جست‌وجوی استاد و پژوهشگر

Sebastian Erdwegمشاهده پروفایل

استاد

• Programming Languages
• Software Engineering
• Incremental Computation
• +۷ مورد دیگر

Sebastian Erdweg is a Professor at the Institute of Programming and Software Engineering at Johannes Gutenberg University Mainz (JGU Mainz) in Germany. He actively contributes to the programming languages research community as evidenced by his extensive involvement in major conferences including PLDI, ECOOP, SPLASH, and ICFP. His leadership roles include serving as Workshops Co-Chair for ECOOP and ISSTA 2023, Steering Committee Chair for GPCE, and various program committee positions across multiple conferences. His research primarily focuses on programming language design and implementation, with particular expertise in incremental computation, Datalog-based systems, abstract interpretation, and language workbenches. Erdweg's work bridges theoretical foundations with practical applications in static analysis, compiler construction, and program transformation. His research demonstrates a consistent thread of improving developer productivity through better language design and tooling, with recent work emphasizing efficient incremental program analysis techniques. Erdweg's publication record shows a strong emphasis on Datalog as a foundation for program analysis, with increasing focus on incremental techniques and WebAssembly analysis in recent years. His work combines theoretical rigor with practical implementation, often resulting in open-source tools that advance the state of the art in language engineering. The consistent appearance of Datalog, incremental computation, and abstract interpretation across his publications indicates a cohesive research vision spanning over a decade. As an active member of the programming languages community, Erdweg has served in numerous organizational roles including Workshops Co-Chair for ECOOP and ISSTA 2023, Steering Committee Chair for GPCE, and various program committee positions. His contributions to conference organization demonstrate his standing within the academic community and commitment to advancing research in programming languages and software engineering.

Cormac Flanaganمشاهده پروفایل

استاد

• Programming Languages
• Security
• Information Flow Control
• +۴ مورد دیگر

Cormac Flanagan is a Professor in the Department of Computer Science and Engineering at the Baskin School of Engineering, University of California Santa Cruz. His research focuses on programming languages, security, and software verification, with particular expertise in concurrent programming, information flow control, and program analysis. Flanagan's research interests span multiple areas of programming languages and software security. He has made significant contributions to the fields of information flow control, concurrent programming verification, and dynamic analysis techniques. His work on dynamic race detection, particularly the FastTrack algorithm, has been highly influential in the field, earning him a PLDI Most Influential Paper Award. He has also pioneered techniques for secure information flow, including the development of faceted values and secure multi-execution approaches, which earned him a POPL Most Influential Paper Award. His recent publications demonstrate a continued focus on program verification, with particular attention to concurrent software, JavaScript verification, and serverless computing security. Flanagan's work often bridges theoretical foundations with practical implementations, resulting in tools like the Anchor Verifier for concurrent software that provide practical verification solutions for real-world programming challenges. Fellow of the Association for Computing Machinery Alfred P. Sloan Foundation Fellow POPL Most Influential Paper Award for 'Multiple Facets for Dynamic Information Flow' PLDI Most Influential Paper Award for 'FastTrack: Efficient and Precise Dynamic Race Detection' PLDI Most Influential Paper Award for 'Extended Static Checking for Java' ECOOP 2024 Distinguished Paper Award for 'Mover Logic: A Concurrent Program Logic for Reduction and Rely-Guarantee Reasoning' CSF Distinguished Paper Award for 'Transparent IFC Enforcement: Possibility and (In)Efficiency Results' PLDI Distinguished Artifact Award for 'BigFoot: Static Check Placement for Dynamic Race Detection' ECOOP Best Paper Award for 'RedCard: Redundant Check Elimination for Dynamic Race Detectors' ISSTA Distinguished Paper Award for 'Exploiting Purity for Atomicity' UCSC Excellence in Teaching Award Professor Flanagan has advised numerous PhD students who have gone on to successful careers in industry and academia, including positions at Google, Shape Security, and San Jose State University. He serves as Steering Committee Chair for the ACM Conference on Programming Language Design and Implementation (PLDI) and as Associate Editor for ACM Transactions on Programming Languages and Systems (TOPLAS). His research has been supported by various grants from funding agencies, though specific details are not provided in the available information. Flanagan leads research projects including the Anchor Verifier for Concurrent Software, data race detection tools, the RoadRunner dynamic analysis infrastructure, and work on cooperable concurrency. His research group at UC Santa Cruz focuses on developing practical techniques for ensuring software reliability and security, with applications to concurrent programming, web security, and cloud computing environments.

Matthew Flattمشاهده پروفایل

استاد

• Programming Languages
• Functional Programming
• Runtime Systems
• +۳ مورد دیگر

Matthew Flatt is a Professor in the School of Computing at the University of Utah, where he has been actively contributing to programming language research and development. His primary affiliation is with the PLT research group, which is responsible for the Racket programming language ecosystem. Flatt received his PhD from Rice University in 1999. His educational background laid the foundation for his extensive work in programming language design and implementation. His research focuses on extensible programming languages , runtime systems , and applications of functional programming . As one of the principal developers of the Racket programming language, Flatt has made significant contributions to macro systems, language composition, and domain-specific language design. His work demonstrates how language-oriented programming can solve complex software engineering challenges through careful language design and implementation techniques. Flatt has served in numerous leadership roles in major programming language conferences including as Program Chair for DLS 2020, ICFP 2018, and GPCE 2017, and as Program Committee member for numerous SIGPLAN conferences including PLDI, POPL, ICFP, and SPLASH across multiple years. His conference contributions reveal a consistent focus on practical language implementation techniques and metaprogramming systems. As an educator, Flatt has developed and taught courses on programming languages, computer systems, and software engineering, with many course materials including videos and slides publicly available. His teaching approach emphasizes hands-on implementation of language concepts, as evidenced by his MSD Software Engineering course materials that guide students through building an interpreter for a programming language called MSDscript.

Christoph Kirschمشاهده پروفایل

استاد

• Concurrent Programming
• Memory Management
• Virtualization
• +۵ مورد دیگر

Christoph Kirsch is Professor and Chair of the Department of Computer Science at the University of Salzburg, Austria since January 2022, and Chair of the Computational Systems Group since April 2004. He also serves as Chair of the Programming Research Laboratory at Czech Technical University in Prague since October 2022. Dr. Kirsch earned his Dr.-Ing. from Saarland University in 1999 while at the Max Planck Institute for Computer Science. He worked as Postdoctoral Researcher at UC Berkeley (1999-2004) and later returned as Visiting Scholar (2008-2013) and Visiting Professor (2014). His research focuses on: Principled design of programming languages and runtime systems Server, quantum, embedded, real-time, and mobile systems Symbolic reasoning, memory management, and concurrency Dr. Kirsch co-invented embedded programming languages (Giotto, HTL, Embedded Machine) and has designed high-performance concurrent data structures. His recent work centers on symbolic execution frameworks like Selfie, with publications spanning efficient model checking, program analysis, and memory management systems. Professional recognitions include ACM Distinguished Speaker (2017-present). He co-founded EMSOFT (2001), served as ACM SIGBED chair (2011-2013), and was associate editor for IEEE TCAD and ACM TODAES. He has supervised 5 postdocs, 10 PhD students, and 18 Masters students since 2004, teaching undergraduate and graduate courses in Compiler Construction, Systems Engineering, and Introduction to Computer Science. Dr. Kirsch leads the Computational Systems Group at University of Salzburg, advancing programming language design, runtime systems, and formal verification methods.

Frank Muellerمشاهده پروفایل

استاد

• Parallel Computing
• Quantum Computing
• Real-Time Systems
• +۵ مورد دیگر

Frank Mueller is a Professor in the Department of Computer Science at North Carolina State University's College of Engineering. He maintains an active research and teaching profile with upcoming courses scheduled through 2025, including Parallel Systems (CSC 548), Embedded/Real-Time Systems for Autonomous Driving with Machine Learning, and Quantum Computing. His research interests span multiple cutting-edge computing domains. Mueller is a member of The NSF Quantum Leap Challenge Institute for Robust Quantum Simulation His work bridges theoretical computer science with practical applications in high-performance computing environments. Professor Mueller has been actively involved in numerous conferences including PLDI, PPoPP, LCTES, and IEEE Quantum Week events through 2026, serving on program committees and organizing workshops related to quantum computing and high-performance systems. His teaching portfolio demonstrates significant expertise across multiple domains of computer systems, with courses ranging from foundational operating systems to advanced quantum computing. He has developed specialized teaching resources including the Arc Cluster for parallel systems education and maintains active connections with industry through equipment donations from companies like ARM, Google, and Microsoft.

Fabrice Rastelloمشاهده پروفایل

پژوهشگر

• Automatic Parallelization
• Compiler Back-End Optimization
• Static Single Assignment (SSA)
• +۴ مورد دیگر

Fabrice Rastello is a leading researcher at Inria, France, where he serves as the leader of the CORSE (Compiler Optimization and Runtime SystEms) research team. His expertise spans automatic parallelization and compiler back-end optimization, with significant contributions to Static Single Assignment (SSA) form theory and register allocation techniques. Affiliated with University Grenoble Alpes - Inria - CNRS - Grenoble INP - LIG, he maintains an active research profile with continuous publications in top-tier conferences including PLDI, CGO, and PPoPP. His research interests focus on combining theoretical foundations with practical applications in compiler design. Key areas include automatic parallelization techniques (building on his PhD work on tiling as a loop transformation), compiler back-end optimization, and the emerging field of hybrid compilation that bridges static compilation with runtime techniques. He has made significant contributions to register allocation for JIT compilation in the context of SSA properties, advising three PhD students on related topics. Analysis of his recent publications reveals a strong trend toward data movement optimization, with numerous papers on I/O complexity bounds, cache modeling, and microarchitectural performance analysis. His work spans both theoretical computer science and practical applications, including contributions to healthcare technology during the pandemic with the eSpiro ventilator project. He has also explored intersections between compiler techniques and machine learning, particularly in using ML for performance modeling. Fabrice Rastello serves on program committees for major conferences in the field, including PLDI, CGO, and CC, demonstrating his standing in the research community. His 2022 book 'SSA-based Compiler Design' as editor further establishes his authority in compiler theory and practice. His recent work shows continued innovation in compiler techniques, with publications in 2024 demonstrating ongoing research activity across multiple domains including cache modeling, program analysis, and machine learning applications.

Andreas Gerstlauerمشاهده پروفایل

استاد

• Embedded Systems
• Cyber-Physical Systems
• Internet of Things
• +۷ مورد دیگر

Andreas Gerstlauer is a Professor and holder of the Cullen Trust for Higher Education Endowed Professorship in Engineering #6 at The University of Texas at Austin. He serves as the Associate Chair for Academic Affairs in the Chandra Family Department of Electrical and Computer Engineering. His academic appointments include membership in the Architecture, Computer Systems, and Embedded Systems (ACSES) research area and the Integrated Circuits & Systems (ICS) research area. Dr. Gerstlauer received his Dipl.-Ing. (M.S.) degree in Electrical Engineering from the University of Stuttgart, Germany in 1997 and M.S. and Ph.D. degrees in Information and Computer Science from the University of California, Irvine in 1998 and 2004, respectively. Prior to joining UT Austin in 2008, he was an Assistant Researcher in the Center for Embedded Computer Systems (CECS) at UC Irvine. His research focuses on embedded systems, cyber-physical systems, and the Internet of Things, with particular emphasis on electronic system-level design methods, system modeling, design languages, and embedded hardware/software synthesis. His work spans from novel hardware/software fabrics and System-on-Chip architectures to system-level design automation methods and tools, with special emphasis on underlying system modeling foundations. His research group, the System-Level Architecture and Modeling (SLAM) Lab, investigates resource-constrained and application-specific embedded, high-performance, and edge computing systems. Dr. Gerstlauer's publication record shows a consistent trajectory in advancing system-level design methodologies, with recent work focusing on IoT applications, deep learning inference at the edge, power modeling using machine learning techniques, and advanced simulation frameworks for heterogeneous architectures. His research bridges the gap between theoretical design methodologies and practical implementation, with commercial applications used by organizations including JAXA and NEC Toshiba Space Systems. Humboldt Research Fellowship (2016-2017) Best Research Paper Award at DAC (2016) Best Paper Award at SAMOS (2015) Outstanding Paper Award at ECRTS (2023) IEEE HSTTC Top Pick in Hardware Security (2021) Best Paper Award at MLCAD (2021) Dr. Gerstlauer has successfully mentored numerous Ph.D. and Master's students who have gone on to prominent positions at companies including Google, NVIDIA, Apple, AMD, Facebook, Intel, and Samsung. His research has been supported by major funding agencies including NSF, DOE, SRC, Sandia National Labs, and industry partners such as AMD, ARM, Intel, Qualcomm, and Samsung. He has served in leadership roles for major conferences including General Co-Chair for ESWEEK 2020-2021 and Program Committee Chair for CODES+ISSS 2015-2016. The SLAM Lab, under his direction, currently pursues active research in neuromorphic computing system co-design, accelerator-rich heterogeneous system architectures, and predictive modeling for next-generation heterogeneous computer system design. The lab maintains strong industry partnerships and has produced multiple open-source software tools including QLA-RTS, DeepThings, LIPPo, and NoSSim that have been adopted by both academic and industrial researchers.

Karine Even-Mendozaمشاهده پروفایل

مدرس

• Software Testing
• Software Verification
• Programming Languages
• +۷ مورد دیگر

Karine Even-Mendoza is a Lecturer in Systems & Programming Languages at King's College London, working within the Department of Informatics in the Faculty of Natural, Mathematical & Engineering Sciences. Previously, she was a Research Associate at Imperial College London's Department of Computing, where she worked in the Software Reliability Group and Multicore Programming Group. She completed her PhD at King's College London, where she also spent four years working with the Software Systems (SSY) group. Dr. Even-Mendoza's research focuses on the intersection of software testing, verification, and programming languages, with recent work increasingly incorporating machine learning and quantum computing techniques. Her work addresses critical challenges in compiler testing, system simulation validation, and the application of large language models to software engineering problems. She has developed innovative approaches like ReFuzzer for enhancing the validity of LLM-generated test programs and SearchGEM5 for improving the reliability of system simulators through search-based testing. Her publication record demonstrates a strong trajectory in top-tier software engineering venues, with a notable shift toward incorporating large language models and quantum computing in recent years. She has become particularly active in applying AI techniques to traditional software engineering challenges, bridging the gap between classical software verification methods and modern AI approaches. Her work spans both theoretical foundations and practical applications, with implementations like CsmithEdge and GrayC contributing tangible tools to the software testing community. Dr. Even-Mendoza has been actively involved in the software engineering research community, serving on program committees for major conferences including ASE, ISSTA, ECOOP, and SPLASH. She has also contributed to artifact evaluation processes, demonstrating her commitment to research reproducibility and scientific rigor in software engineering.

Jean Pichon-Pharabodمشاهده پروفایل

استادیار

• Programming Language Theory
• Systems Programming
• Relaxed Memory Concurrency
• +۵ مورد دیگر

Jean Pichon-Pharabod is a Tenure Track Assistant Professor at Department of Computer Science, Aarhus University , focusing on bridging programming language theory with industrial systems programming in areas like relaxed memory concurrency and formal verification. His work includes developing robust verification tools for WebAssembly and virtual machine security . Research Interests : Relaxed memory models, separation logic, capability safety, systems programming, and memory-safe execution environments. Scientific Awards : Amazon ARC Award (2024), Google ASPIRE Awards (2021-2023), AUFF Starting Grant. Key Contributions : Verified WebAssembly compilation, mechanised memory models, concurrency in ARM/RISC-V, and separation logic frameworks. Students : Zongyuan Liu, Maxime Legoupil, June Rousseau.

Adam Chlipalaمشاهده پروفایل

استاد

• Programming Languages
• Formal Methods
• Computer Systems
• +۶ مورد دیگر

Adam Chlipala is the Arthur J. Conner Professor of Computer Science at the Massachusetts Institute of Technology (MIT). His work bridges programming languages, formal methods, computer systems, and security, with a focus on building practical systems verified end-to-end using the Coq proof assistant. He has advised numerous PhD and Master’s students and leads research into verified compilers, hardware-software stacks, and dependent types for real-world applications through his startup Nectry. Undergraduate: Carnegie Mellon University, 2003 PhD: University of California, Berkeley, 2007 Postdoc: Harvard University, through 2011 His research revolves around verified compilers , hardware-software co-verification , and dependent types for enterprise software . Recent work explores high-performance parallel computing stacks and end-to-end machine-checked proofs for cryptographic systems. His publications span conferences like PLDI, POPL, and ICFP, emphasizing formal verification, optimization, and security. Current research trends highlight verified cryptographic code , concurrent hardware verification , and DSLs with formal guarantees . His students work on topics from state machines to network switches and parallel computing frameworks. Coq Proof Assistant Verified Compilation Cryptographic Security Dependent Types Hardware Verification High-Performance Computing Chlipala has served on program committees for CoqPL, Dafny, CPP, and PLDI. He co-created the MIT course Formal Reasoning About Programs and authored two books: Certified Programming with Dependent Types and Formal Reasoning About Programs .

Yanlin Wangمشاهده پروفایل

استادیار

• Software Engineering
• Large Language Models
• Programming Languages
• +۴ مورد دیگر

Yanlin Wang is an Assistant Professor at the School of Software Engineering, Sun Yat-sen University, where he joined in July 2022 after working as a senior researcher at Microsoft Research Asia in the Data, Knowledge, and Intelligence (DKI) group. His academic journey includes a B.S. from Zhejiang University and a Ph.D. from the University of Hong Kong under the supervision of Prof. Bruno C. d. S. Oliveira. Dr. Wang's research spans multiple domains within computer science, with particular emphasis on applying large language models to software engineering problems. His work bridges traditional software engineering with cutting-edge AI techniques, focusing on code generation, code search, and intelligent software development tools. He has made significant contributions to understanding how LLMs can be effectively applied to repository-level code completion, security analysis of smart contracts, and improving the efficiency of code generation processes. An analysis of his recent publications reveals a strong trend toward applying AI to practical software engineering challenges, particularly in the areas of code generation quality, security analysis, and efficient model deployment. His work often combines theoretical insights with practical implementations, as evidenced by multiple tools and frameworks developed by his research group, including MemoryBank for enhancing LLMs with long-term memory and AGIEval for evaluating foundation models. ACM SIGSOFT Distinguished Paper Award (ISSTA 2024) - for work on LLM code generation acceleration ACM SIGSOFT Distinguished Paper Award (ISSTA 2024) - for work on identifying code security issues ACM SIGSOFT Distinguished Paper Award (Internetware 2024) Distinguished Reviewer Award (Internetware 2024) Best Paper Award (Modularity 2016) Dr. Wang actively contributes to the academic community through service on program committees for major conferences including ISSTA, FSE, ICSE, and COLING. He serves as a reviewer for prestigious journals and conferences such as TKDE, TNNLS, and AAAI. His teaching portfolio at Sun Yat-sen University includes Principles of Compilers, AI Revolution: Decoding Large Models, and Software Source Codes Analysis, reflecting his expertise across both foundational and cutting-edge topics in computer science.

Chengnian Sunمشاهده پروفایل

دانشیار

• Software Engineering
• Programming Languages
• Program Reduction
• +۵ مورد دیگر

Chengnian Sun is an Associate Professor in Software Engineering and Programming Languages at the University of Waterloo, Canada. His research spans program reduction, software testing, and compiler-related technologies, with a focus on developing practical tools for debugging and testing. Dr. Sun's research interests center on Software Engineering and Programming Languages , particularly in program reduction techniques, compiler testing, and software security. His work bridges theoretical foundations with practical applications, developing frameworks like Perses and Latra that have become influential in the software engineering community. His research demonstrates a consistent evolution from basic program reduction techniques to incorporating modern approaches like LLMs for compiler testing. His recent publications show a strong trend toward language-agnostic transformation frameworks and practical debugging tools , with increasing emphasis on security applications and integration of AI techniques. The research spans both theoretical foundations and practical implementations, with several tools developed becoming widely used in the software engineering community. Dr. Sun has served on program committees for major software engineering conferences including ASE, ICSE, ESEC/FSE, and ISSTA, demonstrating his standing in the research community. His extensive publication record shows consistent high-impact contributions across multiple venues, with particular emphasis on program reduction and compiler testing techniques. His work has led to the development of several influential tools including Perses (syntax-guided program reduction), Latra (template-based transformation framework), and AddressWatcher (memory leak localization). These tools have been widely adopted in both academic and industrial settings for debugging and testing purposes.

Joschka Roffeمشاهده پروفایل

پژوهشگر ارشد

• Quantum Computing
• Quantum Error Correction
• Fault-Tolerant Quantum Computing
• +۳ مورد دیگر

Dr. Joschka Roffe is an EPSRC Quantum Career Acceleration Fellow at the University of Edinburgh and serves as the Quantum Error Correction Lead and Board Member at the UK's Quantum Software Lab. His research focuses on developing quantum error correction protocols to enable fault-tolerant quantum computing, addressing the fundamental challenge of qubit fragility in quantum systems. Dr. Roffe's educational background includes: MPhys Physics from Manchester University (2011-2015) A year abroad at the University of California, Santa Barbara (2013-2014) PhD in Quantum Computing from Durham University (2015-2018) Research Associate at Sheffield University (2018-2021) Postdoctoral Researcher at Freie Universität Berlin (2021-2023) Dr. Roffe's research addresses the critical challenge that quantum bits (qubits) are realized through fragile quantum systems such as single ions, photons or superconducting circuits, making them highly susceptible to errors. His work develops quantum error correction protocols designed to mitigate these errors, which is essential for realizing practical quantum computers that can outperform classical systems. His expertise spans theoretical frameworks for quantum error correction to practical implementations that could enable scalable quantum computing architectures. His publication record shows a clear progression from foundational work on the Coherent Parity Check framework during his PhD to increasingly sophisticated approaches for quantum LDPC codes, surface codes, and fault-tolerant architectures. Notably, his 2019 review paper 'Quantum error correction: an introductory guide' published in Contemporary Physics has become a standard reference in the field. His notable scientific achievement is the prestigious EPSRC Quantum Career Acceleration Fellowship, which supports his research at the University of Edinburgh. Dr. Roffe leads the quantum error correction efforts at the Quantum Software Lab, where he collaborates with researchers across the UK to advance quantum software development. His work bridges theoretical quantum information science with practical implementations that could enable the next generation of quantum computers capable of solving problems beyond the reach of classical computing.

Yingfei Xiongمشاهده پروفایل

دانشیار

• Software Engineering
• Programming Languages
• Program Synthesis
• +۴ مورد دیگر

Yingfei Xiong is an Associate Professor at Peking University specializing in Software Engineering and Programming Languages. His research focuses on program synthesis, automated program repair, and software analysis techniques with extensive contributions to top-tier conferences including ASE, ICSE, PLDI, and SPLASH/OOPSLA. Dr. Xiong's primary research interests include: Program Synthesis and Inductive Programming Automated Program Repair and Bug Fixing Static and Dynamic Program Analysis Machine Learning Applications in Software Engineering Compiler and Language Implementation Techniques Software Testing and Verification His publication trends show a strong shift toward neural approaches in program repair, with significant integration of large language models in synthesis tasks since 2023. His work bridges theoretical foundations with practical applications, evidenced by industrial collaborations such as the Alibaba case study on static taint analysis. Recent contributions include GrammarT5 for code generation, Tare for type-aware neural repair, and Equality Saturation techniques guided by LLMs. At Peking University, Dr. Xiong is affiliated with the School of Electronics Engineering and Computer Science (SEI) as indicated by his institutional website domain. He actively contributes to the academic community through program committee service for major software engineering conferences and mentoring student researchers.

• Programming Languages
• Logic Programming
• Constraint Programming
• +۴ مورد دیگر

Ulrich Neumerkel is an Assistant Professor in the Department of Compilers and Languages at Technische Universität Wien (TU Wien). He holds academic titles of Dipl.-Ing. (FH) and Dr.techn. His primary research focuses on programming languages, logic programming, and constraint programming, with significant contributions to Prolog optimization, garbage collection, and formal methods. He is also actively involved in educational initiatives, developing declarative programming tools and curricula. Neumerkel teaches courses such as Logic Programming and Constraints, Advanced Logic Programming, and Programming 2. He leads research in formal semantics of Prolog, constraint solver design, and memory management techniques. His work includes contributions to ISO/IEC Prolog standards and the development of tools like the Vienna Abstract Machine (VAM) and the GUPU environment for Prolog education. His research interests span compiler design, termination analysis, and program transformation. He has supervised students, including M. Seidl, on diploma theses related to virtual machine comparison and other topics. Neumerkel's affiliations include the Compilers and Languages group within TU Wien's Institute for Information Systems Engineering.