Software Vulnerability Exploitation Professors and Supervisors

Sidi Mohamed BeillahiView profile

Lecturer

National and Kapodistrian University of AthensGreece

Sidi Mohamed Beillahi is a Lecturer in the Department of Computer Science at the University of Toronto's Faculty of Arts and Science. He teaches courses including Principles of Programming Languages (CSC324H1S) and Algorithms and Data Structures (ECE345H1F). Previously, he served as a Teaching Assistant at both University of Paris and Concordia University for courses ranging from Automata Theory to Hardware Functional Verification. Dr. Beillahi's research focuses on developing formal verification and programming languages techniques to ensure the correctness of software systems, particularly distributed systems, concurrent programs, blockchain, and smart contracts. His work bridges theoretical computer science with practical security applications in decentralized finance. His publication record shows a clear progression from quantum circuit verification during his Master's to blockchain and smart contract security in his doctoral and postdoctoral work. Recent publications demonstrate expertise in authenticated data structures for blockchain storage, flash loan attack analysis, and formal verification of decentralized applications. Scientific Awards: ACM SIGSOFT Distinguished Paper Award (ICSE '24) ICBC Distinguished Paper Award (ICBC '22) Dr. Beillahi has advised multiple research projects in blockchain security and verification, often collaborating with Professor Fan Long and Professor Andreas Veneris at the University of Toronto. His research has been supported by prestigious fellowships including an NSERC Postdoctoral Fellowship and a Mitacs Accelerate Fellowship.

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Jingyue LiView profile

Professor

Max Planck Institute for Security and PrivacyGermany

Jingyue Li is a Professor in the Department of Computer Science at the Norwegian University of Science and Technology (NTNU), within the Faculty of Information Technology and Electrical Engineering. She earned her Ph.D. in Software Engineering from NTNU in 2006 and has extensive industrial experience including positions at IBM and DNV Research and Innovation. Her educational background includes: Ph.D. in Software Engineering from NTNU (2006) Professor Li's research spans several key areas in software engineering with a focus on both theoretical and practical applications. Her work bridges traditional software engineering practices with emerging technologies, particularly in the domain of security and blockchain systems. She has conducted extensive empirical research and applied design science methodologies to develop innovative tools and approaches. Her recent publications demonstrate a strong trend toward blockchain technologies, software security, and the intersection of AI with software engineering. The research shows increasing focus on practical applications of blockchain in decentralized autonomous organizations, consensus protocols, and security vulnerabilities in smart contracts. There's also significant work on integrating security practices into DevOps (DevSecOps) and applying machine learning techniques to software engineering problems. Professor Li has received recognition through her leadership roles in major conferences: General Chair for FSE 2025 (The ACM International Conference on Foundations of Software Engineering) Member of the EASE (International Conference on Evaluation and Assessment in Software Engineering) steering committee In terms of research leadership, Professor Li has served as Principal Investigator (PI) or Key Scientist on numerous research projects including TRACE4EU (2023-2025), PaaSforChain (2020-2023), CyberSmart (2017-2020), and several others focused on blockchain, security, and software engineering. She has also conducted research visits to institutions including University College London, University of Washington, Hiroshima University, and Peking University. Her research group appears to be actively engaged in both theoretical and applied research, with strong industry connections through projects like CyberSmart and SecureCyber that address real-world challenges in cybersecurity and smart city infrastructure.

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Keshav SoodView profile

Senior Lecturer

Deakin UniversityAustralia

Dr. Keshav Sood is a Senior Lecturer at Deakin University's School of Information Technology, where he leads research in cybersecurity, AI, and next-generation networks. His affiliations include roles as Graduate Research Coordinator and South Asia Country Coordinator. He completed his PhD at Deakin University and a post-doctoral fellowship at the University of Newcastle. Research Interests: Dr. Sood focuses on securing distributed systems, with emphasis on: Federated learning for intrusion detection in IoT/5G networks Biometric privacy in immersive technologies (VR/AR) RF fingerprinting for IoT device authentication Quantum-resistant software-defined networks Adversarial robustness in voice authentication systems His publications consistently explore AI-driven security frameworks, with recent work addressing data sparsity in IoT sensors, cross-domain IIoT authentication, and phishing mitigation using large language models. Awards: Professor of IT Award (2016) IEEE TNSE Excellent Reviewer (2023) Deakin HDR Supervision Award (2023) Course Team Award for Industry Certification Alignment (2021) Supervision & Grants: Dr. Sood currently advises 8 graduate researchers and has secured $655,313 in competitive funding. Key projects include: Smart Farming Cyber Resilience (DFAT Maitri Grant) Secure Access for Critical Infrastructure (Cyber CRC) IoT Data Integrity for Defense Systems (Australian Defence) He leads the Deakin Cyber Research and Innovation Centre, focusing on scalable security solutions for industry partners.

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Klaus von GleissenthallView profile

Assistant Professor

University of California, San DiegoUnited States

Klaus von Gleissenthall is a tenured Assistant Professor in Computer Science at Vrije Universiteit Amsterdam, affiliated with the Theory Group and VUSec security lab. He holds a joint appointment with CWI's Computer Security group. Previously, he was a post-doc at UCSD and completed his PhD at TUM under a Microsoft Research scholarship. His research integrates programming languages , security , and systems to develop formally verified, low-overhead solutions for hardware/software correctness. Key focus areas include: Side-channel attack mitigation via leakage contracts Refinement-type systems for hardware verification Byzantine fault tolerance in distributed systems Publications demonstrate strong emphasis on hardware security (45% of recent papers), formal methods (30%), and distributed systems (25%), with consistent appearances in top-tier venues (S&P, CCS, OOPSLA). Awards & Honors: ERC Starting Grant (€1.5M, 2024) Intel Hardware Security Award Honorable Mention (2020, 2024) Distinguished Paper Awards: CCS'23, OOPSLA'23, POPL'21 He advises four PhD students and two post-docs, supported by his ERC grant. Current projects include refinement types for hardware and pre-silicon leak detection. His lab collaborates with VUSec and CWI, focusing on scalable verification tools like LLVM Blade and methodologies for constant-time execution guarantees.

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Eugene Howard SpaffordView profile

Professor

Menlo CollegeUnited States

Eugene Howard Spafford (known as Spaf) is a Professor of Computer Science at Purdue University's College of Science. He is a renowned computer security expert who founded and served as the first director of the Center for Education and Research in Information Assurance and Security (CERIAS) at Purdue University in 1998. Professor Spafford advises U.S. government agencies and corporations on security matters and has testified before Congress on cybersecurity issues. His educational background includes a PhD and Masters in Information and Computer Science from Georgia Tech and a Bachelors in Mathematics and Computer Science from SUNY Brockport. Professor Spafford's research spans computer security, intrusion detection, digital forensics, and software vulnerability analysis, with recent focus on deception techniques in security defense. Analysis of his publication record shows a consistent focus on practical security solutions, beginning with early work on the Internet Worm of 1988 and evolving to modern concerns about password security, deception techniques, and the balance between privacy and surveillance. His highly cited work on Tripwire established foundational approaches to file integrity checking that remain relevant today. Ranked #408 in Computer Science worldwide according to AcademicInfluence.com Ranked #230 in USA for Computer Science Ranked #1452 in Database worldwide Professor Spafford has supervised numerous students and researchers through CERIAS, contributing to the development of the next generation of security professionals. His work on security education has helped shape curriculum standards in the field. The Center for Education and Research in Information Assurance and Security (CERIAS) continues to be a major hub for interdisciplinary security research under his foundational influence. His laboratory, CERIAS, maintains an active research agenda in information security and can be accessed at http://www.cerias.purdue.edu/.

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Shing-Chi CheungView profile

Professor

Max Planck Institute for Security and PrivacyGermany

Shing-Chi Cheung is a Professor of Computer Science and Engineering at the Hong Kong University of Science and Technology (HKUST), School of Engineering. He founded the CASTLE research group and co-founded the International Workshop on Automation of Software Testing (AST) in 2006. His leadership includes serving as General Chair of FSE 2014 and chairing multiple APSEC conferences. His research focuses on software quality enhancement through program analysis, testing, debugging, and AI techniques, targeting Android apps, open-source software, deep learning systems, smart contracts, and spreadsheets. Current projects include metamorphic testing frameworks, binary analysis tools, and vulnerability detection systems for emerging technologies. His publication portfolio demonstrates consistent contributions to software engineering since 2016, with recent work emphasizing AI-integrated testing methodologies, smart contract security, and deep learning system reliability. Key trends show increasing focus on cross-language analysis, data visualization quality, and compiler-level verification for modern software stacks. Distinguished Member of the ACM Fellow of the British Computer Society Editorial board member: Science of Computer Programming (SCP), Journal of Computer Science and Technology (JCST) Former editorial board member: IEEE Transactions on Software Engineering (2006-2009), Information and Software Technology (2012-2015) Four patents in China and the United States Cheung actively mentors through the CASTLE research group and serves on program committees for major conferences including ICSE, ESEC/FSE, and ISSTA. His work bridges academic research with practical applications through industry collaborations and tool development. He has contributed to numerous workshops and symposia as steering committee member and program chair.

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Xin XiaView profile

Professor

Max Planck Institute for Security and PrivacyGermany

Xin Xia is a Qiushi Distinguished Professor at the College of Computer Science and Technology, Zhejiang University. Previously, he served as the Chief Expert and Director of the Software Engineering Application Technology Lab at Huawei Technologies, China from 2021 to 2025. His academic career spans software engineering research with a focus on AI applications in the field. Ph.D. from Zhejiang University (2014) Supervised by Prof. Xiaohu Yang and Prof. Jianling Sun Visiting student at Singapore Management University (2012-2014) under Prof. David Lo Xin Xia's research primarily focuses on applying data science techniques to software engineering problems. His work spans AI for Software Engineering, Mining Software Repositories, Empirical Software Engineering, and Large Language Models for code understanding and generation. He employs data mining, information retrieval, natural language processing, search-based algorithms, and program analysis to transform software engineering data into automated tools and insights. His recent publications show a strong trend toward leveraging Large Language Models for various software engineering tasks, including code generation, vulnerability detection, and test generation. He has been exploring how to make these models more effective, reliable, and practical for real-world software development scenarios, with a particular focus on Java and Python ecosystems. ACM SIGSOFT Early Career Researcher Award (2022) ACM Distinguished Member 16 best or distinguished paper awards, including nine ACM SIGSOFT Distinguished Paper Awards Recipient of the IEEE Transactions on Software Engineering 2021 Best Paper Award Runner-Up Xin Xia has advised numerous students who have gone on to publish in top software engineering venues. His research has been supported by grants from both academic institutions and industry partners, particularly during his time at Huawei. He actively collaborates with researchers worldwide, especially with David Lo at Singapore Management University. At Zhejiang University, Professor Xia leads research in the intersection of AI and Software Engineering. His work has practical applications in improving developer productivity through automated tools that analyze software repositories and provide actionable insights.

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Chao ZhangView profile

Associate Professor

Max Planck Institute for Security and PrivacyGermany

Chao Zhang is a Tenured Associate Professor at Tsinghua University, specializing in software security, system security, data security, and AI security. He leads the VUL337 research group and serves as the coach of the Blue-Lotus CTF team. His educational background includes a Ph.D. in Computer Science from Peking University (2008-2013), a B.S. in Mathematical Science from Peking University (2004-2008), and a postdoctoral position at UC Berkeley (2013-2016). Dr. Zhang's research focuses on Software Security , System Security , Data and AI Security , Program Analysis , and Vulnerability Discovery . His work spans binary code analysis, fuzzing techniques, blockchain security, and AI security. His recent publications demonstrate a strong emphasis on developing novel frameworks for vulnerability detection, binary code analysis, and securing AI systems against adversarial attacks. His publication trends show a consistent focus on practical security solutions with increasing attention to AI security challenges. Over the past decade, he has published extensively in top security conferences including IEEE S&P, USENIX Security, CCS, NDSS, and ISSTA, with a significant acceleration in publications since 2020. Tencent CSS TSec Professional Prize (2nd place, 2019) Tencent CSS TSec Breakthrough Prize (1st place, 2018) DARPA Cyber Grand Challenge CFE, 2nd in exploiting (2016) DARPA Cyber Grand Challenge CQE, 1st in defense (2015) Microsoft BlueHat Prize Contest's Special Recognition Award (2012) 5th place in Defcon CTF 2017 2nd place in Defcon CTF 2016 5th place in Defcon CTF 2015 Dr. Zhang leads the VUL337 research group at Tsinghua University, which focuses on vulnerability discovery and security analysis. He also serves as the coach of the Blue-Lotus CTF team and is a member of the V group of LiST. His research has received significant attention in the security community, with numerous publications in top-tier security venues and practical contributions to vulnerability discovery and mitigation techniques.

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Jie LuView profile

Associate Professor

Max Planck Institute for Security and PrivacyGermany

Jie Lu is an Associate Professor at the Institute of Computing Technology of the Chinese Academy of Sciences (ICT, CAS), where he leads research in software security and program analysis. His work focuses on developing advanced program analysis techniques to improve software reliability and security, with applications in cloud systems, distributed environments, and modern web applications. Dr. Lu's research interests include: Software Security: Focusing on vulnerability detection and prevention in open-source software Program Analysis: Specializing in static/dynamic analysis techniques and context-sensitive pointer analysis Cloud Systems: Researching distributed system security, crash-recovery, and concurrency bug detection His recent publications demonstrate a strong focus on practical security solutions for real-world systems. The research spans Kubernetes ecosystems, PHP applications, Linux kernel security, Java web applications, and Windows IPC systems. A notable trend is the development of precise static analysis techniques that balance efficiency with accuracy, addressing the longstanding challenge in program analysis. His work often bridges theoretical advances with practical implementations that have been adopted by industry. Dr. Lu has received several prestigious awards: ACM SIGSOFT Distinguished Paper Award 2025 Best Paper Honorable Mention at CCS 2022 Chinese Academy of Sciences Outstanding Doctoral Dissertation 2021 Chinese Academy of Sciences President's Special Award 2020 ICT New Hundred Stars 2020 Dr. Lu actively mentors students and researchers, recruiting PhD candidates, Master students, and research interns interested in software security and program analysis. His research has been supported by the National Natural Science Foundation of China, CCF-Huawei Innovation Research Plan, and CCF-Ant Research Fund. The Program Analysis Group (ICT-PAG) at the National Key Laboratory of Processor has successfully identified numerous errors and vulnerabilities in popular open-source applications, with over 200 severe bugs confirmed by the open-source community and assigned more than 100 CVE numbers. His research group, the Program Analysis Group (ICT-PAG), is based in the National Key Laboratory of Processor at ICT, CAS. The group has achieved significant impact through both academic publications in top venues (SOSP, CCS, USENIX Security, NDSS, OOPSLA, ISSTA, FSE, ASE, TSE) and practical applications in leading IT companies and government organizations.

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Yutian TangView profile

Assistant Professor

Max Planck Institute for Security and PrivacyGermany

Dr. Yutian Tang serves as an Assistant Professor (UK Lecturer) and Principal Investigator at the School of Computing Science, University of Glasgow, where he supervises PhD students and leads research in AI-driven software engineering. His academic journey includes a PhD from The Hong Kong Polytechnic University's Department of Computing. His research spans AI+SE integration , particularly focusing on Large Language Models for program analysis, software testing, and Android security. Key areas include: LLM-assisted vulnerability detection and repair Empirical studies of real-world software systems Privacy protection mechanisms Configuration compatibility in mobile applications Smart contract security optimization His publication portfolio shows a clear trajectory toward AI-augmented software engineering , with recent work demonstrating how LLMs can enhance taint analysis, binary code similarity detection, and test generation. This evolution reflects the field's broader shift toward AI integration while maintaining rigorous empirical validation. Award highlights include: Best Industry Paper Award at ISSRE'18 Elevation to IEEE Senior Member (2024) Three Android OS defects confirmed by Google Security Team As an active researcher and community contributor, Tang serves on 40+ program committees including PLDI, ICSE, and FSE. His work receives funding from National Natural Science Foundation of China, Shanghai Science Commission, OpenAI, and Google. Current projects focus on automated bug localization and LLM-based testing frameworks, with recent grants from OpenAI Cybersecurity and Google Cloud programs. He leads research groups investigating Android security and AI-assisted program analysis, collaborating with institutions like Lund University.

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Lian LiView profile

Professor

Max Planck Institute for Security and PrivacyGermany

Lian Li is a Professor in the Institute of Computing Technology at the Chinese Academy of Sciences, where he leads the program analysis research group. He holds a PhD from the University of New South Wales, Australia, and a Bachelor's degree from Tsinghua University in Engineering Physics. His research focuses on developing innovative program analysis techniques and tools to enhance software reliability and security. His educational background includes a PhD in Computer Science from the University of New South Wales (2003-2007) with a thesis on "ScratchPad Management for Static Data Aggregates" under Professor Jinling Xue, and a Bachelor's degree in Engineering Physics from Tsinghua University (1993-1998). Lian Li's research primarily centers on program analysis techniques, particularly static analysis methods for software security and reliability. His group developed Wukong, a static analysis and detection system capable of identifying deep security vulnerabilities across functions, components, and complex dependencies in C/C++, Java, and Android applications. This tool has discovered thousands of errors in popular open-source software including Google Chromium, Bash, sed, and Hadoop, with hundreds confirmed by developers and over 50 CVEs assigned. His publication record shows a strong focus on program analysis, particularly context-sensitive pointer analysis, taint analysis, and vulnerability detection. His recent work (2021-2024) demonstrates continued innovation in context-free language reachability, efficient IFDS algorithms, and specialized analysis for generics and authorization vulnerabilities. His research spans cybersecurity, programming languages, and software engineering domains, with emphasis on practical applications for real-world software systems. ASE 2019 Distinguished Paper Award CCS 2022 Best Paper Honorable Mention Lian Li has guided numerous PhD and Master's students in computer system architecture and software theory. His research group maintains active collaborations across various software analysis domains, with funding supporting their work on tools like Wukong. They have developed significant intellectual property including multiple patents related to program analysis techniques. The program analysis research group he leads focuses on developing practical tools for software reliability and security. Their work bridges theoretical program analysis with real-world applications, particularly through the Wukong analysis system which has been successfully applied to major open-source projects.

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