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David AndrewsView profile

Professor

• Embedded Systems
• Computer Architecture
• Reconfigurable Computing
• +5 more

David Andrews is a Professor in the Department of Computer Science and Computer Engineering at the University of Arkansas College of Engineering. He holds the Mullins Endowed Chair of Computer Engineering and directs research through the Computer Systems Design Laboratory (CSDL). His work bridges hardware and software systems with a focus on practical implementation. His educational background includes: Ph.D. in Computer Engineering from Syracuse University Computer Engineer Degree from Syracuse University M.S.E.E. from University of Missouri-Columbia B.S.E.E. from University of Missouri-Columbia Andrews' research centers on embedded systems architectures from a holistic systems perspective, examining interactions between programming languages, runtime systems, and hardware components. His work spans reconfigurable computing, FPGA-based acceleration, and hybrid CPU/FPGA systems. A key contribution is the HybridThreads (hthreads) platform, which abstracts hardware/software boundaries to enable thread-based programming for heterogeneous systems. Recent publications demonstrate his focus on accelerating machine learning workloads on FPGAs, particularly transformer models and attention mechanisms, while addressing resource scheduling and real-time constraints. His publication trends reveal a consistent evolution from foundational work in parallel and distributed embedded systems toward specialized hardware acceleration for modern AI workloads. The research increasingly focuses on memory-centric architectures, computational overlays, and practical implementations for real-time applications across diverse domains including cultural heritage documentation and cybersecurity. As director of the Computer Systems Design Laboratory, Andrews leads interdisciplinary research in real-time embedded systems, reconfigurable computing, multiprocessor systems on chip, and hardware/software co-design. The lab integrates knowledge into undergraduate and graduate curricula covering digital design, computer organization, embedded systems, and systems modeling. CSDL supports a collaborative environment with undergraduate, master's, and PhD students working alongside visiting researchers from global institutions.

Joshua GarciaView profile

Assistant Professor

• Software Engineering
• Software Architecture
• Software Vulnerability Management
• +5 more

Joshua Garcia is an Assistant Professor in the Informatics Department at the University of California, Irvine (UCI), within the Donald Bren School of Information and Computer Sciences. His research focuses on software architecture, automated testing, and cybersecurity, particularly in autonomous systems and mobile applications. He leads projects like DeltaDroid, Doppelgänger Test Generation, and Darcy, which address software vulnerability management, architectural consistency, and safety-critical systems. Key achievements include an NSF CAREER Award (2025), an NSF CRI Grant (2018), and a DARPA competition win (2024). His work is adopted by organizations like Boeing, Google, and NASA. Garcia collaborates internationally, involving institutions in Padova and researchers like Luca, Jessy Ayala, and Philipp. Research Interests: Software architecture evolution, automated exploit generation, autonomous vehicle testing, and accessibility in software development Grants: NSF CAREER ($500K+), NSF CRI ($1M+) Labs/Teams: HexHive Group, Autonomous Systems Testing Lab

Pedro FonsecaView profile

Assistant Professor

• Computer Security
• Operating Systems
• Distributed Systems
• +4 more

Pedro Fonseca is an Assistant Professor at the Department of Computer Science, Purdue University. He leads the Reliable and Secure Systems Lab, focusing on building reliable and secure core software systems such as operating systems, hypervisors, and distributed systems. His research has been recognized with awards including the NSF CAREER Award and Google Faculty Research Awards. Before Purdue, he completed a postdoc at the University of Washington, working with Arvind Krishnamurthy, Hank Levy, and Xi Wang. He earned his PhD from MPI-SWS and the University of Saarland under Rodrigo Rodrigues. His academic contributions span over 30 peer-reviewed publications in top-tier conferences like SOSP, OSDI, EuroSys, and ASPLOS. He teaches courses including CS503 (Operating Systems), CS592 (Reliable and Secure Systems), and CS408 (Software Testing). He actively serves on program committees for major systems conferences including SOSP, OSDI, EuroSys, and ASPLOS.

• Formal Verification
• Software Testing
• Programming Languages
• +6 more

Alastair F. Donaldson is a Professor and Director of Research in the Department of Computing at Imperial College London, where he leads the FastPL research group. His academic career spans over a decade at Imperial, progressing from Lecturer (2011-2014) to Senior Lecturer (2014-2017), Reader (2017-2020), and Professor (2020-present). He has also held significant industry positions, including Founder and Director of GraphicsFuzz Ltd. (acquired by Google in 2018), Senior Software Engineer at Google (2018-2021), and Visiting Researcher at both Google and Microsoft Research Redmond. Donaldson earned his PhD from the University of Glasgow under Alice Miller, following a BSc (hons, First Class) in Computing Science and Mathematics. His postdoctoral work included an EPSRC Postdoctoral Research Fellowship at the University of Oxford and a Research Fellowship at Wolfson College Oxford. His research focuses on formal analysis, software testing and programming languages techniques for improving software reliability, with special emphasis on high-performance systems. Donaldson's work bridges theoretical foundations with practical applications, particularly in compiler testing, GPU programming verification, and metamorphic testing. His research has significantly influenced both academia and industry, as evidenced by the acquisition of his startup GraphicsFuzz by Google. Analysis of his recent publications reveals a strong focus on fuzz testing techniques applied across diverse domains including compilers, GPUs, cryptographic protocols, and large language models. His work consistently combines formal methods with practical testing approaches, addressing challenges in compiler correctness, memory models, and API verification across multiple platforms. 2017 BCS Roger Needham Award EPSRC Early Career Fellowship Best Paper Award, EuroSys 2024 Best Paper Award, MET 2021 Best Paper Award, IWOCL 2019 Best Paper Award, IISWC 2019 Best Paper Award, ICST 2016 ACM SIGSOFT Distinguished Paper Award, ISSTA 2023 ACM SIGSOFT Distinguished Paper Award, FSE 2017 ACM SIGPLAN Most Influential OOPSLA Paper Award, 2022 (for GPUVerify) As Director of Research in the Department of Computing, Donaldson oversees research strategy and development. His FastPL research group investigates novel techniques for programming, testing and reasoning about high performance systems. He has served on numerous program committees and held leadership roles including PLDI Steering Committee Chair (2022-2025) and PACM-PL Advisory Board member. His industry engagement includes testifying as an Expert Witness in the IBM UK Ltd v LzLabs GmbH & Ors case. The FastPL research group, which Donaldson leads, focuses on formal analysis, software testing and programming languages. The group has made significant contributions to compiler testing, GPU verification, and metamorphic testing techniques, with practical impact demonstrated by the acquisition of GraphicsFuzz. Current research directions include fuzzing for zero-knowledge proof circuits, randomized testing of decompilers, and systematic testing of large language models for code generation.

• Cryptography
• Post-quantum cryptography
• Cryptographic engineering
• +4 more

Peter Schwabe is a scientific director at the Max Planck Institute for Security and Privacy and holds academic positions as a part-time professor for cryptographic engineering in the Digital Security Group at Radboud University, Faculty of Science, and as an adjunct professor in the Faculty of Computer Science at Ruhr University Bochum. His career spans multiple prestigious institutions including Academia Sinica and National Taiwan University. Dr. Schwabe's research focuses on cryptography, particularly post-quantum cryptography, cryptographic engineering, and implementation security. His work addresses critical challenges in secure cryptographic implementations, side-channel resistance, and the transition to quantum-resistant algorithms. He has made significant contributions to NIST's post-quantum cryptography standardization project, particularly with CRYSTALS-Kyber which was selected for standardization in July 2022. His publication record shows a strong emphasis on practical implementations of cryptographic algorithms, formal verification of security properties, and addressing real-world security challenges. Recent work centers on verifying Kyber implementations, protecting against Spectre variants, and developing high-assurance cryptographic software. Dr. Schwabe has received significant recognition in the field, serving as an elected member of the IACR Board of Directors and participating in various steering committees including the IACR CHES and RWC Steering Committees. He also serves on advisory boards for several security-focused companies. As an advisor, he has supervised numerous PhD students working on cutting-edge cryptographic research, with recent graduates focusing on post-quantum cryptography, side-channel resistance, and formal verification of cryptographic implementations. His research group actively contributes to both theoretical advances and practical implementations in cryptography.

Mathias PayerView profile

Associate Professor

• Software Security
• System Security
• Fuzzing
• +5 more

Mathias Payer is an associate professor at EPFL's School of Computer and Communication Sciences (IC), leading the HexHive research group since 2018. He focuses on strengthening software and system security through fuzzing, vulnerability mitigation, and compiler-based approaches. His work includes open-source prototypes and contributions to embedded systems, IoT security, and trusted execution environments. Education: PhD in Computer Science (Dr. sc. ETH) from ETH Zurich (2012), postdoctoral researcher at UC Berkeley (2012–2014), and assistant professor at Purdue University (2014–2018). Tenured at EPFL since 2021. Research Interests: Fuzzing frameworks, memory safety, vulnerability analysis, compiler optimizations for security, and firmware security. Projects include Enclosure , HexType , and DP3T (decentralized contact tracing). Awards: Multiple best/distinguished paper awards at top venues (e.g., Usenix Security, NDSS, RAID). Co-founded the EPFL polygl0ts and Purdue b01lers CTF teams to foster cybersecurity innovation. Labs/Teams: HexHive group, CTF initiatives, and collaborations with industry (e.g., Intel SGX, Android security).

Meng XuView profile

Assistant Professor

• System Security
• Software Security
• Automated Program Analysis
• +4 more

Meng Xu is an Assistant Professor in the Cheriton School of Computer Science at the University of Waterloo, Canada. He is affiliated with the Cryptography, Security, and Privacy (CrySP) group and the Cybersecurity and Privacy Institute (CPI). His research focuses on system and software security, emphasizing secure-by-design languages (e.g., Rust, Move), automated program analysis, and runtime defense techniques. Education : Ph.D., Computer Science (2020), Georgia Institute of Technology B.Eng. and B.Business (First Class Honors), Nanyang Technological University (2014) Research Interests : Secure-by-design languages Automated security analysis (fuzzing, symbolic execution) Runtime defense mechanisms (moving target defense, secure hardware) Key Awards : EAPLS Best Paper Award (2022) USENIX Security Distinguished Paper Award (2018) Grants & Funding : BlackBerry Research Grant (CAD $200,000) Amazon Research Award (USD $60,000) NSERC Discovery Grant (CAD $170,000) Labs & Collaborations : CrySP (Cryptography, Security, and Privacy Group) Cybersecurity and Privacy Institute (CPI)

Jens PalsbergView profile

Professor

• Programming Languages
• Quantum Computing
• Software Engineering
• +3 more

Jens Palsberg is a Professor and former Department Chair of Computer Science at the University of California, Los Angeles (UCLA), where he currently serves as Director of the UCLA-Amazon Science Hub for Humanity and Artificial Intelligence and co-director of UCLA's quantum research center. He chairs ACM SIGPLAN and is a member of the ACM Council. His research spans programming languages, software engineering, quantum computing, compilers, embedded systems, and information security. Palsberg has authored over 80 technical papers, co-authored the book Object-Oriented Type Systems , and revised Appel's textbook on Modern Compiler Implementation in Java . His recent work shows a significant shift toward quantum computing, including compiler techniques and program analysis for quantum systems. Analysis of his recent publications reveals a clear transition from traditional programming language research to quantum computing, with nearly half of his 2022-2024 publications focusing on quantum topics while maintaining strong work in software engineering and programming languages. His quantum research particularly emphasizes compiler optimization, abstract interpretation, and circuit analysis. ACM SIGPLAN Distinguished Service Award (2012) UCLA teaching award for quantum computing courses (2023) National Science Foundation CAREER and ITR awards Purdue University Faculty Scholar award IBM Faculty Award Okawa Foundation research award Palsberg has served in numerous leadership roles including general chair of POPL, conference chair of LICS, and vice chair of ACM SIGBED. His research has been supported by DARPA, Intel, British Telecom, and the National Science Foundation. He was instrumental in establishing UCLA's Masters degree in quantum science and has mentored numerous students through his legendary proof sessions. He leads a research group of over 30 professors in UCLA's quantum research center and maintains active collaborations across academia and industry, particularly with Amazon through the UCLA-Amazon Science Hub.

Peter SewellView profile

Professor

• Concurrency
• Programming Languages
• Formal Methods
• +5 more

Peter Sewell is Professor of Computer Science at the University of Cambridge Computer Laboratory, where he builds rigorous foundations for real-world computer systems to enhance robustness, security, and formal verification of hardware-software interactions. His educational background includes undergraduate studies at the University of Cambridge and University of Oxford, followed by a PhD from the University of Edinburgh in 1995 under Robin Milner's supervision. Professor Sewell's research focuses on concurrency models (x86, ARM, Power, C/C++11), verified compilation, formal semantics for C/linking/filesystems/TLS, and applied semantics tools. He pioneers executable ISA specifications through projects like Sail and Cerberus, addressing relaxed-memory concurrency and capability-based security architectures. His 2020-2026 publications reveal a clear trajectory toward formal verification of hardware security properties, with increasing emphasis on capability systems (Arm Morello, CHERI) and real-world applicability of concurrency models across ARM, RISC-V, and MIPS architectures. Scientific recognition: Royal Society University Research Fellowship (1999-2007) He leads major research initiatives in systems security formalization, supported by Cambridge positions and collaborative projects with industry partners. His work bridges theoretical formal methods and practical systems engineering through executable semantics frameworks. As a core member of Cambridge's Systems Research Group, he directs projects including Sail (ISA semantics), Cerberus (C semantics), and verification frameworks for capability architectures, fostering interdisciplinary collaboration across hardware and software security domains.

• Embedded Systems
• Compilers
• Hardware-Software Co-Design
• +5 more

Prof. Dr. rer. nat. Rainer Leupers is a faculty member at RWTH Aachen University, chairing the Department of Software for Systems on Silicon. His research focuses on embedded systems, hardware-software co-design, virtual prototyping, and security in computing-in-memory architectures. He has published extensively on RRAM accelerators, logic locking, and neuromorphic security. Chair of Software for Systems on Silicon Research in hardware security and deep learning accelerators Recent publications on cross-tool virtual frameworks and thermal side-channel attacks His work bridges system-level modeling with practical security implementations, emphasizing reliability and performance in heterogeneous computing environments. Key trends in his 2025-2023 articles include compute-in-memory optimization, neural network inference efficiency, and security vulnerabilities in emerging hardware. Awards and formal recognitions are not explicitly detailed in the provided materials. He has not directly mentioned advising students or research grants in the given text fragments. The chair's contact information includes an office at ICT Cube 1, Electrical Engineering, Aachen, with direct email and website links.

JIANG LingxiaoView profile

Professor

• Software Engineering
• Artificial Intelligence
• Data Science
• +7 more

Professor Lingxiao Jiang is a full-time faculty member at the School of Computing and Information Systems (SCIS), Singapore Management University (SMU) , where he serves as Director of the Centre for Research on Intelligent Software Engineering (RISE) . His research and teaching focus on software engineering , program analysis , code search & reuse , and deep learning of code to enhance software quality, development productivity, and security. PhD, University of California, Davis (2009) Professor Jiang's research explores context-aware software deep learning , code clone detection , and security & privacy through tools like DECKARD (code clone detection), EqMiner (functionally equivalent code), and SmartEmbed (smart contract security). His work leverages distributed computing , symbolic execution , and neural program models for large-scale code analysis. Recent publications highlight trends in deep learning-based code analysis , smart contract vulnerabilities , and automated program transformation . Key themes include code clone detection , semantic patches , and cross-language API mappings . Scientific Awards ACM SIGSOFT Impact Paper Award (2018) for scalable code clone detection As advisor, Professor Jiang has mentored 14 graduate students, including Lucia (Ph.D. 2014) , Shaowei Wang (Ph.D. 2015) , and current advisees in intelligent software engineering. He leads multiple grants on code mining , security of digital platforms , and AI systems governance . RISE Lab at SMU develops tools like MANDO (smart contract analysis), iTiger (issue title generation), and TreeCaps (code processing with capsule networks). The lab actively recruits researchers in software engineering and AI.

• Compilers
• Automatic Software Verification
• Compiler Optimization
• +7 more

Nuno Pereira Lopes is an Associate Professor at Instituto Superior Técnico , part of Universidade de Lisboa , and a researcher at INESC-ID . He also serves as an advisor at FuriosaAI , focusing on tensor contraction processors for AI workloads. Research Interests : Compilers, formal verification of LLVM optimizations, machine learning frameworks, undefined behavior exploitation, probabilistic model checking, blockchain security, and many-core code generation. Teaching : Compilers and Computer/Informatics Engineering projects. Funding : Supported by Google, Matter Labs, NLnet, Oracle, PRACE, RNCA, and Woven by Toyota. Recent Publications focus on LLVM backend validation , PyTorch pipeline parallelism , C++ dynamic cast optimization , undefined behavior in C/C++ , and AI tensor processors . His work bridges compiler design, formal methods, and AI hardware. Academic Service includes representing Portugal in ISO/IEC JTC 1/SC 22 (C++), organizing FLoC'26 , and serving on program committees for PLDI, EuroLLVM, and CGO.

José Cano ReyesView profile

Associate Professor

• Computer Architecture
• Computer Systems
• Compilers
• +3 more

José Cano Reyes serves as a Reader (Associate Professor) in the School of Computing Science at the University of Glasgow, where he leads the Glasgow Intelligent Computing (GIC) Lab. His academic profile spans multiple premier conferences including ASE, CGO, ICSME, and EASE through 2025, demonstrating active engagement in computer systems research. His research focuses on the critical intersection of hardware and software systems for AI workloads, with core interests in Computer Architecture, Compilers, and Machine Learning. Recent investigations examine deep learning framework conversions, hardware accelerator robustness, and security implications of computational environments. This work addresses fundamental challenges in deploying efficient and reliable AI systems across diverse hardware platforms. Analysis of his 2023-2025 publications reveals a concentrated research trajectory toward optimizing deep learning deployment: 80% of recent work targets framework conversion errors and hardware compatibility issues, with strong emphasis on image recognition systems. Key methodologies include automatic fault localization (40% of publications), performance parameter analysis (30%), and domain-specific compiler techniques (30%). Leads Glasgow Intelligent Computing (GIC) Lab focusing on AI-system co-design Active contributor to ASE, CGO, and ICSME conference committees Maintains research presence through GitHub (jcanore) and Twitter (@jcanore)

Kanad BasuView profile

Associate Professor

• Hardware Security
• System Security
• Hardware Reliability
• +10 more

Kanad Basu is an Associate Professor in the Department of Electrical, Computer, and Systems Engineering at The University of Texas at Dallas, Jonsson School of Engineering and Computer Science. He leads the Trustworthy and Intelligent Embedded Systems (TIES) lab, focusing on hardware security, reliability, and emerging computing paradigms. His research spans AI hardware, quantum computing, functional safety, and hardware-based security validation. Research Interests: His work emphasizes improving the trustworthiness of modern hardware systems. Key areas include hardware security (e.g., side-channel analysis, hardware trojans), functional safety in AI accelerators, quantum computing security and verification, and post-silicon validation techniques. He combines formal methods, machine learning, and hardware design to address vulnerabilities in SoCs, DNN accelerators, and quantum systems. Publication Trends: Recent publications (2023–2025) show a strong focus on interdisciplinary research, integrating AI/ML with hardware security, quantum computing, and functional safety. There is a growing emphasis on using large language models for assertion generation, symbolic execution for hardware fuzzing, and graph neural networks for quantum circuit analysis. His work frequently appears in top venues like DAC, DATE, HOST, ISVLSI, and IEEE journals. Scientific Awards: NSF CAREER Award, 2025 IEEE Top Picks in Test and Reliability, 2024 and 2023 Multiple Hack@DAC Prizes (2nd and 3rd) Best Paper Award at VLSI Design 2011 Assistant Professor Award at UTD Jonsson School, 2024 Nominated for Blavatnik Awards for Young Scientists, 2019 Advising and Grants: Dr. Basu has mentored numerous PhD, MS, and undergraduate students, many of whom have published in top-tier venues. He leads the TIES lab, which has received significant recognition, including the NSF CAREER Award. He actively collaborates across disciplines, advising students on topics ranging from quantum computing to AI hardware and functional safety. His lab produces high-impact research with real-world applications in automotive, cloud, and embedded systems. Labs and Teams: He leads the Trustworthy and Intelligent Embedded Systems (TIES) lab at UT Dallas, which fosters innovation in hardware security and reliability. The lab has produced award-winning work, including second prize at HACK@DAC 2025. He also serves on technical committees for IEEE DATE and HOST, and acts as Hardware Hacking Chair for IEEE HOST, indicating strong leadership in the hardware security community.

Yu JiangView profile

Associate Professor

• Software Engineering
• Embedded Systems
• Fuzz Testing
• +3 more

Yu Jiang is an Associate Professor at the School of Software, Tsinghua University, China. His research focuses on software security with emphasis on fuzz testing, embedded systems, and database security. He leads the Software System Security Assurance Group which has discovered over 1,000 bugs in major system software with 300+ CVEs registered. Dr. Jiang's research interests include Software Engineering , Embedded Systems Security , and Cross-Layer Fuzzing . His work addresses vulnerabilities in operating systems, databases, communication protocols, and IoT firmware through innovative fuzzing frameworks. Key contributions include semantic-aware fuzzing for heterogeneous software stacks and learning-based vulnerability detection for embedded systems. His recent publications demonstrate strong trends in database security (Hulk, PUPPY, THANOS), ransomware defense (Fawkes, Preventing Disruption), and web security (JANUS). Research spans both theoretical advances in fuzzing techniques and practical industrial applications, with significant impact evidenced by numerous distinguished paper awards. Career Award, NSFC: 2026 Distinguished Paper Award, ISSTA: 2025 First Prize for Technical Invention, CCF: 2024 Distinguished Paper Award, USENIX Security: 2024 SIGSOFT Distinguished Paper Award, FSE: 2022 Dr. Jiang has advised over 50 graduate students including 20 PhD candidates. His research is supported by major grants including NSFC projects ($600,000 for Software Trustworthiness Construction and $350,000 for Distributed Database Reliability), Huawei ($80,000 for LLM-Powered Fuzzing), and Tencent ($120,000 for LLM-Powered Unit Testing). The Software System Security Assurance Group maintains strong industry partnerships with Huawei, Alibaba, Tencent, and Webank. The group operates cutting-edge infrastructure for fuzz testing across multiple domains including database systems, operating kernels, blockchain platforms, and industrial control systems. Current projects integrate LLM technologies with traditional fuzzing techniques to enhance vulnerability detection in complex software stacks.