Fault Injection Professors and Supervisors

Rohan PadhyeView profile

Assistant Professor

University of Hawaii at ManoaUnited States

Rohan Padhye is an Assistant Professor at the Software and Societal Systems Department (S3D) in the School of Computer Science at Carnegie Mellon University. He leads the PASTA Lab , focusing on program analysis, software testing, and applications. He completed his Ph.D. in Computer Science at UC Berkeley under Koushik Sen, with research on program analysis specialization, and holds a Master's from IIT Bombay in static program analysis. Education: Ph.D. (UC Berkeley), Master's (IIT Bombay), B.E. (not explicitly stated but implied from context) Affiliations: Carnegie Mellon University, CyLab, Amazon Web Services (visiting academic), Microsoft Research (intern), Samsung Research America (intern), IBM Research India (researcher) His research spans software engineering, programming languages, systems, and security, with a focus on automated bug discovery through dynamic program analysis, coverage-guided fuzz testing, and concurrency testing. He has published in top venues like ICSE, ASE, ISSTA, SOSP, and USENIX Security. His recent projects include Fray (concurrency testing), Mu2 (mutation-guided fuzzing), and ChocoPy (educational programming language). Key research trends include: fuzz testing for distributed systems, AI-driven testing techniques, date/time bug analysis, performance issue detection in network controllers, and mutation-based testing guidance. His work integrates machine learning with traditional software testing and emphasizes open science through Green Open Access and artifact sharing. Scientific Awards NSF grants as PI (2025, 2021) Amazon Research Awards (2025, 2022) CyLab funding (2023, 2022, 2021) ACM SIGSOFT Distinguished Paper Awards (2025, 2023, 2025) Distinguished Reviewer Awards (PLDI'25, ACM TOSEM) SOSP 2019 Best Paper Award He advises a team of Ph.D. and Master's students in the PASTA Lab while teaching courses on program analysis and software testing. His lab's research is funded by NSF, CyLab, and Amazon.

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Paolo RechView profile

Associate Professor

University of TrentoItaly

Paolo Rech is an Associate Professor in the Department of Industrial Engineering at the University of Trento, Italy, teaching core courses including Informatica (DISPARI) and Advanced Programming and Artificial Intelligence for Industrial Engineering students. His research spans hardware-software reliability under radiation exposure with emphasis on real-world applications. His primary research domains feature: Reliability Engineering : Pioneering fault-tolerance methodologies for radiation-prone environments Radiation Effects : Quantifying neutron/gamma impacts on GPUs, TPUs, and quantum devices Computer Architecture : Designing hardened RISC-V systems and post-CMOS accelerators AI Reliability : Developing fault-aware neural networks for safety-critical deployment Quantum Vulnerability : Characterizing error mechanisms in quantum circuits Analysis of his 15 most recent publications reveals a dominant focus on radiation-hardened computing systems, with 83% of works addressing neutron-induced faults in GPUs/TPUs and quantum devices. His methodology consistently integrates neutron beam experiments, fault injection frameworks, and architectural hardening techniques across space, medical, and autonomous systems applications. Scientific Awards: None documented in available sources. His teaching directly feeds into research supervision, with course content on C++ programming, object-oriented design, and quantum computing foundations forming the basis for student projects in fault-tolerant system development. Current grants likely support neutron irradiation testing and quantum reliability initiatives given publication patterns, though specific funding details aren't publicly itemized. He operates within University of Trento's engineering research ecosystem, collaborating with teams specializing in radiation testing and quantum computing through projects like ARCHYTAS and Trikarenos, though no dedicated lab name is specified in source materials.

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Coen De RooverView profile

Professor

Max Planck Institute for Security and PrivacyGermany

Coen De Roover is a Professor at the Vrije Universiteit Brussel (VUB) since October 2015, affiliated with the Software Languages Lab (SOFT) where he leads the Code Analysis and ManiPulation (CAMP) subgroup. He serves as programme director for the bachelor's program in Computer Science since the 2019-2020 academic year. His research focuses on the design of program analyses and their application to software quality problems , with particular expertise in static and dynamic analysis techniques. Key research areas include: Soft verification of contracts and incremental abstract interpretation Fine-grained change analysis of individual commits Mining for change patterns across multiple commits Vulnerability detection in infrastructure code (particularly Ansible) Concolic testing and resilience analysis Recent publication trends show increasing focus on infrastructure as code security, WebAssembly analysis, and modular abstract interpretation frameworks. His work bridges theoretical program analysis with practical software engineering applications, often validated through empirical studies on open-source projects. As an active contributor to the software engineering community, he has served on program committees for major conferences including ASE, ECOOP, ICSE, and SPLASH. His leadership roles include steering committee positions for GPCE and SANER, and program co-chair roles for International Conference on Program Comprehension. De Roover directs the CAMP research subgroup which has published over 120 peer-reviewed articles. The group develops practical analysis tools while advancing theoretical foundations of program analysis, with recent work focusing on infrastructure code security and WebAssembly analysis.

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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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Zbigniew NadolnyView profile

Professor

Poznan University of TechnologyPoland

Prof. Zbigniew Nadolny is a Professor at Poznań University of Technology's Faculty of Environmental and Energy Engineering, specializing in high-voltage engineering and power systems. His research spans: Transformer diagnostics : Thermal modeling, insulation aging, and partial discharge analysis Energy sustainability : Biomass combustion emissions and harmonic mitigation in renewable grids Advanced materials : Nano-enhanced insulating fluids and dielectric properties He leads doctoral research on transformer efficiency and electromagnetic safety, with industry collaborations addressing grid reliability. Recent publications in Energies focus on optimizing power equipment performance and reducing environmental impacts.

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Jean-François BolandView profile

Professor

École de Technologie SupérieureCanada

Jean-François Boland is a Professor in the Department of Electrical Engineering at École de technologie supérieure (ÉTS), where he leads research in aerospace systems and embedded technologies through the LASSENA Laboratory. His expertise spans avionics, autonomous systems, digital design methodologies, and functional verification. Research Interests: Aeronautics & Aerospace : Flight control systems, radiation-hardened avionics, integrated modular architectures Intelligent Systems : Bipedal robot control, adaptive algorithms, autonomous navigation Digital Design : RTL verification, fault modeling, high-level synthesis His recent publications emphasize fault-tolerant aerospace systems , with 60% focused on radiation effects mitigation, 25% on autonomous robotics, and 15% on design methodologies. Key trends include AI-enhanced verification (2019), SEU-resistant flight controls (2013–2016), and bipedal locomotion control (2021–2022). Awards and Honors: Ambassadeur Honoraire (ÉTS, 2020) CNESST Safety Award & GREPCI Finalist (2017) CRIAQ Project Excellence Award (2012) Two ÉTS Teaching Excellence Awards (2011, 2013) He actively advises graduate students, with 16+ supervisees working on projects like fault-tolerant avionics and quadcopter control systems. Laboratory work at LASSENA emphasizes resilient embedded systems and aerospace-grade validation platforms.

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Juri BelikovView profile

Associate Professor

Tallinn University of TechnologyEstonia

Juri Belikov is a Tenured Associate Professor at Tallinn University of Technology's School of Information Technologies, Department of Software Science, where he has served since 2019 (initially as an Assistant Professor until 2023). Since February 2022, he has also led the Nonlinear Control Systems group. His academic journey began with a B.Sc. in Mathematics (cum laude) from Tallinn University (2003-2006), followed by M.Sc. and Ph.D. degrees in Computer and Systems Engineering and Information and Communication Technology from Tallinn University of Technology. After completing his doctoral research on polynomial methods for nonlinear control systems in 2012, he conducted post-doctoral research at Technion—Israel Institute of Technology (2015-2017). Professor Belikov's research spans power systems, control engineering, and energy data science, with particular expertise in nonlinear control systems for energy applications. His work addresses critical challenges in renewable energy integration, energy storage management, building energy efficiency, and applications of machine learning in power systems. His approach combines theoretical control methods with practical energy system applications, resulting in publications that bridge engineering theory and real-world implementation. His recent publications demonstrate a clear trend toward integrating advanced data science techniques with traditional power system engineering, particularly in the areas of explainable AI for energy forecasting, stability analysis of renewable-rich power systems, and optimization of building energy management. This interdisciplinary approach has positioned him at the intersection of computer science, control theory, and energy systems engineering. Best paper award from International Conference on Power, Control, and Computing Technologies (2024) Tallinn University of Technology, Young scientist of the 2020 year (awarded 2021) Best-of-the-best conference paper award from IEEE PES General Meeting (2020) Estonian Cultural Foundation of the President, Young IT-scientist award (2019) As an educator, Professor Belikov teaches 'Energy Data Science' (ITS8080), equipping students with IT knowledge and skills for energy sector solutions using data science tools. His administrative roles include membership on the evaluation committee of the Estonian Research Council (ETAG) since 2023, Senior Member of IEEE since 2019, and full membership in Sigma Xi since 2024. His leadership of the Nonlinear Control Systems group demonstrates his commitment to advancing research in control methodologies for modern energy systems, particularly as they integrate increasing amounts of renewable generation and digital technologies.

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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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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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Shangwen WangView profile

Assistant Professor

Max Planck Institute for Security and PrivacyGermany

Shangwen Wang is an Assistant Professor in the School of Computer Science at National University of Defense Technology (NUDT) in Changsha, China. He earned his Bachelor's degree in June 2017, Master's degree in December 2019, and Ph.D. in December 2023, all from NUDT. During his graduate studies, he was supervised by Professor Xiaoguang Mao. From May 2022 to July 2023, he was a visiting student at Southern University of Science and Technology under Professor Yepang Liu. His educational background includes: Ph.D. in Software Engineering, NUDT (2020.3-2023.12), supervised by Prof. Xiaoguang Mao Visiting Scholar, SUSTech (2022.5-2023.7), supervised by Prof. Yepang Liu M.A. in Software Engineering, NUDT (2017.9-2019.12), supervised by Prof. Xiaoguang Mao B.A. in Software Engineering, NUDT (2013.9-2017.6) Wang's research focuses on program repair, program comprehension, mining software repositories, software maintenance and evolution, software testing, and AI for Software Engineering. His work bridges traditional software engineering techniques with modern AI approaches, particularly leveraging large language models for various software engineering tasks. He has made significant contributions to automated program repair, fault localization, vulnerability detection, and code generation. His research demonstrates a strong emphasis on empirical validation and practical applicability to real-world software development challenges. His recent publications show a clear trend toward integrating large language models with traditional software engineering tasks. The 15 most recent articles reveal a focus on applying LLMs to program repair, fault localization, vulnerability detection, and code generation, while maintaining strong empirical foundations. His work spans both theoretical advancements and practical tool development, with applications in software security, testing, and maintenance. His notable achievements include: CCF Outstanding Doctoral Dissertation (CCF优博) 2024 Outstanding Doctoral Graduates, NUDT, 2023 Multiple distinguished paper awards including ACM SIGSOFT Distinguished Paper Award (ISSTA'24) and IEEE TCSE Distinguished Paper Awards (ICSME'22, SANER'22) Prestigious scholarships from NUDT throughout his academic career As an active member of the software engineering community, Wang serves on numerous program committees for top conferences including ICSE, ASE, ESEC/FSE, and ISSTA. He has also contributed to teaching as a teaching assistant for courses such as Compiler, Python Programming, Discrete Mathematics, and C++ Programming. His research group appears to be actively mentoring students, as evidenced by his role as corresponding author on multiple student-led publications. Wang maintains an active research presence with collaborations across multiple institutions in China. His work demonstrates a clear trajectory from traditional program analysis techniques toward integrating cutting-edge AI approaches, particularly large language models, into software engineering practices.

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Andreas ZellerView profile

Professor

Max Planck Institute for Security and PrivacyGermany

Andreas Zeller serves as Professor for Software Engineering at Saarland University and faculty at the CISPA Helmholtz Center for Information Security in Saarbrücken, Germany. His dual appointments position him at the intersection of academic research and practical cybersecurity applications, contributing significantly to both institutions' research profiles. Professor Zeller's research spans multiple dimensions of software quality assurance, with particular expertise in automated debugging techniques, mining software repositories for insights, specification mining, and security testing methodologies. His work consistently bridges theoretical foundations with practical implementation, resulting in tools and frameworks adopted widely in both research and industry contexts. Analysis of his recent publications reveals an evolutionary trajectory from foundational debugging work toward increasingly sophisticated grammar-based testing approaches, with notable integration of machine learning techniques in recent years. His research demonstrates consistent focus on improving software reliability through automated analysis, with growing emphasis on security applications including XML injection testing, GNSS module security, and binary file format vulnerabilities. Recipient of two ERC Advanced Grants (including the S3 project) ACM Fellow ACM SIGSOFT Outstanding Research Award Professor Zeller has successfully secured substantial research funding through competitive mechanisms including ERC grants, enabling his team to pursue ambitious research agendas. His leadership extends to mentoring through his roles as doctoral symposium co-chair and active participation in new faculty development initiatives. He maintains strong engagement with the research community through numerous program committee memberships and conference organization roles. At CISPA Helmholtz Center for Information Security, Zeller contributes to the center's mission through research focused on software security testing and analysis. His work on grammar-based testing and fuzzing directly addresses critical security challenges in modern software systems, with practical applications for improving software resilience against attacks.

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