جست‌وجوی استاد و پژوهشگر

Jingmei Huمشاهده پروفایل

پژوهشگر

• Program Synthesis
• Operating Systems
• Human-Computer Interaction
• +۵ مورد دیگر

Jingmei Hu is an Applied Scientist at Amazon since 2022, with a Ph.D. in Computer Science from Harvard University (2022) under Prof. Margo Seltzer and Prof. Stephen Chong. Her research spans program synthesis and verification for systems, focusing on low-level OS development, human-computer interaction, and parallel computing. Ph.D. in Computer Science, Harvard University, 2022 M.S. in Computer Science, Harvard University, 2018 B.S. in Computer Science, Shanghai Jiao Tong University, 2016 Her work combines program synthesis with human-computer interaction and parallelism to improve usability and scalability, particularly for assembly-level code generation. She has also explored provenance tracking to enhance data scientist workflows and developed secure authentication methods for mobile devices. Her recent publications address assembly synthesis efficiency, OS porting, and provenance-driven debugging tools. Key themes include formal methods, domain-specific languages, and automated reasoning. ACM-W Scholarship (2020) National Scholarship (China), Top 1% at SJTU (2013) She has served on review committees for conferences like OOPSLA, PLDI, and POPL, and her technical expertise includes Python, OCaml, C/C++, and AWS cloud services.

Cesare Tinelliمشاهده پروفایل

استاد

• Automated Reasoning
• Satisfiability Modulo Theories (SMT)
• Model Checking
• +۷ مورد دیگر

Cesare Tinelli is the F. Wendell Miller Professor of Computer Science at the University of Iowa within the College of Liberal Arts and Sciences. He is a co-director of the Computational Logic Center and leads the development of critical tools like the CVC4 and cvc5 SMT solvers, as well as the Kind model checker. His academic credentials include: Ph.D. in Computer Science (1999), University of Illinois at Urbana-Champaign M.S. in Computer Science (1995), University of Illinois at Urbana-Champaign Laurea in Scienze dell'Informazione (1990), University of Bari Research Interests : Tinelli specializes in Automated Reasoning , particularly Satisfiability Modulo Theories (SMT) , Model Checking , Software Verification , and Formal Methods . His recent work explores Inductive Reasoning in SMT , Proof-Certificate Generation , and Logical Frameworks for Proof Systems . His methodologies bridge theoretical advancements with practical implementations, impacting both academia and industry. Scientific Contributions : Tinelli's research drives innovation in SMT solving, model checking, and automated theorem proving. His 15 most recent publications span topics from stateful protocol testing ( Saecred ) to proof certification ( IsaRare ) and generalized optimization ( Generalized OMT ). Awards and Recognition : NSF CAREER Award (2003) Haifa Verification Conference Award (2010) CAV Award (2021) Advising and Collaborations : His former students and postdocs hold positions at leading institutions like NASA, Intel, MIT, and EPFL. He collaborates with organizations such as Amazon, Facebook, General Electric, and Microsoft.

Anne M. Enquistمشاهده پروفایل

عضو هیئت علمی

• Legal Writing
• Legal Education
• Legal Pedagogy
• +۳ مورد دیگر

Anne M. Enquist is a Professor Emerita at Seattle University School of Law, where she has served for over three decades. She is a distinguished leader in legal writing education, having directed the university’s nationally top-ranked Legal Writing Program from 2005–2015. Her roles included associate director, faculty advisor to the Seattle University Law Review and Seattle Journal of Social Justice , and mentor to new legal writing faculty. Enquist holds a B.A. and B.S. (magna cum laude) from New Mexico State University (1972) and a Master of Arts in Teaching from the University of Washington (1977). Her expertise focuses on legal writing pedagogy, grammar, and style, with a commitment to improving law student development and academic support. Her research and publications emphasize practical writing skills, bias recognition in legal analysis, and innovative teaching methods. She co-authored foundational texts such as The Legal Writing Handbook and Just Writing , widely adopted in U.S. law schools. Her work often bridges theory and practice, addressing challenges like millennial student engagement and legal writing program advocacy. Enquist has held leadership roles in the Legal Writing Institute (LWI), including co-founding the organization in 1985. She has delivered over 50 presentations on topics ranging from syntax strategies for ESL students to multitasking’s impact on writing productivity. Her contributions have shaped national legal writing standards and faculty development.

Elizabeth Polgreenمشاهده پروفایل

استادیار

• Programming Languages
• Program Synthesis
• Formal Verification
• +۷ مورد دیگر

Elizabeth Polgreen is a Lecturer (~Assistant Professor) in the School of Informatics at the University of Edinburgh, where she conducts research in programming languages and formal methods, particularly program synthesis and verification. She is affiliated with the Laboratory for Foundations of Computer Science and contributes to the Programming Languages and Software Engineering research area. Her research focuses on formal program synthesis, leveraging techniques such as symbolic reasoning, genetic algorithms, and large language models to improve the scalability and automation of software verification. She explores applications in code modernization, tensor program lifting, and explainable AI. Her work bridges programming languages, AI, and formal methods to build trustworthy systems. Her recent publications (2020–2025) span top venues including PLDI, CGO, AAAI, CAV, OOPSLA, and NeurIPS, showing a strong trend in neuro-symbolic synthesis, grammar inference, and verification of AI and low-resource code. She has secured competitive funding, including a Royal Academy of Engineering fellowship and an Amazon Research Award. Scientific awards include: Royal Academy of Engineering Research Fellowship Amazon Research Award Best Paper Award at GPCE Distinguished Paper Award from CGO She advises multiple PhD students, including Yixuan Li, Alexander Brauckmann, and José Wesley de Souza Magalhães, often in collaboration with Professor Mike O'Boyle. Her research is supported by grants from the Royal Academy of Engineering and Amazon. She has delivered keynotes, tutorials, and a TEDx talk, contributing actively to outreach and education in formal methods. She leads a research group within the Laboratory for Foundations of Computer Science, focusing on trustworthy systems through synthesis and verification. Her team includes PhD students and collaborators working on cutting-edge topics in program analysis, AI for code, and compiler design.

Ravi Chughمشاهده پروفایل

دانشیار

• Programming Languages
• Human-Computer Interaction
• Direct Manipulation Programming Systems
• +۳ مورد دیگر

Ravi Chugh is an Associate Professor in the Department of Computer Science at the University of Chicago. His work bridges Programming Languages (PL) and Human-Computer Interaction (HCI), focusing on direct manipulation programming systems and hole-driven development. Affiliation: University of Chicago Role: Director of Undergraduate Studies Research interests: Direct Manipulation Programming Systems Type Systems Program Synthesis Structured Editing Visual Programming His recent work includes Ragged Blocks (UIST 2025) for structured text rendering, Code Style Sheets (OOPSLA 2025) for styling code, and projects like Sketch-n-Sketch and Hazel for bimodal programming environments. Professional Activities: Program Committee: HATRA 2025, VL/HCC 2023, PLDI 2022, POPL 2021 Artifact Evaluation Co-Chair: PLDI 2018-2020 Editorial Board: Journal of Functional Programming (2020–)

Loris D'Antoniمشاهده پروفایل

دانشیار

• Program Synthesis
• Formal Methods
• Trustworthy Software
• +۳ مورد دیگر

Loris D'Antoni is an Associate Professor at the University of California San Diego, affiliated with the Programming Systems Group and serving as a visiting academic at AWS . Previously, he co-founded a research group at UW-Madison. His research focuses on trustworthy software through Program synthesis (e.g., SemGuS toolkit) Formal verification of machine learning and network protocols Automata theory and symbolic constraints Trustworthy LLMs with grammar alignment Recent work explores semantics-guided synthesis and unrealizability logic , with applications to decision trees, LSTMs, and network routing. Publications span top venues like PLDI , OOPSLA , NeurIPS , and CAV . Notable scientific awards include Best Paper Award at ICDCN 23 Distinguished Paper Award at SBES 21 Oral Presentation at EMNLP 21 Nomination for EAPLS Award (part of ESOP 20 ) He teaches courses in programming languages ( CS-536 ) and synthesis/verification ( CS-703 ), and actively contributes to program committees at conferences like PLDI , CAV , and POPL .

Bernd Finkbeinerمشاهده پروفایل

استاد

• Formal Verification
• Reactive Synthesis
• Hyperproperties
• +۴ مورد دیگر

Prof. Bernd Finkbeiner is a faculty member at CISPA Helmholtz Center for Information Security and holds a Professorship in Computer Science at Saarland University. He earned his Ph.D. in 2003 from Stanford University. Leading the Reactive Systems Group since 2003, now part of CISPA, his research focuses on ensuring safety and security in computer systems through formal methods like specification, program synthesis, and verification. Key projects include output-sensitive reactive synthesis (OSARES), hyperproperty logics (HYPER), and real-time monitoring (RTLOLA). Education : Ph.D. in Computer Science, Stanford University, 2003 His research interests span hyperproperties, formal verification, runtime monitoring of cyber-physical systems, and distributed synthesis. He has pioneered tools like StreamLAB and AutoHyper for hyperproperty analysis. His work on temporal causality and information-flow guided synthesis addresses challenges in distributed and secure systems. Key Achievements : Recipient of ERC Advanced Grant 2022–2027 for Project HYPER Best Paper Awards at ICALP 2009, FSEN 2007, and VMCAI 2012 Leader of the Reactive Systems Group at CISPA Grants & Funding : ERC Advanced Grant supporting research on hyperproperties His lab develops cutting-edge tools for formal methods, including BoSy for bounded synthesis and RTLola for runtime verification. Current research explores compositional synthesis, explainable reactive systems, and robust monitoring for medical and autonomous systems.

Borzoo Bonakdarpourمشاهده پروفایل

دانشیار

• Security/Privacy
• Cyber-physical Systems
• Distributed Computing
• +۵ مورد دیگر

Prof. Borzoo Bonakdarpour is an Associate Professor in the Department of Computer Science and Engineering at Michigan State University's College of Engineering. He directs the Trustworthy and Reliable Technologies Lab (TART), focusing on formal methods in distributed systems, cyber-physical systems, and security/privacy. Research Interests Security/Privacy Cyber-physical Systems Distributed Computing Formal Methods His recent work involves runtime verification, hyperproperty analysis, and fault-tolerant systems. He has received multiple awards, including the Withrow Excellence Award in Teaching (2022), Best Paper Awards at IEEE SRDS (2017), SSS (2014), and ACM SIES (2010), and was recognized as Best Professor by the McMaster Software Engineering Club in 2017. Professional Activities: Serve as PC member for ICCPS'24, CAV'24, RV'23, and General Chair for SRDS'21.

Xiaokang Qiuمشاهده پروفایل

دانشیار

• Programming Languages
• Software Engineering
• Program Verification
• +۲ مورد دیگر

Xiaokang Qiu serves as Associate Professor in Purdue University's Elmore Family School of Electrical and Computer Engineering, specializing in Programming Languages and Software Engineering with core expertise in program verification, program synthesis, and automated deduction. His research establishes critical bridges between enumerative and deductive synthesis methodologies, developing novel frameworks for verified program generation. Key contributions include string transformation synthesis with concurrency guarantees, bit-vector manipulation optimization via syntax-guided enumeration, and network design automation through comparative learning techniques. This work consistently advances formal verification foundations while addressing practical software engineering challenges. Publication trends from 2017-2025 reveal escalating complexity in synthesis targets—from basic data-structure manipulations to concurrent string operations and network configurations. His approach increasingly integrates machine learning elements with formal methods, demonstrating how query-based learning can drive near-optimal system design while maintaining provable correctness guarantees across diverse computational domains.

Arjun Radhakrishnaمشاهده پروفایل

پژوهشگر

• Program Synthesis
• Formal Methods
• Concurrency
• +۳ مورد دیگر

Arjun Radhakrishna is a researcher at Microsoft working on program synthesis and formal methods. Previously, he was a post-doctoral researcher at the University of Pennsylvania under Prof. Rajeev Alur and completed his PhD at IST Austria under Prof. Thomas A. Henzinger. His work focuses on developing tools for reliable systems with applications in concurrency and embedded systems. Education: PhD in Computer Science from IST Austria (2014) Postdoctoral research at University of Pennsylvania Research Interests: Arjun's research lies at the intersection of program synthesis , formal methods , and quantitative system analysis . He develops tools that address soft specifications (e.g., performance, energy consumption) for concurrent and reactive systems , combining techniques from programming languages and formal verification. Key projects include performance-aware concurrency synthesis and quantitative specification frameworks for reactive systems. Scientific Awards: 2014 ACM SIGBED Paul Caspi Memorial Dissertation Award Best Paper Nomination at EMSOFT 2012 Service and Contributions: Arjun has served on program committees for conferences including CAV, PLDI, POPL, and VMCAI. He co-developed EUSolver, a tool that won multiple SyGuS competition tracks (2016). His dissertation introduced techniques for quantitative verification and synthesis with applications in embedded systems and concurrent programming.

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.

• Artificial Intelligence
• Reinforcement Learning
• Machine Learning
• +۳ مورد دیگر

Stuart Russell is a Professor at the University of California, Berkeley , affiliated with the Department of Electrical Engineering and Computer Sciences in the College of Engineering. His research spans Artificial Intelligence , Reinforcement Learning , and AI Ethics , focusing on safety, alignment, and theoretical foundations. Research Interests : Provably beneficial AI systems Human-compatible AI Reinforcement learning theory Language model interpretability AI safety and control mechanisms Recent Work Trends : 2025-2024: Safety frameworks (off-switch games, reversal curse analysis) 2024: Reward learning with partial observability, program synthesis via diffusion 2023: Societal risk taxonomy, human feedback coordination Collaborations include leading researchers like Anca D. Dragan (UC Berkeley), Yoshua Bengio (Mila), and Michael I. Jordan (UC Berkeley), with publications in venues such as NeurIPS , ICLR , and ICML .

Haniel Barbosaمشاهده پروفایل

استادیار

• SMT Solvers
• Formal Verification
• Proof Certificates
• +۵ مورد دیگر

Haniel Barbosa is a tenured Assistant Professor in the Department of Computer Science at Universidade Federal de Minas Gerais (UFMG), Brazil. His research focuses on improving SMT solvers for formal verification and enhancing their trustworthiness through proof certificates, as detailed in his work on projects like Lean-SMT and Carcara. He also serves as a senior technical lead for the state-of-the-art SMT solver cvc5 and actively collaborates with institutions like the University of Iowa, Stanford University, and Inria Nancy. Barbosa's research is supported by grants from the Defense Advanced Research Projects Agency (DARPA), CAPES, and Amazon Web Services. He mentors a diverse team of postdoctoral scholars, PhD students, and MSc students, including Caio Raposo, Tomaz Mascarenhas, Pedro Saccomani, and Bruno Andreotti. His teaching portfolio includes courses like Introduction to Computational Logic, Theory and Practice of SMT Solving, and Formal Methods. His publications span topics such as SMT proof production, proof reconstruction, and syntax-guided synthesis, with a focus on scalable algorithms, higher-order logic extensions, and industrial-strength solver development. Key trends in his work include formal verification, automated reasoning, and the intersection of logic with software engineering. Scientific awards include the Distinguished Tutorial Paper Award at FM 2024 and the Best Tool Paper Award at TACAS 2022 . Barbosa also contributes extensively to academic service as a steering committee member for SBMF, PC chair for LSFA and SBMF conferences, and organizer for SMT-COMP. His outreach includes invited tutorials at ATVA 2024, Dagstuhl Seminars, and workshops on SMT solving.

Arjun Radhakrishnaمشاهده پروفایل

پژوهشگر

• Program Synthesis
• Formal Methods
• Concurrent Programming
• +۲ مورد دیگر

Dr. Arjun Radhakrishna is a Researcher at Microsoft in the PROSE team, specializing in program synthesis and formal methods . His work focuses on developing tools to ensure correctness and optimize soft specifications like performance and energy consumption in concurrent and embedded systems. He previously held post-doctoral positions at the University of Pennsylvania and completed his PhD at IST Austria under Prof. Thomas Henzinger.

• Probabilistic Verification
• Formal Methods
• Artificial Intelligence Safety
• +۷ مورد دیگر

Dr. Sebastian Junges is an Assistant Professor at the Software Science Group of Radboud University (Nijmegen, Netherlands) since September 2021. He previously held postdoctoral and research assistant positions at UC Berkeley and RWTH Aachen University respectively, working under prominent researchers like Sanjit Seshia and Joost-Pieter Katoen . Education: Ph.D. in Computer Science, RWTH Aachen University (2020) M.Sc. in Computer Science, RWTH Aachen University (2015) B.Sc. in Computer Science, RWTH Aachen University (2012) His research focuses on trustworthy algorithms for system dependability , particularly in safety-critical domains like autonomous systems and infrastructure automation. Key technical contributions include: Verification algorithms for Markov decision processes (MDPs) Parameter synthesis in probabilistic models Finite state controller generation Runtime monitoring with imprecise sensors Recent work (2022-2024) has explored multi-objective verification , neuro-symbolic reasoning , and scalable analysis of probabilistic models . His methodological approach combines formal methods with machine learning and automated reasoning techniques, often implemented in the state-of-the-art Storm probabilistic model checking framework. Selected scientific contributions include: Keynote speaker at MODEM 2024 Invited tutorial presenter at Dagstuhl 2024 Co-organizer of multiple VeriProp workshops (2021-2024) Program committee member for TACAS 2026, CONCUR 2024, and CAV 2024 He actively supervises Bachelor and Master student projects in algorithm development for probabilistic systems, including topics on: MDP model checking acceleration Runtime monitoring frameworks Syntax-guided controller synthesis State estimation for fault trees Probabilistic inference transpilation His academic service includes: Radboud Science Faculty Diversitee Committee Steering Committee of ETAPS (2025-2026) Program committee roles across 15+ top venues