جست‌وجوی استاد و پژوهشگر

Yue Liمشاهده پروفایل

دانشیار

• Program Analysis
• Programming Languages
• Static Program Analysis
• +۳ مورد دیگر

Yue Li is an Associate Professor at the School of Computer Science, Nanjing University, where they co-run the PASCAL Research Group with Tian Tan. Their work focuses on static program analysis techniques and tools for programming languages, software engineering, security, and hardware verification. PhD in Computer Science from UNSW Sydney (2016) Postdoctoral research at Aarhus University (Denmark) and UNSW Sydney B.Eng and M.Eng from Northwestern Polytechnical University (2010, 2012) Research interests center on Program Analysis and Programming Languages , with a focus on: Pointer analysis for database-backed applications Context sensitivity optimization Reflection analysis in Java/Android Operational semantics for hardware languages Distributed dataflow analysis frameworks Developer-friendly static analysis tools Key publication trends (2016-2025) span static analysis , pointer precision , reflection handling , and tool frameworks across conferences like OOPSLA, PLDI, ICSE, ISSTA, and journals including TOPLAS and IEEE TSE. Notable artifacts include Tai-e and Chianina systems. 2025: ICSE Best Artifact & Distinguished Paper Awards 2024: IEEE TSE Publication on Generic Sensitivity 2023: OOPSLA Distinguished Artifact, SPLASH/ECOOP committees 2021: National Youth Talent Support Program, ZiJin Scholar 2016: ECOOP Distinguished Paper, CGO Best Paper As co-PI of PASCAL Research Group, they lead projects on precision-guided analysis, microservice systems, and cloud-based dataflow frameworks, with teaching awards for SICP and Software Analysis courses.

• Eye tracking
• Online teaching
• Human-computer interaction
• +۵ مورد دیگر

Marian Sauter is a researcher at Ulm University's Institute for Psychology in Germany, specializing in the intersection of psychology, human-computer interaction, and educational technology. Her work primarily focuses on eye-tracking methodologies and gaze analysis to improve online teaching and learning environments. She frequently collaborates with colleagues from the Institute of Media Informatics at Ulm University, indicating strong interdisciplinary connections between psychology and computer science departments. Her research interests center on understanding visual attention patterns in educational contexts, particularly how gaze behavior correlates with learning outcomes in digital environments. Dr. Sauter investigates how eye movement data can be visualized and utilized to optimize instructional design, with specific attention to gaze-laser pointer relationships, gaze synchronicity among students, and attention monitoring in virtual classrooms. Her work bridges cognitive psychology theories with practical applications for e-learning platforms and remote education systems. Analysis of her recent publications reveals a strong trajectory in applying eye-tracking technology to solve real-world educational challenges, particularly those emerging during and after the pandemic-driven shift to online learning. Her research spans both theoretical investigations of visual attention mechanisms and practical implementations for educational technology. The consistent focus on webcam-based eye-tracking demonstrates her commitment to developing accessible methods that don't require specialized hardware, making her research particularly relevant for widespread educational applications. Best Paper Award at ETRA '22 Symposium on Eye Tracking Research and Applications Berlin Health Award (2023) Dr. Sauter's collaborative approach is evident in her frequent co-authorship with Tobias Wagner from Ulm University's Institute of Media Informatics and Anke Huckauf from General Psychology. Her research appears to be supported by institutional resources at Ulm University, though specific external grants are not mentioned in the available information. She appears to be actively mentoring students given her involvement in educational psychology research and student-focused studies. Her work suggests involvement with research groups focused on human-computer interaction, educational technology, and cognitive psychology at Ulm University, though specific lab names are not provided in the available information. The interdisciplinary nature of her publications indicates collaboration across psychology and media informatics departments.

Jingling Xueمشاهده پروفایل

استاد

• Programming Languages
• Compilers
• Program Analysis
• +۵ مورد دیگر

Jingling Xue is a Scientia Professor at the School of Computer Science and Engineering at the University of New South Wales (UNSW) in Sydney, Australia. As an IEEE Fellow of the Computer Society, he leads the Programming Languages and Compilers research group, focusing on practical applications of compiler optimization and program analysis techniques. His work bridges theoretical foundations with real-world software systems, particularly in developing open-source tools for large-scale program analysis. Professor Xue received his B.Eng and M.Eng degrees from Tsinghua University in 1984 and 1987, respectively, followed by a PhD from the University of Edinburgh in 1992. His academic journey has established him as a leading figure in programming languages and compiler technology. Xue's research spans programming languages, compiler technology, and program analysis with emphasis on practical relevance. His current projects include compiler techniques for improving parallelism and locality, pointer/alias analysis for million-line-scale programs, and static/dynamic analysis for detecting bugs and security vulnerabilities in real-world applications like web browsers and Android apps. His group actively develops open-source tools to support scientific replicability and reproducibility in these areas. His recent publications demonstrate a strong focus on applying program analysis techniques to modern challenges including AI compilers, homomorphic encryption, security vulnerability detection, and graph processing systems. The work shows evolution from traditional compiler optimization to addressing emerging domains like privacy-preserving computation and deep learning systems while maintaining rigorous theoretical foundations. Scientific Awards: Best Paper Award at CGO'13 Best Paper Award at CGO'16 Distinguished Paper Award at ECOOP'16 Distinguished Paper Award at ICSE'18 Distinguished Paper Award at ISSTA'19 Distinguished Paper Award at ASE'19 Distinguished Artifact Award at ISSTA'23 Best Artifact Award at FSE'23 Distinguished Paper Award at ASE'23 Test-of-Time Award at CGO'21 Professor Xue has successfully supervised 30 PhD students to completion, many of whom now work as professors or researchers in academia and industry. He has served as Program Chair for major conferences including LCTES'13, CC'18, CGO'20, and General Chair for LCTES'20. His group currently focuses on memory safety in Rust, smart contract analysis, AI compilers, compilation for privacy-preserving computation, and adversarial attacks in deep learning. The Programming Languages and Compilers group maintains strong connections with industry partners, translating theoretical advances into practical tools for real-world software development challenges. Their work on pointer analysis, memory safety, and compiler optimizations continues to influence both academic research and industrial practice.

Patrick Lamمشاهده پروفایل

دانشیار

• Static Program Analysis
• Verifiable Software Specifications
• Software Engineering
• +۸ مورد دیگر

Patrick Lam is an Associate Professor in the Department of Electrical and Computer Engineering at the University of Waterloo, with a cross-appointment to the Cheriton School of Computer Science. His research focuses on applications of programming languages and static analysis to software engineering challenges, emphasizing verifiable software specifications and program understanding. Dr. Lam has held significant grants from NSERC and is recognized for his impactful work, including the First Decade High Impact Paper award for his Soot framework. Education: Doctorate in Computer Science, Massachusetts Institute of Technology, 2007 Master's in Computer Science, McGill University, 2000 Bachelor's in Joint Honours Mathematics and Computer Science, McGill University, 1999 Research Interests: His primary areas include static program analysis, verifiable software specifications, and compiler design, with a focus on linking high-level software designs to low-level implementations. He explores techniques like lightweight specifications and domain-specific languages to enhance software reliability and efficiency. Recent work also addresses empirical studies of programming practices and security through modularization. Publications: Dr. Lam's recent publications span advancements in static analysis tools (e.g., WasmWalker for WebAssembly), formal verification of code generated by AI tools like GitHub Copilot, and empirical studies on C++ immutability usage. His work bridges theoretical programming language research with practical software engineering applications, emphasizing tools for developer productivity and code reliability. Awards and Recognition: First Decade High Impact Paper recognition for "Soot – A Java Optimization Framework" (2010) Teaching and Grants: He has taught courses such as CS 447, ECE 453, and ECE 459 on software testing and performance programming. Active in grant-funded research, he secured NSERC Engage Grant (2013) and an ongoing NSERC Discovery Grant (2013–2018). Lam has also advised graduate students and contributed to the Software Engineering Program at Waterloo as its Director (2016–2019). Labs and Teams: His research group explores topics in program analysis and software engineering, with collaborations on projects like abstract debugging tools (GobPie) and static analysis frameworks (Soot). He maintains an open-source repository on GitHub, contributing to educational materials and research tools.

Gustavo Adolfo Junipero Rodriguez-Riveraمشاهده پروفایل

عضو هیئت علمی

• Operating Systems
• Computer Networks
• Memory Management
• +۱۱ مورد دیگر

Gustavo Rodriguez-Rivera is an Associate Teaching Professor in the Department of Computer Science at Purdue University, part of the School of Science. He joined the department in 2000 and holds a Ph.D. in Computer Science from Purdue University (1998), an M.S. in Electrical Engineering from ITESM Campus Monterrey (1990), and a B.S. in Electrical Engineering from the same institution (1985). His research focuses on Operating Systems, Computer Networks, Memory Management, Embedded Systems, Real-Time Systems, and broader areas like Numerical Analysis and Artificial Intelligence. Dr. Rodriguez-Rivera has received multiple teaching awards, including the ACM Faculty Award in Computer Science (2020, 2023) and Best Teacher in the School of Science (2014, 2016). His work spans software engineering education, structural health monitoring for wind turbines, and memory management algorithms. Notable publications include studies on garbage collection techniques, real-time project tracking in programming courses, and vibro-acoustic modulation for turbine blade inspection. He has advised numerous projects and contributed to grants such as the NSF-funded work on wind turbine blade monitoring. His academic contributions also include developing secure programming course modules and tools for interactive debugging systems.

Michael A. Benderمشاهده پروفایل

استاد

• Algorithms
• Data Structures
• Cache and I/O-Efficient Computing
• +۷ مورد دیگر

Michael A. Bender is the John L. Hennessy Chaired Professor of Computer Science at Stony Brook University. His work spans both theoretical and applied domains in algorithms, data structures, and storage systems. He co-founded Tokutek, Inc., a database company acquired by Percona in 2015, and has held visiting positions at MIT and King's College London. Education: PhD in Computer Science from Harvard University (1998), DEA and Magistère in Computer Science from École Normale Supérieure de Lyon (1993), BA in Applied Mathematics from Harvard (1992). His research focuses on cache-oblivious algorithms , I/O-efficient computing , parallel systems , and scheduling . His work addresses scalability in large-scale data management and computational geometry, with applications in bioinformatics and robotics. The 15 most recent publications highlight advancements in list labeling , hash table design , graph algorithms , and memory optimization . These papers reflect his commitment to solving practical problems with rigorous algorithmic approaches. Awards include: PODS Best Paper Award (2024) ASPLOS Distinguished Paper Award (2023) USENIX FAST Best Paper Award (2016) Chancellor's Award for Excellence in Teaching (2015) R&D 100 Award (2006) He has led the Stony Brook Computer Science Honors Program and advised graduate students in algorithmic research. His grants portfolio includes 39 funded projects, emphasizing algorithm engineering and systems optimization.

• High-Performance Computing
• Parallel Programming
• Domain-Specific Languages
• +۳ مورد دیگر

Wenguang Chen is a researcher affiliated with Tsinghua University and Pengcheng Laboratory , specializing in computer science and high-performance computing . His work bridges theoretical advancements with practical applications in domain-specific languages , parallel programming , and machine learning . Research Interests include: Development of modular DSLs for numerical methods (e.g., Mat2Stencil) Performance optimization in distributed and parallel systems Compiler frameworks for privacy-preserving AI (e.g., FHE-based neural network inference) Graph algorithms scaling to trillion-edge datasets Applications of Rust in memory-safe pointer analysis Recent Publications span 2014–2025, focusing on: Parallelization strategies for supercomputing Compiler automation tools Extreme-scale data processing Performance variance diagnosis in production environments

Andrew Kwongمشاهده پروفایل

استادیار

• Computer Security
• Applied Cryptography
• Side-Channel Attacks
• +۳ مورد دیگر

Andrew Kwong is an Assistant Professor in the Department of Computer Science at the University of North Carolina at Chapel Hill, specializing in computer security and applied cryptography with a focus on side-channel attacks and defenses. His research bridges hardware vulnerabilities and cryptographic systems, particularly targeting microarchitectural weaknesses. His primary research interests include Rowhammer-based exploits , side-channel attacks on cryptographic implementations , hardware security modules , and microarchitectural vulnerabilities . Kwong investigates how physical hardware properties (e.g., DRAM disturbance errors, cache hierarchies, acoustic properties) can compromise system security, with recent work demonstrating end-to-end key recovery against post-quantum cryptography and novel Rowhammer amplification techniques. His publication record features high-impact venues including IEEE S&P (5 papers), USENIX Security (4 papers), and CCS (2 papers), with notable work When Frodo Flips receiving a Best Paper Award Honorable Mention at CCS 2022. Research trends show consistent focus on practical hardware-assisted attacks, evolving from acoustic side-channels (2018-2019) to Rowhammer sophistication (2020-2025). Best Paper Award Honorable Mention (CCS 2022) Kwong teaches graduate courses including Hardware Security and Side-Channels (COMP 790-184) and Research Topics in Computer Security (COMP 790-185), emphasizing hands-on lab assignments for conducting and defending against hardware attacks. His syllabi cover foundational topics like cache side-channels, Spectre variants, Rowhammer, and trusted execution environments, requiring students to implement real-world attacks through programming assignments.

Sandrine Blazyمشاهده پروفایل

استاد

• Formal verification
• Semantics of programming languages
• Compilers
• +۳ مورد دیگر

Sandrine Blazy is a Professor in the Computer Science Department at the University of Rennes, France. She is a member of CELTIQUE (also referred to as Epicure), a joint project-team with Inria Rennes Bretagne Atlantique and the IRISA laboratory. Since 2021, she has served as deputy director of the IRISA CNRS UMR 6074 laboratory and will be the general chair for POPL 2026, which will be held in Rennes. She is also a member of the editorial board of the LMCS journal. Dr. Blazy completed her PhD at CNAM (Conservatoire National des Arts et Métiers) in 1993 with a thesis titled "La spécialisation de programmes pour l'aide à la maintenance du logiciel" (Program Specialization for Software Maintenance Assistance). She later completed her Habilitation à diriger des recherches (HDR) in 2008 at the University of Évry Val d'Essonne with a thesis titled "Sémantiques formelles" (Formal Semantics). Her research focuses on the formal verification of program transformations and semantic properties of programming languages, particularly in the context of the CompCert compiler and Verasco static analyzer. She develops mechanized semantics using the Coq (or Rocq) proof assistant to ensure software correctness and security. A prime application domain of her work is software security, including constant-time programming for cryptographic applications and software obfuscation techniques. Her teaching includes mechanized semantics (in Coq), functional programming (in OCaml), formal methods (using Why3), and software vulnerabilities. Dr. Blazy's publication record from 2019-2025 shows a sustained focus on verified compilation techniques, particularly in preserving security properties during compilation. Her work bridges theoretical formal methods with practical compiler implementation, resulting in tools that have real-world impact in safety-critical systems. She has made significant contributions to the CompCert formally verified compiler project, with particular attention to constant-time preservation for cryptographic applications and JIT compilation verification. Her scientific achievements have been recognized with several major awards: CNRS Silver Medal (2023) Lucas Award from Formal Methods Europe (2023) ACM SIGPLAN Programming Languages Software Award for CompCert (2022) ACM Software System Award for CompCert (2021) Dr. Blazy has been actively involved in the programming languages research community, serving on numerous program committees for major conferences including POPL, ICFP, PLDI, and CPP. She has mentored students and contributed to education through teaching mechanized semantics and formal methods. Her work with the CompCert compiler has led to practical applications in safety-critical systems, with industry collaborations documented in publications like "CompCert: Practical experience on integrating and qualifying a formally verified optimizing compiler" (ERTS 2018). She leads research within the CELTIQUE project team, which focuses on developing trustworthy software using deductive verification. Her team works on advancing the state of the art in formal verification of compilers and static analyzers, with applications in security-critical domains including cryptographic implementations and safety-critical embedded systems.

• Object-Oriented Programming
• Software Engineering
• Formal Methods
• +۵ مورد دیگر

Bertrand Meyer is a renowned academic and software engineering expert affiliated with Constructor University in Switzerland. He previously held positions at ETH Zurich (2001-2016), the University of Toulouse (2015-2016), and Monash University. His research focuses on object-oriented programming, software engineering, formal methods, and programming languages. He is best known for developing the Eiffel programming language and pioneering the 'Design by Contract' paradigm. Meyer earned his PhD from the University of Nancy, France. His contributions include seminal textbooks like *Object-Oriented Software Construction* (1988, 1997), *Touch of Class* (2009), and *Agile!* (2014). He has received the ACM Software System Award (2006) for his work on Eiffel. His research emphasizes rigorous software design principles, formal verification, and practical software engineering practices. Key innovations include: Design by Contract methodology Advancements in object-oriented design patterns Contributions to component-based development Work on software testing and validation techniques Meyer has authored over 374 publications spanning journals, conferences, and books. His work bridges theoretical foundations and practical software development methodologies.

• Computer Engineering
• Information Systems Engineering
• Operating Systems
• +۴ مورد دیگر

M. Anton Ertl is an Associate Professor at TU Wien's Faculty of Informatics, Department of Compilers and Languages. His roles include teaching courses such as 'Compilers,' 'Efficient Programs,' and 'Stack-based languages.' He specializes in compiler back-ends, Forth, interpreters, programming languages, operating systems, and computer architectures. Ertl's research focuses on optimizing interpreters, compiler design, and hardware security, particularly addressing vulnerabilities like Spectre. His research interests span interpreter performance, compiler optimization, and Forth language evolution. Recent work includes exploring hardware-based Spectre mitigation, decompilers for Gforth, and stack-based language efficiency. He actively contributes to the EuroForth conferences as an editor and presenter. Ertl supervises students on topics like compiler construction, reverse engineering, and interpreter optimization. His academic contributions include over 50 publications, with a focus on virtual machine performance, compiler back-ends, and Forth-related advancements. He is a key figure in the Gforth project and regularly teaches advanced courses on programming languages and computer systems.

James Brotherstonمشاهده پروفایل

استاد

• Logic
• Computation
• Separation Logic
• +۵ مورد دیگر

James Brotherston is Professor of Logic and Computation in the Programming Principles, Logic and Verification Group (PPLV) at University College London's Department of Computer Science. His research spans logic, computation, and verification, with a focus on separation logic, cyclic proofs, and automated reasoning for program correctness. Research interests include: Foundations of program verification using separation logic Automated reasoning via cyclic proof systems Concurrency and deadlock detection Formal methods for security and resource management Applications of substructural logics in computer science His publications demonstrate consistent focus on logical foundations of verification, with recent work expanding into concurrency testing and atomic operations compatibility. Trends include theoretical advances in proof systems alongside practical verification tools. Scientific awards and grants: Facebook Testing and Verification Research Award (2019) £6M EPSRC Programme Grant for IRIS project (2018-2024) Facebook Faculty Grant (2015) Multiple EPSRC fellowships and grants totaling over £1.2M (2008-2017) He has supervised 12+ PhD students and research fellows, with current students working on verification of concurrent systems. Leads research in the PPLV group and collaborates internationally on logical frameworks.

• Formal Methods of Software Engineering
• Operating Systems Verification
• Critical Systems Development
• +۵ مورد دیگر

Alexey Vladimirovich Khoroshilov is an Associate Professor at the Faculty of Computer Science of the National Research University Higher School of Economics (HSE), affiliated with the Basic Department "System Programming" of the Institute for System Programming named after V.P. Ivannikov of the Russian Academy of Sciences (ISP RAS). He joined HSE in 2015, bringing 20 years of scientific and teaching experience to his position. His academic background includes a Candidate of Physical and Mathematical Sciences degree (2006) and a specialty in Applied Mathematics and Computer Science from Moscow State University named after M.V. Lomonosov (2001), with the qualification of Mathematician and Systems Programmer. His primary research interests focus on formal methods of software engineering, particularly in the verification and validation of critical systems. He specializes in methods for designing and developing critical systems, formal verification techniques, model-based testing, and requirements analysis. His work has significant applications in operating systems security, real-time systems, and safety-critical software development. His recent publications demonstrate a strong focus on operating system verification, with particular emphasis on abstract model-based runtime verification, security policy integration, and multi-level requirements compliance. His research often combines theoretical formal methods with practical applications in operating system security and verification. The recurring themes across his work include component-based verification approaches, thread-modular analysis techniques, and formal modeling of security policies. Khoroshilov maintains a strong connection with the Institute for System Programming of the Russian Academy of Sciences, where he has worked since 1999 and held the position of leading research fellow as of 2014. He also teaches at Moscow State University's Department of System Programming within the Faculty of Computational Mathematics and Cybernetics since 2009. His teaching focuses on operating system development, particularly courses on the design of operating system kernels for both bachelor's and master's programs. His technical expertise includes verification of operating system components, security policy implementation, and requirements management for critical systems. He has contributed to significant projects related to aviation real-time operating systems, formal security models, and Linux kernel verification.

Bryan Wardمشاهده پروفایل

استادیار

• Real-Time Systems
• Embedded Systems Security
• Cyber-Physical Systems
• +۳ مورد دیگر

Bryan Ward is an Assistant Professor of Computer Science and Electrical and Computer Engineering at Vanderbilt University's School of Engineering. His research focuses on enhancing the security and resilience of real-time and embedded systems in critical domains such as industrial control systems and space systems. Ward holds a Ph.D. in Computer Science from the University of North Carolina at Chapel Hill, along with dual bachelor's degrees in Computer Science and Engineering and Mathematics from Bucknell University. His academic contributions span multiple areas including operating system security, real-time scheduling, and hardware-software co-design for safety-critical systems. Key research themes include control-flow integrity, secure resource management in multi-core environments, and mitigating timing-based attacks in real-time embedded systems. Ward's work has explored advanced defense mechanisms like dynamic address space randomization, tagged architecture implementations, and retry-free transactional memory models. He has also investigated vulnerabilities in kernel scheduling and cache-sharing behaviors in multi-core platforms, proposing novel solutions to ensure predictability and security. Current projects emphasize securing cyber-physical systems through adaptive defenses that maintain strict timing guarantees required for safety-critical applications.

Jan Pfisterمشاهده پروفایل

پژوهشگر

• Natural Language Processing
• Deep Learning
• Sentiment Analysis
• +۵ مورد دیگر

Jan Pfister is a researcher at the Chair of Data Science (Informatik X) , affiliated with the Faculty of Mathematics and Computer Science at the University of Würzburg . Holding an M.Sc. in Computer Science from 2021, he contributes to the DMIR group while maintaining the BibSonomy platform. His work bridges Natural Language Processing and Deep Learning , with a focus on structured sentiment analysis and German language modeling. His research explores the integration of Large Language Models with Pointer Networks to extract fine-grained sentiment information. He has developed ModernGBERT , a German-only encoder model, and LLäMmlein , advancing NLP capabilities for the language. Pfister's recent publications highlight trends in encoder-decoder architectures, model-agnostic hallucination detection, and multi-label classification frameworks that refine LLM outputs. He has taught courses including Information Retrieval (SS '22), Text Mining (WS '23), and Selected Topics in Machine Learning (SS'21, WS '21, WS'24). His collaborative projects span medical informatics, human-AI interaction, and social media analysis, often involving interdisciplinary teams and real-world data.