David I. August is a Professor at Princeton University specializing in programming languages and compiler systems. His research bridges theoretical compiler techniques with practical systems implementation, focusing on memory safety, speculative execution, and compiler optimization. His primary research interests include Compiler Design , Rust Programming Language safety mechanisms , and LLVM infrastructure extensions . His work emphasizes practical implementations that enhance both performance and security in modern programming systems. Recent publications demonstrate consistent contributions to memory profiling frameworks (PROMPT), Rust safety enhancements, and speculative dependence analysis. His research shows strong focus on making low-level systems programming safer without sacrificing performance. August serves regularly on program committees for major conferences including PLDI and CGO, indicating his standing in the programming languages research community. He has mentored students in compiler construction and programming language design, with research projects often involving practical implementations integrated into production-quality compiler frameworks.
Sang Kil Cha is an Associate Professor at KAIST's Graduate School of Information Security and School of Computing, where he also serves as Director of the Cyber Security Research Center (CSRC). His research focuses at the intersection of computer security and software engineering, with emphasis on building and evaluating systems that analyze programs. Dr. Cha received his B.S. from Korea University, and both his M.S. and Ph.D. from Carnegie Mellon University (CMU). His educational background forms the foundation for his experimental approach to computer science research. His primary research interests include software security, software engineering, program analysis, binary code analysis, and fuzzing. Dr. Cha's work centers on developing practical security tools and methodologies that bridge theoretical concepts with real-world applications, particularly in program analysis and vulnerability detection. His research has significant implications for improving software reliability and security through advanced analysis techniques. Dr. Cha's publication record shows a strong focus on fuzzing techniques, binary analysis, and program understanding, with recent work expanding into blockchain security and decompilation. His research consistently appears in top-tier security and software engineering conferences including IEEE S&P, USENIX Security, and CCS. ACM Distinguished Paper Award (2024, 2022, 2014) USENIX Distinguished Paper Award (2023) IEEE Best Paper Award (2021) NDSS Best Paper Award (2019) As Director of CSRC and leader of SoftSec Lab at KAIST, Dr. Cha oversees multiple research projects focused on practical security solutions. His lab develops tools like B2R2 (a binary analysis framework) and OFuzz (a fuzzing platform), which have gained recognition in the security community. Dr. Cha actively contributes to the research community through program committee roles at major conferences including PLDI, ICSE, and ISSTA.
Nikolaos Papaspyrou is a Professor at the School of Electrical and Computer Engineering of the National Technical University of Athens (NTUA) and a member of the Software Engineering Laboratory . His research focuses on the theory and implementation of programming languages, including semantics, type systems, compilers, static analysis, and formal verification. Since October 2021, he has been on leave from NTUA, working as a Software Engineer for Google in the memory management team for the V8 JavaScript and WebAssembly engine. He previously served as Director of the Division of Computer Science (2017-2019) and was on sabbatical with Google's compiler group in Munich (2015-2016). His work includes the RELEASE project (EU FP7 STREP) for reliable large-scale server software and uncertainty handling in distributed databases (European Social Fund). Ph.D. and Diploma in Electrical and Computer Engineering from NTUA M.Sc. in Computer Science from Cornell University His research interests span programming languages , software engineering , and formal verification , with recent publications on coinductive proofs in Liquid Haskell, concurrency semantics, and quantum compilation. He has supervised over 50 diploma projects and mentored numerous students now at institutions like MIT, Princeton, and UC Berkeley. Awards include conference organizing and program committee roles, though no formal scientific prizes are listed.
Vikram S. Adve is a Professor in the Department of Computer Science at the University of Illinois at Urbana-Champaign. He co-founded and co-leads the Center for Digital Agriculture and directs the USDA-funded AIFARMS Institute , focusing on AI applications in sustainable agriculture. His research bridges compilers, parallel systems, and AI to address challenges in edge computing and digital farming. Research interests span compiler technologies (LLVM, HPVM), parallel programming models , software reliability , and AI-driven agriculture . Key projects include: CropWizard : Generative AI for agricultural decision-making. HPVM/ApproxHPVM : Compiler IR for edge devices. Hydride/MISAAL : Automated retargetable compiler construction. Recent publications (2018-2025) emphasize compiler optimizations, approximate computing, binary analysis, and AI for systems. Trends show convergence of compiler techniques , heterogeneous computing , and AI applications in agriculture and edge devices. Adve actively recruits students for projects funded by USDA, Intel, Amazon, and Illinois DPI. He leads the HPVM compiler team and digital agriculture initiatives , integrating cross-disciplinary research across CS, engineering, and agronomy.
Stefan K. Muller is the Gladwin Development Chair Assistant Professor in the Computer Science Department at Illinois Institute of Technology. He previously served as a Postdoctoral Researcher at Carnegie Mellon University from 2018-2020 following completion of his PhD there under advisor Umut A. Acar. His academic journey began with an AB from Harvard University in 2012 under Stephen Chong. Dr. Muller's research centers on programming language techniques to improve correctness and efficiency of software, particularly in parallel computing domains. His work spans language and type system design, static resource analysis, and parallel computing methodologies. He leads the Responsive Parallelism research project which extends implicit parallelism models to handle features of consumer software like user interaction and responsiveness requirements. His publication record shows consistent output in top-tier venues including PLDI, POPL, ICFP, and SPAA, with recent work focusing on graph types, responsive parallelism, and resource-aware GPU programming. His research has been supported by NSF grant CCF-2107289. Current advisees include Marelle León (BS), Godha Pallavi Bhogadi (MS), and Alex Friedman (PhD) Former students have gone on to positions at Apple, Amazon, Bloomberg, American Express, and PhD programs at UPenn Teaching responsibilities at Illinois Tech include graduate courses CS534 (Types and Programming Languages), CS536 (Science of Programming), CS440 (Programming Languages and Translators), and CS443 (Compiler Construction). Previously at CMU, he taught Principles of Functional Programming.
Michael L. Scott is the Arthur Gould Yates Professor of Engineering in the Department of Computer Science at the University of Rochester's Hajim School of Engineering and Applied Sciences. He received his Ph.D. from the University of Wisconsin-Madison in 1985 and has been a faculty member at Rochester since 1985, serving as Department Chair multiple times (1996-99, 2007, 2017, 2020-2024). He is a Fellow of the ACM, IEEE, and AAAS, and recipient of numerous awards including the Edsger W. Dijkstra Prize in Distributed Computing. Dr. Scott's research focuses on parallel and distributed systems, with particular expertise in synchronization mechanisms, transactional memory, and persistent memory systems. His work spans theoretical foundations to practical implementations, with numerous influential publications and open-source systems like RSTM and Ralloc. His research has addressed critical challenges in concurrent programming, memory management, and system reliability. His publications show a consistent focus on improving the reliability and performance of concurrent systems, with recent work centered on persistent memory technologies. The trajectory of his research demonstrates a progression from fundamental synchronization algorithms to sophisticated systems addressing modern hardware challenges. His publications span top venues in systems, architecture, and programming languages. His scientific honors include: ACM Fellow (2006) IEEE Fellow (2010) AAAS Fellow Edsger W. Dijkstra Prize in Distributed Computing (2006) University of Rochester's Goergen Award for Teaching (2001) Hajim School Lifetime Achievement Award (2018) IEEE TCCA/HPCA Test of Time Award (2022) Dr. Scott has advised over 25 Ph.D. students who have gone on to successful careers in academia and industry at institutions including Lehigh University, Google, Intel, Facebook, and NVIDIA. His textbook 'Programming Language Pragmatics' is a standard reference in the field, now in its 5th edition. He also co-authored 'Shared-Memory Synchronization,' a comprehensive treatment of the field. He spent the 2014-2015 academic year as a Visiting Scientist at Google. His research group, the Rochester Concurrent Systems Group, has developed numerous influential systems including RSTM (a software transactional memory system), Ralloc (a persistent memory allocator), and Montage (a system for persistent data structures). His work often bridges theoretical correctness with practical performance considerations.
Michael D. Bond is a Professor in the Department of Computer Science & Engineering at Ohio State University's College of Engineering. He leads the Programming Languages and Software Systems (PLaSS) Research Group, which focuses on designing program analyses and software and hardware systems that enhance computing reliability, scalability, and security. His academic service includes general chair for PLDI 2027, program committee membership for multiple top conferences, and committee roles in SIGPLAN Research Highlights (2024-2027). Professor Bond's research spans programming languages, systems, and security, with particular expertise in memory management, concurrency, hardware transactional memory, information flow control, and predictive race detection. His work bridges theoretical foundations with practical implementations, as evidenced by numerous open-source projects accompanying his publications. The PLaSS group has made significant contributions to understanding and improving memory models, developing efficient garbage collection techniques for modern architectures, and creating novel approaches to secure programming in languages like Rust. Analysis of his recent publications reveals a clear trajectory toward addressing security and reliability challenges in modern computing systems, particularly through language-based approaches. His work increasingly focuses on Rust programming language security mechanisms, memory disaggregation for datacenters, and advanced techniques for detecting and preventing concurrency bugs. The research demonstrates strong continuity in exploring memory models and concurrency while adapting to emerging hardware trends and security challenges. Outstanding Teaching Award, Department of Computer Science and Engineering, Ohio State University (2018) Lumley Research Award, College of Engineering, Ohio State University (2016) OOPSLA 2015 Distinguished Paper and Artifact Awards NSF CAREER Award ACM SIGPLAN Outstanding Doctoral Dissertation Award Intel PhD Fellowship Professor Bond actively mentors several PhD students including Chujun Geng, Vincent Beardsley, Chris Xiong, Victor Chen, and Noah Charlton, with external co-advisee Zixian Cai at Australian National University. His research is currently supported by multiple NSF grants including SaTC-2348754 (2024-2027), CyberCorps-2336531 (2024-2029), and CSR-2106117 (2021-2025), reflecting sustained funding for his work in information flow control, security, and systems research. The PLaSS Research Group maintains a strong presence in both academic and industrial communities, with graduated PhD students securing positions at major technology companies like Google, Amazon Web Services, and Huawei, as well as academic positions at institutions like UIUC and IIT Kanpur. The group's work combines theoretical rigor with practical implementation, consistently producing open-source artifacts that enable reproducibility and further research in the systems and programming languages community.
Ruzica Piskac is a Professor of Computer Science at Yale University, where she leads the Rigorous Software Engineering (ROSE) group. She has made significant contributions to the fields of software verification, security, automated reasoning, and code synthesis, focusing on improving software reliability and trustworthiness through formal techniques. Dr. Piskac received her PhD from the Swiss Federal Institute of Technology (EPFL) in 2011, where her dissertation won the Patrick Denantes Prize. Prior to joining Yale, she led an independent research group at the Max Planck Institute for Software Systems in Germany (2012-2013). Her research spans several key areas: symbolic execution for Haskell (G2), privacy-preserving formal methods (PPFM), functional reactive synthesis, verification of configuration files, and analysis of software updates. Her work consistently bridges theoretical formal methods with practical applications in real-world systems. Dr. Piskac's recent publications demonstrate a strong trend toward applying formal verification techniques to emerging challenges including large language models, quantum computing security, legal accountability of automated systems, and cyber-physical systems. Her research increasingly intersects with AI, cryptography, and legal domains while maintaining strong foundations in formal methods. Her scientific achievements have been recognized with numerous prestigious awards: Multiple Amazon Research Awards Yale University's Ackerman Award for Teaching and Mentoring Facebook Communications and Networking Award Microsoft Research Award for the Software Engineering Innovation Foundation (SEIF) Patrick Denantes Prize for her PhD dissertation Dr. Piskac has graduated five PhD students, four of whom have gone on to become assistant professors of computer science. She has served as Program Chair of the 37th International Conference on Computer Aided Verification and is on the Steering Committee of the Formal Methods in Computer-Aided Design conference. She leads the Rigorous Software Engineering (ROSE) group at Yale, which focuses on several key projects including: Symbolic Execution Engine for Haskell (G2) Privacy Preserving Formal Methods (PPFM) Functional Reactive Synthesis Verifications for Configuration Files Analysis of Software Updates and Configuration Files
Steve Blackburn is a research scientist at Google DeepMind and professor of computer science at the Australian National University in the College of Engineering and Computer Science. His primary research focus is on programming language implementation, with expertise spanning memory management, virtual machines, and performance analysis. He has served in significant leadership roles including Associate Dean for Diversity and Inclusion (2016-2019) and as Program Chair for PLDI 2015 and General Chair for PLDI 2023. Blackburn's research interests center on making software run faster and more power-efficiently on modern hardware. His primary areas include microarchitectural support for managed languages, fast and efficient garbage collection, and the design and implementation of virtual machines. He maintains a strong interest in sound methodology and infrastructure for successful research innovation. His work bridges theoretical computer science with practical systems implementation, with particular focus on memory management frameworks and performance benchmarking. His publication record reveals a consistent focus on memory management systems, with recent work exploring garbage collection in modern contexts including CRuby, Julia, mobile devices, and memory-disaggregated datacenters. His research shows an evolution from foundational garbage collection algorithms toward practical implementations addressing real-world constraints in contemporary programming languages and hardware platforms. A notable trend is his increasing focus on quantifying and understanding the true costs of garbage collection in production environments. Fellow of the ACM Blackburn has supervised numerous doctoral students including Zhen He, John Zigman, Robin Garner, Ting Cao, and currently advises Wenyu Zhao, Zixian Cai, and others. He has also served on multiple program committees for major conferences including PLDI, ASPLOS, ISMM, and OOPSLA, demonstrating his significant contributions to the programming languages and systems research community. His service includes editorial roles for ACM Transactions on Programming Language Applications and Systems from 2017-2020. He leads two major research infrastructure projects: the MMTk memory management framework and the DaCapo benchmark suite, both of which have become foundational tools for researchers in programming languages and systems. These projects reflect his commitment to shared research infrastructure and reproducible methodology in systems research.
Alastair F. Donaldson is a Professor in the Department of Computing at Imperial College London's Faculty of Engineering, where he leads the Multicore Programming Group. He also works as a Software Engineer at Google in the Android Graphics Team. Previously, he served as Director of GraphicsFuzz, an Imperial College spinout company acquired by Google in 2018. His research spans programming languages, compilers, verification, and testing, with a particular focus on randomized and fuzz testing techniques for compilers and program analyzers. Donaldson has developed several influential testing frameworks including GraphicsFuzz, RustSmith, and GrayC, which have significantly advanced compiler testing methodologies. Analysis of his recent publications reveals a strong trend toward practical applications of compiler testing techniques across diverse domains including GPU programming, verification-aware languages, and memory models. His work increasingly incorporates continuous integration practices and focuses on addressing real-world challenges in compiler development and verification. Donaldson maintains active involvement in the programming languages research community, serving on program committees for major conferences including PLDI, POPL, ASPLOS, and SPLASH. He has contributed significantly to advancing compiler testing methodologies and has mentored numerous researchers through PLMW (Programming Languages Mentoring Workshop). He leads the Multicore Programming Group at Imperial College London, which focuses on challenges in parallel and concurrent programming. His work bridges theoretical computer science with practical software engineering challenges, particularly in the areas of compiler correctness and verification.
Zhenjiang Hu is a Chair Professor and Dean of the School of Computer Science at Peking University. He serves as Director of the Programming Languages Laboratory and has held significant academic positions including Professor at the National Institute of Informatics and University of Tokyo. BS and MS from Shanghai Jiaotong University (1988, 1991) PhD from University of Tokyo (1996) Lecturer/Assistant Professor at University of Tokyo (1997) Associate Professor at University of Tokyo (2000) Full Professor at National Institute of Informatics (2008) Full Professor at University of Tokyo (2018-2019) Professor Hu's research primarily focuses on programming languages and software engineering, with special emphasis on functional programming, bidirectional transformation, and software adaptation. His work explores transformational programming approaches for automatic program optimization, systematic parallelization of sequential programs, efficient manipulation of structured documents, and bidirectional model transformation for software development. His research has significantly advanced the field of bidirectional programming, developing foundational theories and practical applications that enable more reliable and maintainable software systems. His recent publications demonstrate a strong trajectory in bidirectional programming, program synthesis, and graph processing. The research shows increasing sophistication in handling program transformations, with growing emphasis on practical applications in software engineering contexts. His work increasingly integrates formal methods with practical programming language design, creating systems that maintain theoretical soundness while addressing real-world software development challenges. The research spans multiple venues including top conferences like PLDI, POPL, ICFP, and OOPSLA, reflecting its broad impact across programming language research. Fellow of JFES (Japan Federation of Engineering Society, 2016) ACM Distinguished Scientist (2016) Member of Academia Europaea (2019) IEEE Fellow (2020) Member of Engineering Academy of Japan (2020) Professor Hu actively mentors students and has welcomed excellent candidates to join his group through Peking University's International Elite PhD Program and Boya Postdoctoral Fellowship Program. He serves on numerous program committees for major conferences including PLDI, POPL, ICFP, and OOPSLA, and holds editorial positions for prestigious journals such as Journal of Functional Programming and Science of Computer Programming. His leadership extends to conference organization, having served as PC Chair for CNCC 2024 and General Co-Chair for SoICT 2019. As Director of the Programming Languages Laboratory at Peking University, Professor Hu leads a research team focused on advancing programming language theory and practice. His lab has developed influential frameworks like BiGUL for bidirectional programming and Fregel for graph processing. The laboratory maintains strong international collaborations and contributes to both theoretical foundations and practical implementations in programming languages and software engineering.
Michael Carbin is an Associate Professor at MIT in the Department of Electrical Engineering and Computer Science (EECS), where he leads the Programming Systems Group at the Computer Science and Artificial Intelligence Laboratory (CSAIL). His research centers on developing programming systems that handle uncertainty through probabilistic programming, quantum computing, and neural networks. Carbin's work spans programming languages, systems, and machine learning, with themes including uncertainty management, efficiency optimization, and formal verification. His publications demonstrate a strong focus on probabilistic inference methods, neural network optimization, and quantum programming frameworks. Awards and Honors: Sloan Research Fellowship (2020) Multiple Best Paper Awards (OOPSLA 2013, 2014; ICLR 2019) NSF CAREER Award (2018) Google Faculty Research Award (2018) As the head of the Programming Systems Group, he advises 10+ graduate students and postdocs, focusing on cutting-edge systems research. He has secured grants including Facebook Research Awards and NSF funding.
Nikolaos S. Papaspyrou is a Professor at the School of Electrical and Computer Engineering of the National Technical University of Athens (NTUA), affiliated with the Software Engineering Laboratory and the Division of Computer Science. His research focuses on programming languages, compilers, formal verification, and concurrency. Since October 2021, he has been on leave from NTUA while working as a Software Engineer at Google's V8 JavaScript and WebAssembly engine team. Previously, he served as Director of the Division of Computer Science (2017–2019) and held a sabbatical at Google's Munich compiler group (2015–2016). His academic contributions include pioneering work on Erlang/OTP scalability, concolic testing for functional languages, and static analysis techniques. He has authored numerous publications in top venues like ACM Transactions on Programming Languages and Systems and IEEE conferences. Papaspyrou has supervised over 50 diploma students and multiple PhD candidates, contributing to the education of future researchers and engineers. He actively participates in programming competitions, coaching Greek Olympiad teams, and volunteers in the Hellenic Informatics Society. He teaches advanced courses on programming languages, compilers, and software engineering at NTUA, emphasizing practical applications of theoretical concepts. His educational philosophy integrates problem-solving through programming, as highlighted in his FedCSIS 2013 paper on teaching methodologies.
Kostas Kanakis is a Professor of Sociolinguistics at the University of the Aegean, serving as Director of the Laboratory of Ethnographic Approaches to Language (LEAL) and the Postgraduate Program in 'Gender, Culture and Society'. He holds a PhD from the University of Chicago (1995) and has taught at institutions including Princeton University and the National University of Athens. His research focuses on sociolinguistics, pragmatics, and anthropological linguistics, particularly in Balkan contexts, with an emphasis on language, gender, sexuality, and ethnic identity. Education: Bachelor's in English Language and Literature, National University of Athens (1990) PhD in Linguistics, University of Chicago (1995) Research interests include: Language and society in the Balkans Gender and sexuality in linguistic discourse Linguistic landscape analysis Pragmatics and discourse analysis Ethnographic methods in language studies His recent work explores language use during the pandemic, Balkan sociopolitical dynamics, and the intersection of language with citizenship and nationalism. He has collaborated with the Center for the Greek Language and held fellowships at Humboldt-Universität zu Berlin (2015–2016). He edits the Aegean Working Papers in Ethnographic Linguistics and serves on editorial boards for journals like Journal of Sociolinguistics and Gender and Language . His publications span monographs, edited volumes, and over 30 peer-reviewed articles.
Wei Yang is an Associate Professor in the Department of Computer Science at the University of Texas at Dallas, actively contributing to software engineering research through program committee roles at ICSE, FSE, ASE, and ISSTA conferences since 2015. His research focuses on software testing innovation , particularly in mobile security, GUI testing, and AI-driven test automation. Key contributions include frameworks for malware analysis (MalScan), UI exploration (Guardian, Vet), and neural network testing (DeepPerform, EREBA), addressing critical challenges in test oracle generation, flaky tests, and resource-constrained environments. Recent work demonstrates a strategic shift toward LLM and foundation model applications for testing, with 2023-2026 publications exploring vision-language models for GUI testing, parameter ownership in collaborative AI development, and instruction alignment in large language models. This evolution reflects the field's broader trajectory toward AI-integrated quality assurance.
