Sanjit A. Seshia is the Cadence Founders Chair Professor in the Department of Electrical Engineering and Computer Sciences at the University of California, Berkeley . He is affiliated with the Group in Logic and the Methodology of Science and participates in centers like the Industrial Cyber-Physical Systems Center , Berkeley AI Research , and the Simons Institute for the Theory of Computing . Research interests include formal methods for automated verification and synthesis of dependable systems, with applications to cyber-physical systems , AI-based autonomy , and computer security . His work spans SMT solving, model counting, syntax-guided synthesis, and algorithmic improvisation, with tools like UCLID5 , VerifAI , and Scenic for verifying autonomous systems and educational platforms like CPSGrader . Students and collaborators include notable researchers such as Dorsa Sadigh (Stanford), Daniel Fremont (UC Santa Cruz), and Hazem Torfah (Chalmers). He has co-founded startups like Decyphir and 20ⁿ Labs based on his research.
Professor Helen Finch (University of Leeds) is a leading scholar in German Literature , with a focus on Holocaust Studies , Queer Memory , and German-Jewish Cultural Production . Affiliated with the School of Languages, Cultures and Societies and the Centre for Jewish Studies , she co-leads the LCS Queer Area Studies Network and contributes to equality initiatives through the LGBT+ staff network . Research: Holocaust representation in German works, queer identity in postwar literature, transnational memory studies, curriculum design in German studies Awards: Fellow of the Higher Education Academy (2014) Academic Output : Her 15 most recent publications span Holocaust poetics , queer life writing , translation ethics , and Sebaldian intertextuality , with a particular focus on intersections between trauma , identity , and intergenerational testimony . Supervision : Currently guides PhD research on topics including transnational transphobia , queer art practices , and LGBTQ+ cross-cultural representation . Her students explore areas from German exile photography to postcolonial queer narratives .
Loris D'Antoni is an Associate Professor in the Department of Computer Science and Engineering at the University of California at San Diego (UCSD) . He is also a Visiting Academic at Amazon Web Services (AWS) . His research focuses on helping people write trustworthy software through techniques in program synthesis, formal verification, and machine learning robustness. Bachelor and Master in Computer Science from University of Torino (2008, 2010) PhD in Computer Science from University of Pennsylvania (2015) His research integrates programming languages , automata theory , and formal methods to ensure software reliability. Recent work explores semantics-guided synthesis and specification-aligned LLMs , with applications in network security, machine learning fairness, and automated code repair. Key trends in his publications include program synthesis , formal verification , and trustworthy AI systems . He has contributed to tools like AutomataTutor and SemGuS , a framework for customizable synthesis problems using constrained Horn clauses. Phillip R. Certain-Gary D. Sandefur Distinguished Faculty Award NSF CAREER Award Microsoft Research Faculty Fellowship Google and Facebook Faculty Awards Best Paper Award at ICDCN 2023 Distinguished Paper Award at SBES 2021 D'Antoni actively contributes to academic community service as a committee member in PLDI , OOPSLA , POPL , and CAV . He leads the Programming Systems Group at UCSD and collaborates with SemGuS research team on synthesis frameworks.
Kimia Zamiri Azar serves as an Assistant Professor in the Department of Electrical and Computer Engineering at the University of Central Florida, focusing on hardware security and verification methodologies. Her research bridges theoretical formal methods with practical security implementations in semiconductor design and testing. Her educational background includes: Ph.D. in Electrical and Computer Engineering, George Mason University (2021) Postdoctoral Research, University of Florida Dr. Azar's research spans hardware security with emphasis on system-level verification, VLSI design-for-trust, and advanced IC testing. She pioneers techniques in logic locking, secure heterogeneous integration, and IC supply chain security, developing frameworks for authenticated encryption in Systems-in-Package and runtime security monitoring. Her work integrates formal verification with innovative testing methodologies to address hardware trust challenges across the semiconductor lifecycle. Analysis of her recent publications reveals two dominant trends: (1) Application of large language models (LLMs) to hardware design tasks including high-level synthesis code generation and RTL optimization, and (2) Advancement of secure heterogeneous integration techniques for System-in-Package architectures with focus on counterfeit prevention and split-test security protocols. These directions address critical gaps in hardware trustworthiness amid increasingly complex semiconductor supply chains. Her scientific contributions have earned significant recognition: Best Paper Award at ICCAD 2019 Best Paper Award at ISVLSI 2020 Best Paper Award at ICCAD 2020 Best Paper Award at IEEE DCAS 2020 Best Paper Award at HOST 2022 Best Paper Award at DATE 2023 Dr. Azar secures substantial research funding from premier agencies including NSF, SRC, DARPA, AFRL, DoD (NG), and Microsemi. Her grants support projects spanning hardware security validation frameworks, secure heterogeneous integration, and AI-augmented verification methodologies. She actively mentors students in her research group, guiding publications in top venues like IEEE D&T, IEEE TC, and DAC while fostering industry-academic collaborations. Her work directly impacts semiconductor security standards through patented innovations and open-source verification tools. As an active IEEE and ACM member, she contributes to community advancement through conference organization (HOST, DATE), journal editorial roles, and workshop leadership on hardware security standards. Her research group collaborates with semiconductor industry leaders to translate theoretical security frameworks into practical design-for-trust methodologies for next-generation integrated circuits.
Lingming Zhang is an Associate Professor at the Department of Computer Science, University of Illinois Urbana-Champaign, affiliated with the Grainger College of Engineering. His research focuses on the intersection of Software Engineering, Programming Languages, and Machine Learning, with a particular emphasis on automated program repair, compiler testing, and large language model (LLM) applications in software engineering. He has published over 100 papers, achieving an h-index of 50+, and holds an ACM Distinguished Member status. Research Interests: LLM-based software testing, repair, and synthesis Fuzzing of deep-learning libraries and compilers Open-source code LLMs (e.g., StarCoder2, Magicoder) with over 1M downloads Automated program repair systems (e.g., AlphaRepair, ChatRepair, Agentless) Recent Contributions: Developed TitanFuzz for coverage-guided compiler fuzzing Released Agentless , an LLM-based coding tool adopted by OpenAI and DeepSeek Proposed SWE-RL to enhance LLM reasoning via reinforcement learning Service Roles: Program Co-Chair for ASE 2025 and LLM4Code 2025 Associate Chair for OOPSLA 2024 and Area Chair for ICSE 2025/2026 Recipient of NSF CAREER Award and ACM SIGSOFT Early Career Award Lab/Teams: Develops open-source tools like UniAPR for efficient patch validation Active in releasing industry-adopted LLM-based software engineering tools
Aws Albarghouthi is affiliated with the University of Wisconsin-Madison, USA. He is an active researcher with significant contributions to program synthesis, formal verification, and machine learning. Key roles: Author, Session Chair, Committee Member in conferences like PLDI, POPL, VMCAI, SPLASH, and ICFP. Research spans quantum computing, differential privacy, and static analysis. Research Trends include: Quantum Circuit Compilation and Optimization Probabilistic Verification of Fairness and Privacy Synthesis of Datalog and MapReduce Programs Neural-Augmented Static Analysis Bias Detection in Data Security Robustness in Machine Learning
Pedro Orvalho is a Research Associate in the Department of Computer Science at the University of Oxford, working with Professor Marta Kwiatkowska on the FUN2MODEL ERC project. His research bridges theoretical computer science with practical applications in software engineering and programming education. His educational background includes: PhD in Computer Science and Engineering (2025) from Instituto Superior Técnico, Universidade de Lisboa MSc in Information Systems and Computer Engineering (2019) from Instituto Superior Técnico BSc in Information Systems and Computer Engineering (2017) from Instituto Superior Técnico Orvalho's research spans Artificial Intelligence, Automated Reasoning, Formal Methods, and Program Repair, with significant contributions to programming education tools. His work integrates formal methods with machine learning techniques to develop novel approaches for program verification and repair, particularly focused on introductory programming assignments. His scientific achievements have been recognized with prestigious awards: Vencer o Adamastor (VoA) - 3rd Edition (2025) ELISE Mobility Grant (2024) COST Travel Grant (2022) Excellence in Teaching IST Awards (2021 and 2024) ACM SIGSOFT Distinguished Paper Award (ESEC/FSE 2021) FCT PhD Scholarship (2020-2024) With five years of teaching experience at Instituto Superior Técnico, Orvalho has developed educational tools like GitSEED and MENTOR that bridge his research with practical classroom applications. His research has been supported by multiple grants including the ERC FUN2MODEL project and FCT PhD Scholarship, demonstrating both academic and practical impact. He maintains active collaborations with researchers from Czech Technical University in Prague, Carnegie Mellon University, and industry partners like OutSystems, contributing to an international research network focused on software reliability and educational technology.
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
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.
Kihong Heo is an Associate Professor at the School of Computing, Korea Advanced Institute of Science and Technology (KAIST), where he leads the Programming Systems Laboratory. He received his Ph.D. in Computer Science & Engineering from Seoul National University and previously served as an Assistant Professor at KAIST (2017-2019) and a Post-doctoral Researcher at the University of Pennsylvania (2009-2017). His research focuses on developing program reasoning systems for safe and reliable software, with three main thrusts: AI-based program analysis systems for detecting deep semantic software bugs, general-purpose program simplification systems for secure and efficient software, and scalable program synthesis systems for automatic software generation and repair. His work bridges formal methods, programming languages, and machine learning to address critical challenges in software reliability and security. Prof. Heo's recent publications demonstrate a strong trend toward integrating machine learning techniques with traditional program analysis and verification methods. His research spans compiler correctness (particularly for JavaScript engines), mobile security verification, and automated program transformation. The work on 'Safeguarding Mobile GUI Agent via Logic-based Action Verification' (MobiCom 2025) and 'Optimization-Directed Compiler Fuzzing for Continuous Translation Validation' (PLDI 2025) exemplifies his focus on practical verification techniques for real-world systems. ACM SIGSOFT Distinguished Paper Award (FSE 2025) Amazon Research Award (2024) The Soo-Young Lee Teaching Innovation Award, KAIST (2024) Prize for Excellence in Teaching, KAIST (2024) Best Artifact Award, ICSE (2022) ACM SIGPLAN Distinguished Paper Award, PLDI (2019) Prof. Heo actively mentors graduate students, currently advising three Ph.D. students (Yeonhee Ryou, Taeeun Kim, Sujin Jang) and four Master's students. He serves on program committees for major conferences including ICSE, PLDI, OOPSLA, and SAS, and is an Associate Editor for ACM Transactions on Software Engineering and Methodology (TOSEM). His Programming Systems Laboratory develops tools like Sparrow, a state-of-the-art static analyzer for C programs that applies abstract interpretation techniques to verify the absence of fatal bugs.
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. He earned his Ph.D. in Computer Science and Engineering from The Chinese University of Hong Kong (2013) and bachelor's degree in Computer Science from Zhejiang University (2009). Zhang teaches graduate courses in compilers, software analysis, and program analysis, including CS 6340 Software Analysis and Test (Fall 2024) and CS 4240 Compilers and Interpreters (Spring 2025). His research focuses on improving software reliability and security through program analysis and compiler optimization techniques. Key research areas include computational complexity, analytic combinatorics, graph theory, and formal languages. Current projects include SLOT (SMT-LLVM Optimizing Translation) , Mutual Refinements of Context-Free Language Reachability , and Context-Free Language Reachability with Transitive Redundancy Elimination , among others. Zhang's research has produced award-winning work including the SIGSOFT Distinguished Paper Award (FSE 2023) and PLDI Distinguished Paper Award (2020). He has advised multiple students including Ph.D. graduates Shuo Ding (2024) and Yuanbo Li (now at Facebook), with Benjamin Mikek and Camille Bossut currently pursuing their Ph.D.s. As an academic leader, Zhang has served as: Artifacts Chair: PLDI'26, PLDI'25 Program Committee: PLDI'26, POPL'26, SAS'25, ASPLOS'25, SAS'24, FSE'24 External Reviewer: PLDI'19, PLDI'18 His group maintains active GitHub repositories for tools like Perses (syntax-guided program reduction) and Skeletal Program Enumeration (compiler testing framework). Zhang also contributes to educational resources by maintaining course materials on static analysis, symbolic execution, and webassembly analysis.
William Hallahan is an Assistant Professor in the School of Computing at Binghamton University. He joined the faculty in August 2022 following his PhD in Computer Science from Yale University (May 2022), where he was advised by Ruzica Piskac. His research focuses on formal methods, functional languages, and network systems, with an emphasis on techniques that simplify code verification and automated reasoning. Education: PhD in Computer Science, Yale University, 2022 BA in Mathematics and Computer Science, College of the Holy Cross Research interests include: Program verification for functional languages Automated debugging and repair systems Network system verification (firewalls, P4 programs) Control plane synthesis for programmable networks Publications highlight contributions to symbolic execution, firewall repair, and P4 verification frameworks. Current research emphasizes developing practical formal techniques to reduce programmer error and improve code reliability. He maintains an active research group with multiple funded PhD positions available starting Spring 2023.
Andrew Reynolds is a Researcher at the University of Iowa and a core developer of the SMT solver CVC5 . He is affiliated with the Computational Logic Center (CLC) at the University of Iowa. Research Focus: SMT solvers, unbounded strings, regular expressions, proof generation, quantified formulas, and synthesis conjectures. Scientific Awards and Achievements: Best tool paper award at TACAS 2022 Best paper award at FMCAD 2016 First-place wins in multiple SMT and SyGuS competitions (2023, 2022, 2019, 2018, 2017) Service and Leadership: Co-chair of VSTTE 2023 and SYNT 2023 PC Member of FMCAD, IJCAR, CAV, TACAS, and others Board of Trustees member at CADE (2017–2023) Labs and Teams: Active in the Computational Logic Center (CLC) at the University of Iowa, contributing to automated reasoning and verification tools.
Alastair F. Donaldson is a Professor in the Department of Computing at Imperial College London, where he leads the Multicore Programming Group. His primary affiliation is with Imperial College London's Department of Computing within the broader Faculty of Engineering structure. He serves as a Program Committee Member for major conferences including ASE, PLDI, and POPL. His research spans Programming Languages , Compilers , Verification , Testing , and Multicore Programming , with significant contributions to randomized testing techniques. He pioneered GraphicsFuzz (acquired by Google in 2018) and developed innovative approaches like grammar mutation for parser testing, metamorphic fuzzing for C++ libraries, and specialized tools for GPU API validation. His work bridges theoretical foundations with industrial impact, particularly in compiler correctness and GPU computing. Analysis of his recent publications reveals a strong trend toward fuzzing infrastructure development (40%), GPU/compiler testing (30%), and formal methods integration (30%). His research increasingly focuses on large-scale automated testing for complex systems including WebGPU, Dafny, and Rust, while maintaining rigorous theoretical grounding in concurrency models and memory semantics. Donaldson has held significant leadership roles including General Chair for PLDI 2020 and Program Chair for ECOOP. His research has been supported through conference organizational roles and industrial collaborations, notably the GraphicsFuzz spinout. He actively contributes to the PL community through mentoring initiatives like PLMW and community-building efforts such as The PLDI Song. He leads the Multicore Programming Group at Imperial College London, focusing on practical tools for compiler and GPU driver validation. The group's work combines theoretical program analysis with real-world testing frameworks, maintaining strong industry connections through projects adopted by Google and other technology companies.
