projects funded by VeTSS and industrial partners. He is a key contributor to the Isabelle proof assistant ecosystem, particularly in the development of the (co)datatype package and foundational consistency results. His work combines deep theoretical insight with practical implementation, making significant impacts in both academia and applied security.
Mauricio Ayala Rincón is a Full Professor at Universidade de Brasília, affiliated with the Department of Computer Science and the Department of Mathematics. He is a leading researcher in computational logic, formal methods, and term rewriting systems, and heads the Theory of Computation research group (GTC/UnB). Research Interests: His work focuses on the formalization of mathematical and computational theories using proof assistants like PVS. Key areas include term rewriting systems, equational and rewrite-based deduction, automated reasoning, unification, nominal logic, formal verification, and applications in genomics and evolutionary algorithms. He also explores ethics in AI and mechanized mathematics. Recent Publication Trends: His recent articles (2023–2024) reflect a strong emphasis on formalizing algebraic and logical theories in PVS, advancing nominal equational reasoning, anti-unification over algebraic theories, and applying evolutionary algorithms to computational biology. The work is highly theoretical yet applied in verification and combinatorics. Scientific Awards: Best Paper Award at CICM 2023 for "Nominal AC-matching" Advising and Grants: He actively seeks PhD students in algorithmics, formal methods, theorem proving, and AI ethics. He has led numerous research projects, evidenced by extensive publications and editorial roles. He has not listed specific grants, but his continuous output suggests sustained funding. Labs and Teams: He leads the Grupo de Teoria da Computação (GTC/UnB) , which develops PVS libraries for term rewriting (TRS), nominal theories, and evolutionary algorithms. The group maintains public repositories and contributes to the NASA PVS library.
Bruce Draper is a Professor and Chair of the Department of Computer Science in the College of Natural Sciences at Colorado State University. His work bridges artificial intelligence, machine learning, and computer vision, with a strong emphasis on real-world applications involving visual data and intelligent systems. Research Interests: Draper's research centers on machine learning with a focus on visual learning, adversarial AI, and visual agents. He investigates how AI systems can perceive, interpret, and interact with visual environments through technologies like facial recognition, object tracking, augmented reality, and automated visual communication. His work addresses both the capabilities and vulnerabilities of modern AI, particularly in defending systems against adversarial attacks. Publication Trends: His recent scholarly output reflects a consistent trajectory in advancing computer vision and AI robustness. The articles span topics from adversarial defense mechanisms and visual agent autonomy to scalable learning frameworks and real-time video analysis. Collectively, they emphasize secure, efficient, and context-aware visual intelligence systems grounded in deep learning and representation learning. Scientific Awards: No specific awards mentioned in the provided text. Advising and Grants: While no students or grants are explicitly listed, his leadership role as department chair and prior experience as a DARPA program manager suggest extensive involvement in research funding, mentorship, and high-impact project direction. His background indicates likely supervision of graduate students and management of federally funded research initiatives in AI and computer vision. Labs and Teams: Although no specific lab or research group is named, his research scope implies leadership or affiliation with interdisciplinary teams working on AI security, computer vision, and augmented reality systems within the Department of Computer Science at CSU.
Antonio Di Stasio is a Lecturer in the Department of Computer Science at City, St George's, University of London, and an Associate Member of the Department of Computer Science at the University of Oxford. He is also a Member of the Common Room at Kellogg College, Oxford. His research is centered in formal methods, particularly game theory, parity games, temporal logic, synthesis, verification, and automated planning. Dr. Di Stasio earned his Ph.D. in Mathematical and Computer Science from the University of Napoli "Federico II" under the supervision of Prof. Aniello Murano. During his doctoral studies, he was a visiting research scholar at Rice University, working with Prof. Moshe Vardi. His postdoctoral experience includes a Senior Research Associate role at the University of Oxford on the Advanced ERC project WhiteMech with Prof. Giuseppe De Giacomo, and a postdoc at Sapienza University of Rome. His research interests lie at the intersection of logic, games, and AI, with a strong focus on formal verification and synthesis. He has made significant contributions to LTLf synthesis, parity games, and reactive systems. His recent work explores environment specifications, finite-trace logics, and compositional synthesis techniques. The analysis of his recent publications reveals a consistent focus on temporal logic synthesis, especially under finite traces (LTLf) and environment constraints. His work bridges theoretical foundations with practical implementation, as seen in algorithmic improvements for parity games and real-world applications such as attack graphs in cybersecurity. The recurring themes across his articles include formal specification, reactive synthesis, and the application of game-theoretic models to planning and verification. Service Chair, Highlights of Reasoning about Actions, Planning and Reactive Synthesis (ECAI 2024) Chair, On the Effectiveness of Temporal Logics on Finite Traces in AI (AAAI 2023 Spring Symposium) PC Member: AAMAS 2025, VMCAI 2025, ECAI 2024, KR 2023-2024, IJCAI 2023-24, AAAI 2021, ECAI 2020 Journal Reviewer: JAIR, ACM Computing Surveys, Fundamenta Informaticae Dr. Di Stasio has taught courses such as Foundations of Self-Programming Agents at Oxford and delivered PhD-level courses on Game-Theoretic Approaches to Planning and Synthesis at Sapienza University and ESSAI. He is affiliated with the Research Centre for Machine Learning at City, St George's, where he contributes to advancing formal methods in AI. His future work likely continues in the direction of scalable synthesis, practical verification tools, and applications of formal methods in security and autonomous systems.
Jeff Offutt is a Professor and Chair of the Department of Computer Science at the University at Albany, part of the College of Nanotechnology, Software, & Engineering. Previously, he was a Full Professor with Tenure in Software Engineering at George Mason University, where he led the MS in Software Engineering program and developed numerous courses in software testing, web engineering, and software analysis. His research has significantly influenced both academia and industry in software testing and engineering education. His research interests span software testing, mutation testing, model-based testing, automatic test data generation, web application testing, and software engineering education. He has pioneered techniques such as bypass testing and model-based testing, with applications embedded in tools like Selenium. His work emphasizes practical, impactful research—what he calls "science fiction"—with a clear path to real-world use by software engineers. His recent publications reflect a strong trend in cost-effective mutation testing, model-based testing strategies, educational innovations like self-paced learning models (e.g., SPARC), and security aspects of web applications. The keywords across his work include software testing, empirical studies, automation, and education, with subfields such as fault localization, test oracles, input partitioning, and scalable pedagogy. John Toups Presidential Medal for Excellence in Teaching (2020) George Mason University Faculty Member of the Year (2020) Virginia Outstanding Faculty Award (2019) George Mason Teaching Excellence Award (2013) 10-year Most Influential Paper Award, MODELS 2020 Best Paper Award, ICST 2021 Most Influential Paper, ISSRE (2019) Jeff Offutt has advised numerous students and collaborated internationally, including at Swedish universities. He has led major educational initiatives such as the NSF-funded SPARC project, aimed at improving scalability and diversity in introductory CS courses. He has also been actively involved in curriculum development, including co-authoring IEEE/ACM guidelines for software engineering programs. His leadership extends to founding and chairing major conferences like IEEE ICST and serving as Editor-in-Chief of Software Testing, Verification and Reliability . He leads research projects on smart test automation, minimal mutation, and K–5 computer science integration. His work has resulted in widely used tools including muJava, Mothra, and SpecTest. He frequently gives keynote talks on testing, education, and research methodology, and is known for his popular talk "How to Get Your Paper Rejected."
Jakob Lykke Andersen is an Associate Professor in the Department of Mathematics and Computer Science at the University of Southern Denmark (SDU), where he conducts research in algorithms with applications in cheminformatics and complex systems. He also holds a former external appointment as a Research Fellow at the Tokyo Institute of Technology (2015–2017). Research Interests: His work lies at the intersection of computer science and theoretical chemistry, focusing on algorithmic methods for analyzing chemical reaction networks. He employs hypergraphs, mixed-integer linear programming, and probabilistic models to study metabolic pathways, reaction databases, and prebiotic systems. His research emphasizes computational efficiency, formal modeling, and software implementation. Publication Trends: His recent publications (2019–2025) show a consistent focus on graph-based modeling of chemical systems, rule extraction from reaction databases, thermodynamic feasibility, and stochastic analysis. These works appear in high-impact journals in cheminformatics, bioinformatics, and complex systems, reflecting strong interdisciplinary collaboration. Scientific Contributions: While no specific awards are listed, his sustained research output and leadership in funded projects highlight significant contributions to algorithmic cheminformatics. Grants and Projects: He is actively involved in two major ongoing research projects: (1) Software Infrastructures for Teaching at Scale (funded by Innovation Fund Denmark, 2022–2025), and (2) DIREC (Danish Research Center for Digital Economy, 2020–2025), indicating active engagement in both educational technology and core computational research. Advising and Outreach: While no students are listed, he participates in academic advising through project supervision. He contributes to public discourse through media appearances on topics such as mathematics in health (e.g., intestinal system modeling in obesity) and educational well-being. Labs and Teams: He collaborates with interdisciplinary teams, including researchers from bioinformatics, chemistry, and computer science, particularly through projects involving Merkle, Flamm, Fagerberg, and Stadler. His work is associated with algorithmic cheminformatics and software framework development groups at SDU.
Philipp Schuster is a researcher at the University of Tübingen, Germany, specializing in programming languages, compiler design, and functional programming. His work focuses on effect handlers, type systems, and efficient code compilation, with a strong emphasis on lexical scope and formal verification. His research contributions include innovations in capability-passing style for effect handlers, direct-style compilation, and monomorphization techniques. He has actively participated in program committees and artifact evaluations for major conferences like ICFP, SPLASH, and APLAS. Key trends in his publications revolve around effect handling, lambda calculus, type safety, and compiler optimization. His work bridges theoretical foundations with practical implementations, aiming to improve modularity and runtime efficiency in functional programming languages. He has served on program committees and artifact evaluation panels for conferences such as ICFP, SPLASH, APLAS, and HOPE, demonstrating leadership and collaboration in advancing programming language research.
Manuel A. Serrano is a Professor at the School of Computer Science, University of Castilla-La Mancha, Spain. With over 25 years of professional experience including industry roles as programmer/web designer and secondary school teacher, he has been a full-time researcher in the Alarcos group since 2000. Currently coordinates professional practice programs in Computer Engineering. Education : PhD in Computer Engineering (2004, UCLM, cum laude) Research Interests : Data quality, quantum software engineering, business intelligence, Big Data security, IoT, and AI ethics His research spans two major domains: Quantum Computing : Pioneering quantum software engineering, developing testing methodologies, assertion frameworks, and hybrid system guidelines Cybersecurity : Creating security reference architectures for Big Data and automotive systems, with focus on quantum security integration Recent publications demonstrate these interests through: Quantum algorithm verification techniques Security frameworks for automotive systems Ethical AI methodology development Big Data risk analysis patterns Scientific achievements include: 24 JCR-indexed journal articles Over 50 SCI-category conference papers 3 research six-year periods Best Scientific Article Award at JNIC 2018 Research leadership: Coordinated regional project with University of Alicante Principal investigator for national project QUASIMODO Contributor to 20+ national/regional and 3 international projects (SDGear, DQIoT, Di4SPDS) Industrial collaborations with INDRA on ORIGIN and LPS-BIGGER projects Additional qualifications: Professional Scrum Manager certification Cambridge C1 English certification Spin-off participation in AQCLabs and DQTeam
Matthew Hague is a Professor at the Department of Computer Science, Royal Holloway University of London. His research focuses on theoretical and practical aspects of infinite-state verification, with a particular emphasis on higher-order recursion and counter systems. Education: MEng in Computing, Imperial College London DPhil (PhD) in Computer Science, University of Oxford Research Interests: Matthew's work spans infinite-state systems verification , higher-order program analysis , string constraint solving , and pushdown automata . He develops practical tools like Ostrich (for string constraints), C-SHORe (for HORS analysis), TreePed (for CSS optimization), and PDSolver (for pushdown parity games). Scientific Contributions: His recent work includes symbolic Parikh's theorem applications (2024), regex-dependent string constraint solving (2022), collapsible pushdown parity games (2021), and path feasibility analysis with integer data types (2020). These span formal methods, automata theory, and programming language design. Awards & Grants: EPSRC Early Career Fellowship (2013-2018) EPSRC Grant for String Constraint Solving (PI, 2019-2022) Academic Leadership: Matthew has supervised numerous PhD students including Emma Lieu and Jonathan Hoyland, and organized key conferences like BCTCS 2018 and ICALP 2026. He maintains active involvement in program committees for POPL, LICS, and MFCS. Laboratory Tools: He leads development of Ostrich (string constraint solver), PDSolver (pushdown system analysis), and C-SHORe (higher-order verification) tools.
Anders Møller is a Professor at the Department of Computer Science , Aarhus University , Denmark. His career spans roles as an author , committee member , and session chair in conferences like SPLASH, OOPSLA, ECOOP, ISSTA, ICSE, and PLDI. Affiliation: Aarhus University Co-founder: Coana Research Focus : Specializing in static and dynamic program analysis for JavaScript, TypeScript, Java, and Node.js applications, his work addresses: Pointer analysis precision in Java Race condition detection in Node.js Library evolution and semantic patching Soundness improvements in static analyzers Type safety in modern languages Concolic execution for web testing Publication Trends : Recent work (2021–2024) emphasizes security-critical static analysis (taint specifications, Node.js security), soundness optimization (approximate interpretation), and program verification (channel-based communication). Earlier work (2013–2018) includes foundational contributions to JavaScript refactoring , Dart type safety , and AJAX race detection . Scientific Recognition : ISSTA 2019 Distinguished Paper Award Leadership Roles : Active in steering committees for SPLASH, ECOOP, and SIGPLAN, with chairs in OOPSLA, ECOOP, and PLDI program committees.
Dr Anthony J H Simons is a Senior Lecturer in the Department of Computer Science at the University of Sheffield, where he serves as Deputy Director of UG Admissions. He is a member of the Testing research group and has been affiliated with the university since completing his PhD there. His academic journey spans several decades, moving from speech recognition systems to object-oriented programming languages and currently focusing on model-based testing and cloud computing applications. Dr Simons holds an MA in Modern Languages from the University of Cambridge and a PhD in Computer Science from the University of Sheffield. His educational background in both humanities and technical fields has informed his interdisciplinary approach to software engineering research. His primary research interests center around turning formal verification results into practical software engineering benefits. Currently, he investigates Model-Based Testing and Model-Driven Engineering with applications to Cloud Computing. Earlier in his career, he made significant contributions to object-oriented software engineering, including type theory and software development methods. He is the inventor of the JWalk automatic software testing tool for Java and the JAST library for processing XML in Java, and co-author of the OPEN Toolbox of Techniques. His work bridges theoretical computer science with practical software development needs. Analysis of his recent publications reveals a clear trajectory from foundational work in object-oriented type theory to applied research in cloud computing and model-based testing. His scholarship demonstrates consistent focus on formal methods applied to practical software engineering challenges, with increasing emphasis on cloud infrastructure testing and verification in recent years. Dr Simons has secured significant research funding as Principal Investigator, including the Broker@Cloud project (EC-FP7, £323,688, 2012-2015), Future Engineering System (InnovateUK, £199,874, 2016-2019), and Ferromone Trails Concept (Department for Transport, £24,635, 2017). He has supervised numerous undergraduate and masters' projects throughout his career and continues to mentor students despite being semi-retired. He leads the Testing research group at Sheffield and has developed several research projects including CatWalk (a software testing tool for Java), ReMoDeL (a conceptual modeling language), and tools for verifying specifications and generating tests for software services in the cloud. His research has practical applications in cloud service brokerage and quality assurance.
