Find Academic Supervisors

Nikolaos FoutrisView profile

Researcher

• Dependable Computer Architectures
• Energy-Efficient Systems
• Hardware/Software Co-Design
• +5 more

Nikolaos Foutris is a Researcher at The University of Manchester, specializing in dependable and energy-efficient computer architectures. His work emphasizes hardware/software co-design, focusing on systems and processors that balance performance with reliability. Key research areas include memory optimization, GPU acceleration for cryptographic computations, and radiation effects on MPSoC systems. His research intersects with UN Sustainable Development Goals, particularly through energy-efficient technologies and resilient computing infrastructure. Collaborations span academia and industry, addressing challenges in NUMA systems, blockchain, and cloud applications. Recent publications highlight trends in memory analysis for managed applications, SPIR-V code generation frameworks, and mitigating radiation-induced errors in advanced embedded systems. No scientific awards or grants are explicitly mentioned in the provided text.

Ronald GarciaView profile

Associate Professor

• Programming Languages
• Gradual Typing
• Type Systems
• +6 more

Ronald Garcia is an Associate Professor in the Department of Computer Science at the University of British Columbia, affiliated with the Faculty of Science and the Software Practices Lab. His research focuses on programming language theory, emphasizing gradual typing, type systems, and end-user programming. He teaches courses such as Programming Language Principles (CPSC 509) and Compiler Construction (CPSC 411). Education details are not explicitly stated in the provided texts, but his extensive academic contributions span over two decades. Research interests include formal semantics of programming languages, typestate systems, dependent types, and improving software practices for end-users. He has advised numerous Ph.D. and Master's students, contributing to over 30 academic publications. Recent work explores hybrid programming environments for end-users, runtime type slicing for debugging, and foundational frameworks for gradual dependent types. Garcia actively participates in academic conferences as a PC member and keynote speaker, notably in PLDI, POPL, and ICFP. His lab and collaborations focus on advancing theoretical foundations while addressing practical challenges in software development and education.

Reid HolmesView profile

Professor

• Software Engineering
• End-user Programming
• Software Maintenance
• +3 more

Reid Holmes is a Professor in the Department of Computer Science at the University of British Columbia , part of the Faculty of Science . His research focuses on improving software engineering practices, particularly in end-user programming, developer tool design, and empirical software engineering. He leads the Software Practices Lab and has contributed extensively to understanding developer workflows, testing methodologies, and educational tools for programming. Education: PhD in Computer Science, University of Calgary (2008) MSc in Computer Science, University of British Columbia (2004) BSc in Computer Science, University of British Columbia (2002) Research Interests: End-user programming environments, software testing, developer productivity tools, human-centered AI, educational technology, and empirical studies on software development practices. His work emphasizes bridging the gap between theoretical advancements and practical usability for both professional developers and novice programmers. Recent Article Trends: Focus on hybrid programming environments (e.g., block-based and graph-based systems), human-AI collaboration in testing/assertion generation, and age-inclusive IDE design. His research often involves empirical evaluations of tool effectiveness and developer workflows. Awards: FSE Most Influential Paper Award ICSE Most Influential Paper Award UBC Computer Science Teaching Award CS-Can/Info-Can Outstanding Research Prize Advising & Grants: Supervised over 30 graduate students and postdocs. Noted for collaborative projects with industry partners (e.g., Mozilla, Microsoft). Active in curriculum development for software engineering education. Labs/Teams: Leader of the Software Practices Lab , collaborating with industry and academic partners on tools like CodeShovel , AutoAssert , and Devy (conversational developer assistant).

• Static Analysis
• Abstract Interpretation
• Programming Languages
• +3 more

Julian Erhard is a researcher and lecturer at the Technical University of Munich (TUM), affiliated with the Chair of Languages and Description Structures in Computer Science under Prof. Helmut Seidl. His research focuses on static analysis techniques, particularly leveraging abstract interpretation to enhance precision and performance in compiler optimization and concurrency analysis. He contributes to the Goblint static analyzer and is a member of the ConVeY research training group. Erhard has organized preparatory mathematics courses and served as an exercise instructor for core computer science courses such as Functional Programming and Verification, Compiler Construction, and Static Analysis. His teaching spans multiple semesters from 2019 to 2025, emphasizing practical programming concepts and theoretical foundations. In research, he addresses challenges in context-sensitivity management, concurrency validation, and pointer analysis. His work includes developing frameworks like the digest framework for concurrency-sensitivity and tools like C-2PO for weakly relational pointer domains. Recent publications explore correctness witnesses for concurrent programs and optimizing context sensitivity dynamically. Erhard has co-organized ConVeY retreats and contributed to projects such as the Goblint validator and the Clustered relational thread-modular analysis framework. His expertise bridges theoretical advancements in abstract interpretation with practical compiler tool development.

• Compiler Design
• Static Analysis
• Programming Languages
• +5 more

Michael Petter is a faculty member at the Technische Universität München (TUM), affiliated with the School of Computer Science II (Informatik 2) and the Department of Languages and Description Structures in Computer Science. He specializes in compiler design, static analysis, and formal verification, with a focus on developing tools like the Goblint framework for multi-threaded C programs. His teaching spans courses such as Compiler Construction, Program Optimization, and Functional Programming, reflecting his expertise in programming languages and software engineering. His research interests include static analysis techniques, concurrency control, and abstract interpretation frameworks. He has contributed to advancements in flow-sensitive analysis, context-sensitivity management, and precision recovery in program analysis. Recent work emphasizes improving static analysis tools for industrial benchmarks and enhancing their usability through incremental methods. Petter’s publications highlight innovations in numerical abstract domains (e.g., octagons), non-local jump misuse detection, and thread-modular analysis for multi-threaded systems. His involvement in projects like the DFG Research Training Group ConVeY underscores his commitment to advancing continuous verification in cyber-physical systems. He advises thesis projects on topics like quantum computing at compile time and program synthesis, fostering interdisciplinary collaboration. While actively engaged in academic events and editorial roles, he maintains a lab focused on cutting-edge compiler and static analysis research.

Mark UttingView profile

Associate Professor

• Software Verification
• Model-Based Testing
• Formal Methods
• +5 more

Associate Professor Mark Utting is affiliated with the University of Queensland (UQ), specifically within the School of Electrical Engineering and Computer Science. He holds the rank of Associate Professor and focuses on software verification, model-based testing, and programming language design. His academic journey includes roles at multiple Queensland universities, Waikato University (NZ), and the University of Franche-Comte (France). He earned his PhD from UNSW on object-oriented language semantics. Utting has authored over 80 publications and the book 'Practical Model-Based Testing: A Tools Approach.' His current research emphasizes verifying compilers, blockchain smart contracts, ARM64 binaries, and AI-generated code. Key projects include the Algorand Centre for Sustainability Informatics and the BASIL project on secure information-flow logics. His research spans formal methods, theorem proving, and software engineering. Utting leads supervision in areas like compiler verification and smart contract analysis, with active involvement in grants such as the 'Directed and Incremental Analysis for DevSecOps' project. Utting collaborates on interdisciplinary projects, including energy grid simulations and cybersecurity strategies. His work bridges academia and industry, with past experience in genomics and manufacturing software development.

• Program Specification and Verification
• Concurrent Separation Logics
• Symbolic Execution
• +5 more

Philippa Gardner is a Professor in the Department of Computing at Imperial College London, holding a UK Research and Innovation Established Fellowship (2018–2023). She specializes in program specification, verification, and concurrent separation logics. Her Gillian platform unifies symbolic execution, verification, and testing for C and JavaScript. She was elected a Fellow of the Royal Academy of Engineering (2020) and directed the Research Institute on Verified Trustworthy Software Systems (VeTSS, 2017–2023). Her work includes foundational contributions to separation logic, concurrent program reasoning, and mechanised language specifications. Education: PhD in Computer Science from Edinburgh (1992), supervised by Gordon Plotkin. Key roles: General Chair of POPL 2024, organiser of the Isaac Newton Institute's 'Verified Software' programme (2022). Research interests span formal methods, concurrency, and tool development. Notable grants include £1.5M EPSRC Established Career Fellowship (2018–2023) and £500K Facebook Research gift (2020). Awards include Imperial’s President and Rector’s Teaching Award (2013).

• Formal Methods
• Programming Languages
• Program Verification
• +3 more

Adithya Murali is an Assistant Professor at the University of Wisconsin-Madison's Department of Computer Science. His research focuses on Formal Methods and Programming Languages , specifically democratizing software verification through data-driven logic learning and neuro-symbolic approaches. He holds a Ph.D. from the University of Illinois at Urbana-Champaign (UIUC), advised by P. Madhusudan Parthasarathy. Education: Ph.D. in Computer Science (UIUC, 2024), B.Tech. from BITS-Pilani (2017) Roles: Subreviewer for PLDI, CONCUR, ICALP, and LICS; Teaching Assistant for courses in Logic, Compilers, and Trustworthy AI His research interests center on reducing the cognitive burden of software verification, enabling non-experts to verify code through innovative techniques like logic learning from data. Cross-disciplinary work integrates machine learning with symbolic reasoning, exemplified in projects like the CLEVR VDP Dataset and GQA VDP Dataset for visual discrimination puzzles. Recent publications span formal verification frameworks (e.g., FO-Complete Heap Logics), neuro-symbolic systems, and automated reasoning. His work has received the ACM Europe Best Paper Award (OOPSLA 2023) . Awards: Ray Ozzie Fellowship (2018), Gold Medal (BITS-Pilani 2017), INSPIRE Scholarship (2012-2016) Grants: UIUC Travel Grants, SIGPLAN Funding He advises students across UIUC and UW-Madison, focusing on program synthesis, verification, and AI integration. Collaborations include the Formal Methods Seminar at UIUC and volunteer roles at major conferences.

• Programming Languages
• Computer Security and Privacy
• Blockchain
• +2 more

John Mitchell is the Mary and Gordon Crary Family Professor in Stanford’s School of Engineering and holds courtesy professorships in Electrical Engineering and Education. He chairs the Computer Science Department and directs the d.school. His roles include former Vice Provost for Teaching and Learning, leading over 1,000 online education projects and co-founding Stanford CourseWare, foundational to MOOCs. He co-directs the Lytics Lab, Carta Lab, and Pathways Lab, focusing on data-driven educational improvements. Education: BS in Mathematics from Stanford (1978), PhD in Computer Science from MIT (1984). Research focuses on programming languages, cybersecurity, blockchain, machine learning, and edtech. Key projects include Reinforcement Learning for educational scheduling, cryptographic analysis in generic groups, and privacy in telephony metadata. He authored textbooks like Foundations for Programming Languages and has over 250 publications with 30,000+ citations. Publications emphasize edtech innovations and security (e.g., Bitcoin consensus protocols, generative AI ethics). Awards include ACM Fellow and American Academy of Arts and Sciences election. Advises doctoral students (e.g., Jeongyeon Kim) and oversees grants on learning technologies. Leads teams exploring Generative AI in education, trustworthy ML systems, and hybrid pedagogy post-pandemic. Active in labs advancing educational outcomes through iterative design and data science.

Anthony GoodacreView profile

Professor

• Computer Architecture
• High-Performance Computing (HPC)
• Embedded Systems
• +7 more

Anthony Goodacre is a Professor of Computer Architectures at the School of Computer Science, holding a part-time role while serving as Director of Technology and Systems at ARM Ltd. in Cambridge. He leads research spanning nanotechnology, hardware design, operating systems, and heterogeneous runtimes, with a focus on scalable, power-efficient systems for embedded, enterprise, and HPC applications. Research interests include: Exascale computing through EU-funded projects like EUROSERVER and ExaNoDe 3D silicon integration and system virtualization for heterogeneous architectures Quantum-classical programming languages (e.g., Quff) Power management techniques like cyclic power-gating Memory models and runtime systems for ARM-based data centers His 15 most recent publications highlight trends in FPGA acceleration, radiation-hardened MPSoC systems, and hybrid quantum-classical programming. Contributions to EU FP7/H2020 projects (e.g., EUROSERVER, ExaNEST) emphasize commercialization of ARM technology for exascale computation. Current collaborations include: KALEAO Limited (CSO/CTO since 2015) ARM Ltd. (Director since 2002) Technology Strategy Board (member since 2015) Academic partnerships in EU H2020 projects He co-supervises two PhD students and contributes to policy discussions, including parliamentary select committee evidence. His work aligns with UN SDGs for energy efficiency and sustainable computing.

Timos AntonopoulosView profile

Lecturer

• Logic
• Verification
• Formal Languages
• +3 more

Timos Antonopoulos is a Research Scientist and Lecturer in the Department of Computer Science at Yale University. He is a member of the Rigorous Software Engineering (ROSE) group, led by Ruzica Piskac. His office is located in Dunham Laboratory (Room 404) at 10 Hillhouse Avenue, New Haven, CT. Antonopoulos's research focuses on formal methods and their applications in security and reliability. Key areas include: Logic and Verification : Developing tools and algebras for relational verification, termination analysis, and program correctness. Cryptography & Privacy : Designing zero-knowledge protocols (e.g., ZKSMT, ppSAT) and privacy-preserving techniques for automated decision-making and model checking. Automated Reasoning : Creating frameworks for intentional behavior analysis, SMT-based oracles, and invariant inference to handle uncertainty and complexity. His recent publications (2020–2024) reflect a strong emphasis on cryptographic code security, zero-knowledge proofs, and formal accountability tools. Trends include scalable privacy protocols (e.g., parallelization of zero-knowledge systems), legal/ethical AI verification (e.g., soid for automated decisions), and novel graph/algebraic methods for secure computation. Antonopoulos collaborates extensively within the ROSE group, contributing to projects involving oblivious algorithms, timing-attack mitigation, and secure multi-party SAT solving. His work bridges theoretical foundations (e.g., automata theory, relational algebra) with practical systems security challenges.

Wei YangView profile

Associate Professor

• Software Engineering
• Security
• AI on Edge Devices
• +5 more

Wei Yang is an Associate Professor in the Department of Computer Science at the University of Texas at Dallas, working within the Erik Jonsson School of Engineering and Computer Science. He holds a regular faculty position with an office in ECSS 4.225 and is actively engaged in teaching, research, and mentoring graduate students. His academic journey spans multiple prestigious institutions, and he currently serves on editorial boards for major software engineering journals. Dr. Yang received his Ph.D. in Computer Science from the University of Illinois at Urbana-Champaign in 2018, advised by Prof. Carl A. Gunter and Prof. Tao Xie. He earned his M.S. in Computer Science from North Carolina State University in 2013 under Prof. Tao Xie, and his B.E. in Software Engineering from Shanghai Jiao Tong University in 2011 under Prof. Jianjun Zhao. He was also a visiting researcher at the University of California, Berkeley, invited by Prof. Dawn Song. Dr. Yang's research spans multiple cutting-edge areas at the intersection of software engineering and security. His primary focus centers on software engineering for AI systems , particularly addressing challenges in deploying AI on edge devices like mobile phones, IoT devices, and autonomous vehicles. His pioneering work on efficiency robustness (initiated in 2019) explores how different inputs can trigger varying computational costs in neural networks, leading to novel attacks and defenses. He also develops infrastructure support for AI deployment , including compiler toolchains for dynamic-shaped neural networks and security analysis for IoT deployments. His research extends to mobile testing (since 2012), malware detection using expectation context analysis, and intelligent tools for software engineers and security researchers. Dr. Yang's publication record demonstrates a clear trajectory toward addressing critical challenges in AI security and efficiency. His recent work shows increasing focus on foundation models, large language models, and their security implications, while maintaining strong connections to practical software engineering challenges. The publications reveal a consistent pattern of high-impact research in top-tier venues across software engineering, AI, and security domains. NSF CAREER Award (2022) ACM SIGSOFT Distinguished Paper Award (2021) Amazon Research Award Dr. Yang actively mentors a large group of graduate and undergraduate students, with several PhD students currently working under his supervision. He serves as a faculty advisor for the ASTRO (AI Security and Trustworthiness Operations) team, which was selected as a red teaming participant in the Amazon Nova AI Challenge. His research is supported by significant grants, including the NSF CAREER award providing approximately $500,000 over five years. He emphasizes practical student development, helping them navigate the job market and transition from academic training to professional careers. Dr. Yang leads a vibrant research group focused on software engineering and security challenges in AI systems. His team, including the ASTRO group participating in the Amazon Nova AI Challenge, develops innovative techniques for testing, securing, and improving AI-based systems. The research environment fosters collaboration across multiple domains, with students working on projects ranging from mobile security to foundation model engineering.

Grigore RosuView profile

Professor

• Formal Methods
• Software Engineering
• Programming Languages
• +8 more

Grigore Rosu is a Professor in the Department of Computer Science at the University of Illinois at Urbana-Champaign , where he leads the Formal Systems Laboratory (FSL) . He is also the founder and President of Runtime Verification, Inc. (2010) and Pi Squared, Inc. (2023). Rosu's research bridges theoretical foundations and practical system development in formal methods , software engineering , and programming languages . His academic journey includes a Ph.D. in Computer Science (2000, University of California at San Diego), an M.S. in Fundamentals of Computing (1996, University of Bucharest), and a B.A. in Mathematics (1995, University of Bucharest). Prior to UIUC, he worked as a Research Scientist at NASA Ames Research Center (2000-2002) and took a sabbatical at Microsoft Research (2008). Rosu's research has shaped the field of runtime verification (coined with Klaus Havelund in 2001), introduced the K framework (2003) for executable semantics, and pioneered matching logic as a unifying foundation for formal reasoning. His work spans automated coinduction, monitoring-oriented programming, and formal semantics for C, Java, JavaScript, Python, and the Ethereum Virtual Machine. He has received numerous awards, including the NSF CAREER , Dean's Award for Excellence in Research , and IEEE/ACM Most Influential Paper Award . Scientific Honors : AAAS Fellow (2022) IEEE Fellow (2021) Test of Time Awards (RV 2001, 2018; RV 2003, 2023) Distinguished Paper Awards (ASE 2008, ASE 2016, OOPSLA 2016, ETAPS 2002) NSF CAREER Award (2005) Dean's Award for Excellence in Research (2014) Rosu teaches advanced courses in programming language design , formal semantics , and blockchain technology . His innovations have been commercialized through Runtime Verification, Inc., serving clients like NASA, Boeing, Toyota, and blockchain entities such as Ethereum Foundation.

• Static analysis
• Dynamic Analysis
• Abstract interpretation
• +5 more

Quentin Stiévenart is a post-doctoral researcher at the Software Languages Lab of the Vrije Universiteit Brussel (VUB) in Belgium, specializing in programming languages and program analysis. His research spans multiple areas within static and dynamic analysis, with a particular focus on WebAssembly security and analysis techniques. His primary research interests include: Static and dynamic program analysis Abstract interpretation Type systems and effect systems Concurrent and higher-order programming languages WebAssembly security and analysis Interpreter and framework design Stiévenart's recent publications demonstrate a strong focus on compositional and modular analysis techniques, particularly applied to WebAssembly. His work addresses critical security concerns in WebAssembly, including information flow analysis, binary analysis, and vulnerability detection. He has also contributed to frameworks for static analysis of higher-order languages and techniques for improving analysis performance through parallelism and incremental computation. His academic service includes extensive peer review activities and program committee membership for major conferences including SAS, SCAM, ICFP, ECOOP, and OOPSLA, with a particular emphasis on artifact evaluation committees. Stiévenart has developed several research tools including Wassail (a static analysis tool for WebAssembly security), MAF (a framework for modular static analyses), and Scala-AM (a framework for developing static analyses in Scala).

Yu David LiuView profile

Professor

• Software Systems
• Energy Efficiency
• Performance Optimization
• +6 more

Yu David Liu is a Professor at the School of Computing, State University of New York at Binghamton. He received his Ph.D. from Johns Hopkins University under Scott Smith. Research interests include Software Systems Energy Efficiency Reliability Performance Optimization Security Unmanned Aerial Vehicles Data-Intensive Software Side-Channel Attack Mitigation His work spans runtime systems, compilers, and programming languages for cross-cutting concerns. Key trends in recent publications: 2025-2024 focus on TEE security , UAV regulation , and energy-aware data processing . Earlier works explore secure caches , Green JVM methods , and SLAM system bottlenecks . Scientific Awards NSF CAREER Award (2010) Google Faculty Research Award (2011) Outstanding Research Achievement Award (2018, SUNY Binghamton CS Dept) Outstanding Research Achievement Award (2019, Watson School) Advising: Mentored 11 Ph.D. students (including 2025 Distinguished Dissertation Award winner Timur Babakol) and 14 M.S./B.S. students. Current advisees include Kerem Arikan (Ph.D.), Joseph Raskind (Ph.D.), and Huaxin Tang (Ph.D.). Grants: Funded by NSF awards 2053391 and 2215016 . Former NSF grants include 1910532, 1815949, and 1823260. Labs: Leads the programming language group at SUNY Binghamton, collaborating on UAV software (JCopter, ICRA'21), energy-efficient systems (Vesta, PLDI'24), and security (TEE-SHirT, NDSS'24).