Find Academic Supervisors

• 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).

• Software Security
• Systems Security
• Smart Contract Security
• +5 more

Lucas Vincenzo Davi is a Professor of Computer Science at the University of Duisburg-Essen and Director of the paluno - the Ruhr Institute for Software Technology . He leads the SYSSEC research group and is a Principal Investigator (PI) in the SFB CROSSING and CASA excellence cluster. His work focuses on practical software and systems security, including memory corruption vulnerabilities, exploit mitigation, and blockchain smart contract security. Davi holds an ERC Starting Grant for Smart Contract Security research. Education: PhD in IT Security, TU Darmstadt (2011–2015), Dissertation: "Code-Reuse Attacks and Defenses" Master of Science in IT Security, Ruhr-Universität Bochum (2007–2009) Diplom (FH) in Business Informatics, FOM Neuss (2003–2007) Research: Davi's work emphasizes real-world security challenges like runtime attacks, trusted execution environments (TEE), and secure embedded systems. His contributions include Wemby (WebAssembly security analysis), HCC (smart contract hardening), and rowhammer mitigations like CATT. His research has influenced industry practices, e.g., Microsoft EMET v5.1 improvements. Awards: Best Teacher Award (2025) Finalist German IT Security Prize (2022, 2020) ACM SIGSAC Dissertation Award (2016) CAST Förderpreis (2010) Grants & Leadership: ERC Starting Grant (Smart Contracts), SFB CROSSING PI, CASA Cluster PI, and leadership in interdisciplinary initiatives like Nano Security (DFG Priority Program). Labs/Teams: Director of paluno, SYSSEC group leader, and collaborator in projects like HERA (hotpatching for embedded systems) and DMA’n’Play (DMA-based attestation).

• Computer Science
• Programming Languages
• Blockchain Technology
• +3 more

Alvise SPANO' is a Researcher at Ca' Foscari University of Venice, affiliated with the Department of Environmental Sciences, Computer Science and Statistics. He is also part of the Research Institute for Complexity. His academic focus includes Blockchain Programming Languages, Programming Languages, and Information Systems. Research projects include ALGOMOVE for Algorand and the RINmaker bioinformatics tool. He has taught courses like Object-Oriented Programming and Introduction to Programming at both undergraduate and doctoral levels. Research interests span smart contract analysis, type systems, and cybersecurity in distributed systems. He contributed to projects like secure RPL for mobile networks and Android-LEGO interoperability. Funding includes the CEVID 2016 project (Role: LD), collaboratively managed with researchers like Agostino Cortesi and Salvatore Orlando. His work bridges theoretical foundations (e.g., COBOL code typing) with practical applications in wearable systems and bioinformatics. Collaborations include the Blockchain Programming Languages research group with Lorenzo Benetollo and Sabina Rossi.

Sanoop MallisseryView profile

Lecturer

• Cybersecurity
• Dependable Systems Security
• Data Privacy Preservation
• +5 more

Sanoop Mallissery is a Lecturer at Monash University's Malaysia School of Information Technology. He holds a PhD in Computer Science (Dependable Systems Security) from National Yang Ming Chiao Tung University, Taiwan, and has over eight years of teaching and five years of industry experience in cybersecurity. His research focuses on software security, critical infrastructure protection, AI-driven threat detection, and privacy preservation. Education : PhD in Computer Science (2024) - National Yang Ming Chiao Tung University, Taiwan Master’s in Cyber Security (2010) - An Optimized Alert Correlation Engine for Enhanced Intrusion Detection Bachelor’s in Information Technology (2006) - University of Calicut Research Interests : His work spans dependable software security, cybersecurity for industrial control systems (ICS/OT), next-gen fuzzing for vulnerability detection, and AI-driven threat mitigation. He emphasizes privacy-preserving techniques in data lifecycle management and resilient software design. Collaborations & Experience : Threat Researcher at TXOne Networks (Taiwan) for ICS/OT security Cyber Security Engineer at ITRI (Taiwan) Research Fellow at ESIGELEC—IRSEEM (France) for vehicular network security Former Assistant Professor at Manipal Institute of Technology, India Grants & Labs : Currently integrating research into teaching at Monash Malaysia while exploring emerging cybersecurity challenges. Actively collaborates on UN SDG-related education and infrastructure security projects.

• Constraint Programming
• Algorithm Selection
• String Constraint Solving
• +4 more

Roberto Amadini is an Associate Professor in the Department of Computer Science and Engineering at the University of Bologna. His work focuses on constraint programming, algorithm selection, and string constraint solving, with applications in cloud-edge computing and IoT systems. He leads research in deploying microservices over hybrid infrastructures and optimizing solver portfolios for constraint satisfaction problems. Research interests include advanced constraint solving techniques, formal methods for software analysis, and energy-efficient resource allocation. Amadini’s contributions span the design of frameworks like FREEDA and SUNNY-as2, which enhance deployment resilience and algorithm selection efficiency. His work bridges theoretical foundations with practical implementations in programming languages and verification tools. Recent publications explore sustainable cloud-edge applications, failure-resilient systems, and dynamic symbolic execution. He actively contributes to open-source projects like JSetL and participates in international solver challenges. No awards are explicitly listed in the provided materials. Amadini’s research group addresses cutting-edge challenges in distributed computing and constraint-based methodologies. Ongoing projects focus on optimizing solver portfolios for real-world computational tasks and advancing string analysis techniques in programming paradigms.

• Learning and Teaching
• Computer Education
• Serious Games
• +7 more

Dr. Julian Dermoudy is an Associate Professor and Associate Head (Learning and Teaching) in the School of Information and Communication Technology at the University of Tasmania. With over 25 years of teaching experience, he has received national and institutional recognition for his pedagogical contributions. His roles have included Head of School, Associate Dean, and Course Coordinator, reflecting his leadership in academic administration. His teaching spans the Bachelor of ICT and Master of ITS programs. Research Interests: Learning and Teaching Innovations Computing Education and Curriculum Design Serious Games and Gamification for Behavior Change Multimodal Analysis and Verification Parallelism and Software Engineering Funded Projects: UTAS Internal Funding: Embedding Indigenous Knowledge in Curriculum (2021-2021) Advising: Supervised 11 doctoral candidates across domains like biometric authentication, ICT curriculum design, and mobile technology impact. Recent students include Simon Stanton (Cooperative Intent) and Shahan Chowdhury (Collaborative In-Store Shopping). Labs/Teams: Active in curriculum redesign initiatives and educational technology innovation, particularly in VR and gamification applications.

José ProençaView profile

Assistant Professor

• Formal Methods
• Concurrency
• Coordination Models
• +5 more

José Proença is an Assistant Professor at the Faculty of Sciences of the University of Porto (FCUP) and a Researcher at CISTER Research Centre, collaborating with INESC TEC. He specializes in formal methods for component-based systems, concurrency, and cyber-physical systems. His research focuses on coordination models, embedded systems, and software product lines, with contributions to frameworks like Reo and LooCI. Education: PhD in Concurrent & Distributed Computing (Leiden University, 2011), BSc+MSc in Mathematics & Computer Science (University of Minho, 2005) Research interests include formal verification, runtime verification for real-time systems, and hybrid systems programming. He coordinates projects like Ibex (FCT-funded) and has been involved in ECSEL projects like VALU3S. Supervised numerous MSc and PhD students, including work on CPS monitors, hybrid simulations, and variability analysis. Teaching includes Concurrent Programming, Algorithms, and Software Verification at the MSc level. Active in program committees for conferences like COORDINATION and SAFECOMP, and steering committee roles. Tools developed include Lince and RebeCaos for system simulation and formal analysis.

ArvindView profile

Professor

• Computer Architecture
• Parallel Computing
• Memory Systems
• +3 more

Arvind is the Johnson Professor of Computer Science and Engineering at MIT and a member of CSAIL (Computer Science and Artificial Intelligence Laboratory). He holds a B.Tech. from IIT Kanpur (1969), M.S. and Ph.D. from the University of Minnesota (1972-1973). His research focuses on computer architecture, parallel computing, memory models, and hardware synthesis. He pioneered dataflow architectures and developed the pH programming language. Notable projects include the Monsoon dataflow machine and Sandburst, a semiconductor company for 10G-bit Ethernet routers. Arvind has received prestigious awards like the IEEE Harry H. Goode Memorial Award (2012) and ACM Fellow (2007). He co-founded Bluespec Inc. and managed collaborations like Nokia-CSAIL (2006-2010). His work spans academia and industry, emphasizing scalable systems and secure computing. Research interests include synthesis/verification of digital systems, graph algorithms, and weak memory models. Current projects explore next-gen Graph AI systems and financial security applications.