Find Academic Supervisors

• Pragmatics
• Biolinguistics
• Literary Theory
• +1 more

Alexis Kalokairinos serves as Professor of General Linguistics at the Department of Philology, School of Philosophy, University of Crete, where he has chaired the Department since 2016. His leadership roles include Dean of the School of Philosophy (2006-2010) and Director of the Department's Postgraduate Program (2004-2007), alongside visiting professorships at Freie Universität Berlin (2010-2011, 2015-2016) and École des Hautes Études en Sciences Sociales, Paris (2013). His academic foundation stems from studies at the University of Athens and École des Hautes Études en Sciences Sociales, Paris. Kalokairinos' research integrates linguistic theory with historical and literary analysis through four core domains: Pragmatics examining language use in context Biolinguistics exploring biological foundations of language Literary Theory analyzing narrative structures History of Ideas about Language tracing conceptual evolution His interdisciplinary approach bridges humanities and cognitive sciences. He received the Nikos Kazantzakis Award from Heraklion Municipality in humanities (2011). Administrative contributions include mentoring graduate students as Postgraduate Program Director and shaping departmental strategy as current Chair. External engagements feature presidency of the Society of Cretan Historical Studies (since 2009), editorship of Cretan Chronicles journal (since 2011), Museums Council membership under Greece's Ministry of Culture (since 2018), and directorship at A. & M. Kalokairinos Foundations (since 1995).

• Distributed Computing
• Concurrent Computing
• Transactional Memory
• +4 more

Rachid Guerraoui is a Moroccan-Swiss computer scientist and Full Professor in the School of Computer and Communication Sciences at EPFL. He is renowned for his significant contributions to distributed and concurrent computing, holding the prestigious Chair in Distributed Computing at the Collège de France (2018-19). As an ACM Fellow (2012) and recipient of the Dahl-Nygaard Senior Prize (2024), his work has shaped both theoretical foundations and practical implementations in distributed systems. Guerraoui earned simultaneous Master's degrees in Computer Engineering from École supérieure d'informatique électronique automatique (ESIEA) and in Computer Science from Pierre and Marie Curie University in 1989. He completed his PhD at Université d'Orsay in 1992 under the supervision of Christian Fluhr, with a dissertation titled "Programmation Répartie par Objets: Études et Propositions." Following postdoctoral research at EPFL, he joined the computer science faculty in 1999 after working at HP Labs and MIT. Guerraoui's research spans distributed computing, concurrent systems, transactional memory, and asynchronous algorithms. His work on establishing theoretical foundations of Transactional Memory, including the concept of opacity, has been highly influential. He has also made significant contributions to scalable information dissemination methods, asynchronous distributed computations, and the mathematical abstraction of indulgence. His research bridges theoretical rigor with practical implementations, as evidenced by systems like SwissTM and STMBench7. His publication record shows a clear evolution from theoretical foundations to practical implementations and broader applications. Early work focused on fundamental problems like consensus and renaming, while more recent publications address machine learning applications and public understanding of AI. The consistent thread throughout his career is a focus on making distributed systems more reliable, efficient, and accessible. Guerraoui has received numerous prestigious awards including: ACM Fellow (2012) ERC Advanced Grant Award (2013) Google Focused Award (2014) Middleware Best Paper Award (2014) Middleware 10-Years Best Paper Award Chair in Distributed Computing, Collège de France (2018-19) Dahl-Nygaard Senior Prize (2024) As an academic advisor, Guerraoui has mentored students including El Mahdi El Mahmdi, with whom he co-created the Wandida project - a collection of educational videos on computer science. His research has been supported by significant grants from the European Research Council and Google. Beyond research, Guerraoui actively participates in public discourse, particularly regarding computer science education and technology policy. Guerraoui leads the Distributed Computing Laboratory (DCL) at EPFL, which focuses on advancing the state of the art in distributed systems. The lab's work spans theoretical foundations, practical implementations, and educational outreach, reflecting Guerraoui's holistic approach to computer science research and education.

• Polymer Chemistry
• Polymer Technology
• Biomaterials
• +3 more

Zoe Terzopoulou serves as an Assistant Professor at the Department of Chemistry, University of Ioannina, where she leads research within the Laboratory of Industrial Chemistry. Her academic role focuses on advancing polymer science and sustainable material development. Her educational qualifications include a Master's Degree (MSc) and Doctorate (PhD) in Polymer Chemistry and Technology, with doctoral research supported by the Aristotle University of Thessaloniki. Dr. Terzopoulou's research program centers on synthesizing and characterizing bio-derived polyesters, copolymers, blends, polymer composites, nanocomposites, and hybrid polymer-inorganic biomaterials. Her work specifically targets polymer scaffolds for tissue engineering applications, bridging sustainable chemistry with biomedical innovation. This research portfolio demonstrates strong emphasis on eco-friendly polymer solutions and functional biomaterials development. Her scholarly impact is evidenced by significant recognition: Two Best Poster Awards and one Best Oral Presentation Award at scientific conferences Excellence Scholarship for Doctoral Candidates (Aristotle University of Thessaloniki, 2016) IKY Postdoctoral Scholarship for bio-derived polyester research (2020) Inclusion in Stanford University/Elsevier's top 2% most cited scientists globally (since 2022) She has managed extensive research engagement through over 30 national and international conference participations and leadership in numerous European and national research projects since 2014. Her editorial service includes membership on the boards of Polymers and Materials Letters: X journals. Current work continues through the Laboratory of Industrial Chemistry, focusing on next-generation sustainable polymers and tissue engineering scaffolds with over 100 publications and 4,000+ citations to date.

Mattia FazziniView profile

Assistant Professor

• Software Engineering
• Software Testing
• Software Maintenance
• +5 more

Mattia Fazzini is an Assistant Professor in the Department of Computer Science & Engineering at the University of Minnesota's College of Science and Engineering. His primary academic appointment focuses on software engineering research and teaching, with active involvement in major conferences including ASE, ISSTA, ICSE, and MOBILESoft where he has served in leadership roles such as General Co-chair (MOBILESoft 2023) and Program Committee Co-chair. His research centers on software testing, maintenance, and security , with particular emphasis on mobile applications. Key research themes include: Developing techniques for automated Android testing and maintenance Addressing API compatibility issues across Android versions Creating tools for test oracle generation and bug reproduction Investigating security vulnerabilities in mobile ecosystems Optimizing test suites through test double analysis His recent publications (2021-2025) reveal strong focus on Android-specific challenges, with recurring themes in compatibility testing, automated test generation, and security analysis. Over 60% of his work involves tool development for practical testing scenarios, particularly targeting mobile platforms. Notable recognitions include: IEEE TCSE Distinguished Paper Award (2024) for work on test suite optimization ACM Distinguished Paper Award (2022) for COVID-19 app analysis As an educator, he advises multiple PhD and Master's students while teaching undergraduate and graduate courses including CSCI 3081W (Program Design) and CSCI 5802 (Software Engineering II). His service contributions span conference organization (MOBILESoft, ISSTA, ICSE) and extensive program committee work across top software engineering venues. He leads research projects focused on practical testing solutions with real-world applicability in mobile software development.

Chao PengView profile

Part-Time Lecturer

• Software Testing
• Program Analysis
• Programming Languages
• +5 more

Chao Peng is a Principal Research Scientist at ByteDance where he leads the Trae Research team (ByteDance Software Engineering Lab), conducting cutting-edge research on AI agents for software engineering. He also serves as a Part-time Postgraduate Student Mentor at Fudan University's School of Computer Science, bridging industry research with academic mentorship. PhD in Informatics (2021), University of Edinburgh, UK MSc in High Performance Computing and Data Science (2017), University of Edinburgh, UK BEng in Computer Science and Technology (2016), Xuzhou University of Technology, China Dr. Peng's research focuses on the intersection of software testing, program analysis, and large language models. His work explores how AI agents can revolutionize software engineering practices, with particular emphasis on automated bug detection, code generation, and testing frameworks. He has pioneered approaches for evaluating LLM performance in software engineering contexts and developing agent-based systems that enhance developer productivity while maintaining code quality and security. His recent publications demonstrate a clear trend toward integrating large language models with traditional software engineering practices. The research spans code generation evaluation, security vulnerability detection, automated bug reproduction, and issue localization. These works collectively advance the field of AI-assisted software development by addressing practical challenges in reliability, security, and efficiency of AI-generated code. Distinguished Reviewer for FSE'25 School of Informatics Scholarship (fully-funded PhD scholarship) Outstanding Graduate Scholarship at Xuzhou University of Technology Multiple China National Scholarships Honours Spot Bonus at ByteDance Certificate of Achievement for HPCAC Student Cluster Competition Dr. Peng actively mentors students through his role at Fudan University and previously at the University of Edinburgh, where he served as sub-supervisor for MSc projects and teaching assistant for software testing courses. His research has attracted significant industry attention, leading to multiple collaborations between ByteDance and academic institutions. He frequently serves on program committees for major software engineering conferences including ASE, FSE, and ICSE, demonstrating his leadership in the field. As leader of the Trae Research team at ByteDance Software Engineering Lab, Dr. Peng oversees research on AI agents for software engineering, including the application and evaluation of AI agents and training LLMs for agent-based systems. The lab's work focuses on practical systems that predict, detect, diagnose, and fix bugs across various software systems, with particular emphasis on real-world applications and measurable impact on developer productivity.

Xiaoyin WangView profile

Associate Professor

• Software Testing and Analysis
• Software Privacy
• Program Analysis
• +3 more

Xiaoyin Wang is an Associate Professor in the Department of Computer Science at the University of Texas at San Antonio, specializing in software testing, privacy, and program analysis. Her research focuses on enhancing software quality through innovative approaches to build systems, virtual reality testing, and privacy policy enforcement. She earned her PhD from Peking University in 2012 and completed postdoctoral work at UC Berkeley. Her research interests span Software Testing and Analysis , Software Privacy , Build Systems , and Virtual Reality Testing . She develops techniques for detecting privacy leaks in mobile apps, optimizing build scripts, and testing immersive applications. Her work bridges program analysis with practical software engineering challenges, particularly in security-critical contexts. Recent publications reveal strong trends in Virtual Reality testing frameworks (e.g., VRGuide, VRTest), automated build diagnostics (PExReport, HireBuild), and privacy policy verification (GUILeak, DAISY). Her research increasingly integrates machine learning for bug prediction and test oracle generation, with significant contributions to augmented reality testing and cross-project compatibility analysis. President's Research Achievement Award (UTSA, 2019) NSF CAREER Award (2019) for build script analysis Distinguished PhD Dissertation Awards from CCF (2013) and Peking University (2012) MSRA Fellowship (2009) Wang actively advises PhD students including Rodney Rodriguez (defended 2022, now at Accenture) and Xueling Zhang (defended 2021, now Assistant Professor at RIT). She leads NSF-funded projects including CAREER: Analysis and Repair of Build Scripts for DevOps and EAGER: Tracing Privacy-Policy Statements into Code . Her service includes chairing ICSE 2019 proceedings and serving on ASE/ICSE/ISSTA program committees. Current work focuses on security analysis for AR applications and automated privacy compliance verification.

Ying WangView profile

Associate Professor

• Dependency management
• Software ecosystem governance
• Software refactoring
• +5 more

Dr. Ying Wang is an Associate Professor and Assistant Dean at the Software College of Northeastern University in China, where she also serves as a doctoral supervisor. She received her PhD in Software Engineering from Northeastern University in January 2019 and joined the faculty in February 2019. Her academic career includes a postdoctoral fellowship at the Hong Kong University of Science and Technology (2022-2023) and a visiting scholar position at Microsoft Research Asia (2021) through the StarTrack Program. Her research focuses on dependency management, software ecosystem governance, software refactoring, and software supply chain security. She has made significant contributions to understanding cross-language dependencies, vulnerability propagation across ecosystems, and developing tools for dependency conflict detection and resolution. Her work spans multiple programming language ecosystems including Java, C#, Python, Go, JavaScript, Android, and Rust. Dr. Wang's publication record shows a consistent trajectory of high-impact research in top software engineering conferences (CCF-A level) including ASE, ICSE, ESEC/FSE, and ISSTA. Her recent work increasingly integrates large language models with traditional software engineering techniques, particularly in dependency analysis and software refactoring. The publications demonstrate a strong emphasis on practical tool development with industry applications. Microsoft Research Asia Star Program Scholar (2020) CCF Outstanding Doctoral Dissertation Award nomination (2020) Liaoning Province Outstanding Doctoral Dissertation Award (2021) ACM SIGSOFT Distinguished Paper Award (ICSE 2021 and ESEC/FSE 2023) Multiple CCF ChinaSOFT Software Prototype Competition awards (2020, 2023) OpenHarmony Community Security Governance Contributions (2024, 2025) Dr. Wang actively mentors a large group of graduate students working on various aspects of software engineering, with many graduates securing positions at major technology companies including Huawei, Microsoft, Alibaba, and Tencent. She serves on the editorial board of IEEE Transactions on Software Engineering and has held numerous program committee positions at top software engineering conferences. Her research has strong industry connections, with several tools developed by her team being integrated into commercial platforms at Huawei and Microsoft.

Jifeng XuanView profile

Professor

• Software Analysis and Testing
• Software Testing
• Software Debugging
• +2 more

Jifeng Xuan is a Professor and Deputy Dean at the School of Computer Science, Wuhan University, China. He leads the CSTAR (Centre of Software Testing, Analysis and Reliability) research group and has made significant contributions to software engineering, particularly in software testing, debugging, and analysis. Dr. Xuan completed his bachelor's degree and PhD at OSCAR Lab, School of Software, Dalian University of Technology, China, under the supervision of Prof. He Jiang. He also conducted postdoctoral research at SPIRALS Team in INRIA Lille - Nord Europe, France, working with Dr. Martin Monperrus and Prof. Lionel Seinturier. His research focuses on Software Analysis and Testing , with specific interests in software testing and debugging, software data analysis, and search-based software engineering. Dr. Xuan's work bridges theoretical foundations with practical applications, addressing real-world challenges in software quality assurance. His research has led to numerous publications in top-tier software engineering venues and has influenced both academic research and industrial practices. Dr. Xuan's recent publications demonstrate a strong focus on innovative approaches to software testing, debugging, and analysis. His work spans multiple subfields including log analysis, fuzz testing, bug triage, and automated program repair. He has made significant contributions to understanding software crashes, improving bug report quality, and developing techniques for more effective software testing and analysis. 2025 ACM SIGSOFT Distinguished Paper Award 2025 IEEE TCSE Distinguished Paper Award 2024 CCF NASAC Youth Software Innovation Award 2018 ACM SIGSOFT Distinguished Paper Award 2015 Young Talent Development Program of CAST and CCF 2015 Luojia Young Scholar Program of Wuhan University 2014 Outstanding Doctoral Dissertation of CCF Dr. Xuan actively mentors PhD and master's students through his CSTAR research group at Wuhan University. He has served on numerous program committees for major software engineering conferences including ICSE, FSE, ASE, and ISSTA. His editorial service includes roles on the editorial boards of Empirical Software Engineering (EMSE), PLOS One, and Frontiers of Computer Science. Dr. Xuan has also organized several workshops and conferences, demonstrating his leadership in the software engineering community. As founder of CSTAR (Centre of Software Testing, Analysis and Reliability), Dr. Xuan leads a research team focused on advancing the state of the art in software quality assurance. The group's work spans theoretical foundations and practical applications, with strong connections to industry challenges. CSTAR has established collaborations with both domestic and international research institutions, contributing to a vibrant research ecosystem in software engineering.

Işıl DilligView profile

Associate Professor

• Program analysis
• Program synthesis
• Program verification
• +4 more

Işıl Dillig is an Associate Professor of Computer Science at the University of Texas at Austin, where she leads the UToPiA research group. Her academic career spans over a decade of significant contributions to programming languages research, particularly in program analysis, verification, and synthesis. Dr. Dillig received all her academic degrees (BS, MS, and PhD) from Stanford University before joining the faculty at UT Austin. Her educational background established the foundation for her innovative research approach that bridges theoretical computer science with practical applications. Her research focuses on developing techniques to make software systems more reliable, secure, and easier to build through advanced program analysis, verification, and synthesis methods. She has pioneered approaches that combine symbolic reasoning with machine learning to tackle complex software engineering challenges across multiple domains including security, databases, and programming language theory. Her work demonstrates exceptional depth in creating practical tools that address real-world software development problems while maintaining strong theoretical foundations. Analysis of Dr. Dillig's publication record reveals a consistent trajectory of innovation in program synthesis, with recent work expanding into neurosymbolic approaches that bridge neural networks with formal methods. Her research shows strong connections between theoretical foundations and practical applications, particularly in security-critical systems, database technologies, and blockchain applications. The evolution of her work demonstrates increasing sophistication in handling complex program structures while maintaining practical usability. Dr. Dillig has received prestigious recognition for her research contributions: Sloan Fellowship NSF CAREER award As a dedicated educator and research leader, Dr. Dillig has served in significant roles including Program Chair for PLDI 2022 and Steering Committee member for PLDI. She has mentored numerous students through her UToPiA research group, guiding research in program synthesis, verification, and analysis. Her work has been supported by substantial research grants that have enabled innovative projects at the intersection of programming languages and security. Dr. Dillig leads the UToPiA (UT Austin Programming, Languages, and Analysis) research group, which focuses on developing novel techniques for program analysis, verification, and synthesis. The group maintains strong collaborations with industry partners and academic institutions worldwide, translating theoretical advances into practical tools that address real software engineering challenges.

Yufei DingView profile

Associate Professor

• Compiler Technology
• Machine Learning
• Quantum Computing
• +3 more

Yufei Ding is an Associate Professor in the Computer Science & Engineering Department at the University of California, San Diego (UCSD), where she leads the PICASSO Lab. Her research spans domain-specific language design, architecture and compiler optimization, and hardware acceleration, with current focus on developing high-performance, energy-efficient, and high-fidelity programming frameworks for quantum computing and machine learning. Dr. Ding received her Ph.D. in Computer Science from North Carolina State University and a B.S. in Physics from the University of Science and Technology of China. Her interdisciplinary background bridges physics and computer science, enabling her to tackle challenges in emerging computing paradigms. Her research interests focus on Compiler Technology, Machine Learning, and Quantum Computing , with specific expertise in domain-specific language design, architecture and compiler optimization, and hardware acceleration. Dr. Ding's work addresses critical challenges in programming frameworks for emerging technologies, particularly in making quantum computing more accessible and efficient through innovative compiler techniques and runtime systems. Dr. Ding's scientific contributions have been recognized with prestigious awards including the NSF CAREER Award (2020) and the IEEE Computer Society TCHPC Early Career Researchers Award for Excellence in High-Performance Computing (2019) . As an active researcher and educator, Dr. Ding serves on program committees for major conferences including PLDI, PPoPP, and SPLASH. She currently has Ph.D. openings in quantum computing and machine learning systems research, as well as a postdoc position in quantum computing for physics Ph.D. candidates with relevant background. Dr. Ding founded and leads the PICASSO Lab at UCSD, which focuses on developing innovative solutions for programming emerging computing technologies. The lab's work bridges theoretical foundations with practical implementations to address real-world challenges in high-performance computing.

Arjun GuhaView profile

Associate Professor

• Programming Languages
• Program Synthesis
• Low-Resource Programming Languages
• +6 more

Arjun Guha is an Associate Professor at Northeastern University's Khoury College of Computer Sciences, where he also serves as the Area Chair for Software. He conducts research in programming languages with a focus on program synthesis for low-resource programming languages and understanding how computer science education is impacted by large language models. His work spans multiple domains including WebAssembly, software-defined networking, and serverless computing. Guha's research interests center around programming language design, implementation, and application. He has made significant contributions to understanding JavaScript through formal semantics (LambdaJS), developing functional reactive programming for web applications (Flapjax), and creating tools for software-defined networks (NetKAT, Frenetic). His recent work focuses on leveraging large language models for code generation in specialized programming languages and understanding their impact on programming education. His publications reveal a strong trend toward applying AI and machine learning techniques to programming language problems, particularly in code generation and understanding. The research spans from foundational programming language theory to practical applications in education and software development tools, with increasing focus on the intersection of programming languages and large language models. Guha has received several prestigious awards including the OOPSLA Most Influential Paper Award in 2019 for his work on Flapjax, an ACM SIGPLAN Research Highlight for his work on NetKAT, and a Best Student Paper Award. His research has been recognized for its foundational contributions to programming language theory and practical impact on software development. OOPSLA Most Influential Paper Award (2019) for Flapjax ACM SIGPLAN Research Highlight for A Fast Compiler for NetKAT Best Student Paper Award for Flapjax paper Guha advises numerous PhD, MS, and undergraduate students, with several alumni now at leading tech companies and academic institutions. His research has been supported by the National Science Foundation, the Department of Energy, the Office of Naval Research, and industry partners including Google, JPMorgan Chase, MathWorks, Meta, Oracle, and Roblox. He leads the Programming Research Laboratory at Northeastern and is actively involved in major research collaborations like the BigCode Project. Guha is a member of the Programming Research Laboratory at Northeastern and leads several major research initiatives including the BigCode Project's evaluation working group. His lab develops practical software systems like MultiPL-E (a polyglot benchmark for Code LLMs) and WasmFX (bringing effect handlers to WebAssembly), with applications in education, software development, and high-performance computing.

Shachar ItzhakyView profile

Associate Professor

• Program Synthesis
• Automated Reasoning
• Functional Programming
• +5 more

Shachar Itzhaky is an Associate Professor in the Department of Computer Science at Technion - Israel Institute of Technology, Haifa. His research spans multiple areas of programming languages, formal methods, and software engineering, with a focus on making program development and verification more accessible and efficient. He has served on program committees for numerous prestigious conferences including PLDI, POPL, SPLASH, and ICFP. Dr. Itzhaky's research interests center around program synthesis, automated reasoning, and formal verification. His work in program synthesis explores techniques for automatically generating programs from high-level specifications, with applications in end-user programming and software development. In automated reasoning, he has made significant contributions to e-graph based reasoning, invariant inference, and property-directed verification. His research in formal methods focuses on practical applications for program verification, particularly for data structures and security properties. An analysis of his recent publications reveals a strong focus on leveraging advanced formal techniques for practical program understanding and generation. His work consistently bridges theoretical foundations with practical applications, particularly in program synthesis, verification, and end-user programming tools. The trend shows increasing integration of machine learning techniques with traditional formal methods, as well as expanding applications to security and privacy domains. ACM SIGPLAN John C. Reynolds Doctoral Dissertation Award Dr. Itzhaky has been actively involved in the programming languages research community, serving on numerous program committees and contributing to the advancement of formal methods and program synthesis. His work has practical implications for software development tools, security analysis, and end-user programming environments. While specific grant information isn't detailed in the provided text, his extensive publication record in top-tier venues suggests successful funding for his research endeavors. His work on projects like Object Spreadsheets and Lifty demonstrates a commitment to creating practical tools that address real-world programming challenges. Dr. Itzhaky's research is conducted within the vibrant programming languages and formal methods group at Technion's Computer Science department. His work intersects with multiple research threads including program synthesis, verification, and security, suggesting collaboration across these areas within the department. His tools like EPR-based Verification, PDR∀, and VeriCon represent significant technical contributions that likely form the basis of ongoing research projects with students and collaborators.

Eran YahavView profile

Associate Professor

• Program Analysis
• Program Synthesis
• Program Verification
• +4 more

Eran Yahav is an Associate Professor in the Computer Science Department at the Technion - Israel Institute of Technology. He previously served as a research staff member at IBM T.J. Watson Research Center from 2004 to 2010. His academic journey began with a B.Sc. from the Technion in 1996, followed by a Ph.D. from Tel Aviv University in 2005. Yahav's research focuses on program analysis, program synthesis, program verification, and machine learning for programming. His work bridges theoretical foundations with practical applications, particularly in developing techniques that help programmers work more effectively with complex frameworks and APIs. He has pioneered approaches that combine static analysis with machine learning to address challenges in code search, completion, and understanding. His recent work heavily intersects with neural network applications to programming tasks, demonstrating how deep learning can enhance traditional program analysis techniques. His publication record shows a clear evolution from traditional program analysis and verification toward integrating machine learning with programming language processing. The most recent articles reveal a strong focus on neural methods for code understanding, including structural language models, adversarial examples for code models, and neural approaches to binary analysis and program synthesis. This represents a significant shift toward leveraging AI techniques to solve longstanding problems in programming languages and software engineering. Yahav has received numerous accolades including the prestigious Alon Fellowship for Outstanding Young Researchers, the Andre Deloro Career Advancement Chair in Engineering, and an ERC Consolidator Grant. He also earned best paper awards at ISSTA 2006 and 2007. As an advisor, Yahav has mentored numerous Ph.D. and Master's students who have gone on to make significant contributions in academia and industry. His research has been supported by substantial grants, including the ERC Consolidator Grant. He also serves as CTO at Tabnine, demonstrating the practical impact of his research. Yahav leads multiple research projects including PRIME (Programming with Millions of Examples), Fender (Preserving Correctness under Weak Memory Models), Saint (Synthesis using Abstract Interpretation), and several others focused on program analysis, verification, and synthesis. His work often involves building practical tools that translate theoretical advances into usable software engineering solutions.

Qirun ZhangView profile

Associate Professor

• Program Analysis
• Programming Languages
• Software Engineering
• +4 more

Qirun Zhang is the Catherine M. and James E. Allchin Early Career Associate Professor in the School of Computer Science at Georgia Institute of Technology. His research focuses on program analysis, compiler optimization, and formal language theory, with numerous publications in top-tier programming language and software engineering conferences including PLDI, POPL, OOPSLA, and FSE. He teaches courses on compilers, program analysis, and software testing. Dr. Zhang's research interests center on improving software reliability and security through advanced program analysis techniques. He approaches problems from perspectives including computational complexity, analytic combinatorics, graph theory, and formal languages. His work often bridges theoretical foundations with practical applications in compiler design and program verification. His recent publications show a strong focus on context-free language reachability, Dyck-language based analyses, and SMT solving techniques. His research demonstrates consistent innovation in making program analysis more precise while maintaining scalability, with applications ranging from debug information validation to software debloating and type inference. PLDI Distinguished Paper Award (2020) SIGSOFT Distinguished Paper Award (2023) OOPSLA Distinguished Artifact Award (2022) Dr. Zhang actively mentors PhD and MS students, with current advisees including Camille Bossut and Benjamin Mikek. His service to the academic community includes Artifact Evaluation Co-Chair roles for PLDI 2025 and 2026, and program committee membership for numerous top conferences including PLDI, POPL, and OOPSLA. He leads research projects including SLOT, Context-Free Language Reachability with Transitive Redundancy Elimination, and Debug Information Validation.

Gilbert BernsteinView profile

Assistant Professor

• Computer Graphics
• Programming Languages
• High-Performance DSLs
• +7 more

Gilbert Bernstein is an Assistant Professor in the Computer Science & Engineering department within the College of Engineering at the University of Washington. His research bridges computer graphics and programming languages, with a focus on high-performance domain-specific languages. Previously, he was a post-doctoral scholar at UC Berkeley and MIT working with Jonathan Ragan-Kelley, and received his PhD from Stanford University under Pat Hanrahan. His research interests span Computer Graphics, Programming Languages, High-Performance DSLs, Physical Simulation, Geometry & Topology, Differentiable Programming, Hardware DSLs, Tools for Artists, Fabrication, and Human-Computer Interaction. Bernstein develops languages and compilers that enable efficient computation for creative applications, physical simulations, and graphics rendering systems. His recent publications reveal strong trends in differentiable programming for graphics applications, domain-specific languages for hardware acceleration, and computational approaches to traditional crafts like quilting and knitting. His work consistently combines formal language theory with practical applications in graphics and fabrication. Bernstein actively mentors students across multiple institutions including current advisees Felix Hahnlein (UW Postdoc), Ryan Zambrotta (UW PhD), Haoran Peng (UW PhD), and previous students including Alex Reinking (UC Berkeley PhD 2022, now at Qualcomm) and MacKenzie Leake (Stanford PhD 2021, now at Adobe Research). His lab works on diverse projects including debugging CAD programs, compilers for finite element methods, semantics for knitting machines, algebraic scheduling of tensor programs, and exocompilers for hardware accelerators. Bernstein also collaborates on DSLs for networking, Counterstrike bots, gradient-based optimization, memory management, hardware design, and garment design tools.