جست‌وجوی استاد و پژوهشگر

Kuldeep S. Meelمشاهده پروفایل

دانشیار

• Automated Reasoning
• Formal Methods
• Artificial Intelligence
• +۶ مورد دیگر

Kuldeep S. Meel is the Stephen Fleming Early-Career Associate Professor at the School of Computer Science, Georgia Institute of Technology, and an Associate Professor at the University of Toronto (on leave). He previously held a NUS Presidential Young Professorship at the National University of Singapore. His research focuses on automated reasoning, aiming to enable computing systems to handle uncertain real-world environments through scalable techniques integrating randomized algorithms, statistical inference, formal methods, distribution testing, and software engineering. Core research areas: Automated Reasoning, Formal Methods, Approximate Model Counting, Probabilistic Inference, Constraint Solving His research group has achieved significant recognition in both individual awards and publications. Key trends in his recent work include advancing model counting algorithms, developing frameworks for probabilistic explanations, and improving scalability in formal verification and constraint satisfaction. His tools have consistently ranked top in international competitions, demonstrating practical impact in automated reasoning. 2019 NRF Fellowship for AI 2022 ACP Early Career Researcher Award 2020 IEEE Intelligent Systems AI's 10 to Watch Top placements in Model Counting, SAT, and CAV competitions He mentors a diverse group of PhD and Master's students and collaborates with institutions worldwide. His group's publications span premier conferences in AI, formal methods, and design automation, reflecting interdisciplinary contributions to theoretical and applied computer science.

Sanjit A. Seshiaمشاهده پروفایل

استاد

• Formal Methods
• Cyber-Physical Systems
• Computer Security
• +۱۰ مورد دیگر

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.

Endadul Hoqueمشاهده پروفایل

استادیار

• Computer Networks Security
• IoT Systems Security
• Vulnerability Detection
• +۳ مورد دیگر

Endadul Hoque is an Assistant Professor in the Department of Electrical Engineering and Computer Science at Syracuse University (SU), leading the SYNE Lab. Previously, he held a similar position at Florida International University (FIU). He earned his Ph.D. in Computer Science from Purdue University in 2015, with postdoctoral research at Northeastern University. His research focuses on cybersecurity, particularly in automated vulnerability detection, network/system security, and IoT defense mechanisms. He draws on program analysis, formal verification, and fuzz testing. Key honors include the NSF CAREER Award (2024) and a Google Research Scholar Award (2022). His work has been published in top venues like ACM CCS, NDSS, and IEEE S&P. He actively seeks students for PhD/MSc positions in security, IoT, and program analysis. His grants include NSF funding for IoT policy enforcement and context-sensitive fuzzing. Education Ph.D., Computer Science, Purdue University, 2015 M.S., Computer Science, Marquette University, 2010 B.S., Computer Science and Engineering, Bangladesh University of Engineering and Technology, 2008 Research Interests Dr. Hoque’s work spans secure network systems, IoT security, vulnerability detection, and automated reasoning methods like SMT solving and symbolic execution. Recent innovations include VetIoT (runtime IoT defense validation) and LLM-driven security tools like iConPAL. He emphasizes practical defenses and user-centric security solutions, such as the SeQR enterprise Wi-Fi configurator. Awards NSF CAREER Award (2024) Google Research Scholar Award (2022) NDSS Distinguished Paper (2018) Grants & Service He leads NSF-funded projects on IoT policy enforcement and context-sensitive fuzzing. Served on program committees for S&P, SecDev, and DSN. Teaches courses on systems security and operating systems at SU and FIU. Lab/Team SYNE Lab at Syracuse University focuses on securing networked systems through automated analysis, runtime verification, and resilient protocols.

• Programming Languages
• Formal Methods
• Software Engineering
• +۴ مورد دیگر

Alexander Summers is an Associate Professor at the Department of Computer Science , University of British Columbia . He joined UBC in March 2020 after serving as a Senior Researcher (Oberassistent) at ETH Zurich from 2014-2020. His research bridges Programming Languages , Formal Methods , and Software Engineering , with a focus on automated verification tools for heap-based and concurrent programs. MSc Joint Mathematics and Computer Science, Imperial College London (2004) PhD Computer Science, Imperial College London (2009) Postdoc, ETH Zurich (2009-2014) Summers leads the Prusti Project , developing deductive verification tools for Rust, and contributes to the Viper Project for intermediate verification languages. His work addresses challenges in: Memory safety and concurrency verification Ownership models and aliasing control Automated reasoning with SMT solvers Resource-oriented programming specifications Debugging verification condition quantifiers Formal validation of verification infrastructure His research has been recognized with a Amazon Research Award and ACM SIGPLAN Distinguished Paper Awards . He teaches courses like Advanced Software Engineering and Program Verifiers and Program Verification , and supervises graduate students in formal verification and Rust-related research.

Zhe Zengمشاهده پروفایل

استادیار

• Artificial Intelligence
• Machine Learning
• Neurosymbolic AI
• +۸ مورد دیگر

Zhe Zeng is an incoming Assistant Professor in the Department of Computer Science at the University of Virginia starting July 2025. Currently, she serves as a Faculty Fellow in the Computer Science Department at New York University. She earned her Ph.D. in Computer Science from UCLA in 2024 under Professor Guy Van den Broeck, and her B.S. in Mathematics from Zhejiang University in 2018. Research Focus: Dr. Zeng specializes in neurosymbolic AI and probabilistic machine learning, developing methods that integrate symbolic knowledge (logical constraints, graph structures) with probabilistic uncertainty. Her work spans three core areas: Reasoning: Probabilistic inference, tractable probabilistic models Learning: Constrained deep learning, graph ML, weakly supervised learning Trustworthiness: Explainability, uncertainty quantification, domain-knowledge integration Awards & Honors: Rising Star in EECS (2023) Amazon Doctoral Fellowship (2022) NEC Research Fellowship (2021) ICML Travel Award (2018) Outstanding Graduate, Zhejiang University (2018) Advising & Mentoring: Has supervised six students including PhD candidates and undergraduates at UCLA, Tsinghua, and CAS, with placements at Princeton and UT Austin. Academic Service: Regularly reviews for NeurIPS, ICML, ICLR, UAI; served as UAI 2023 discussant; active in WiML mentorship programs.

Zhendong Suمشاهده پروفایل

استاد

• Programming Languages
• Compilers
• Software Engineering
• +۳ مورد دیگر

Zhendong Su is a full professor in the Department of Computer Science at ETH Zurich since August 2018. Previously, he held a full professorship at UC Davis from 2003 until June 2019. He earned his Ph.D. in Computer Science from UC Berkeley and dual Bachelor’s degrees in Computer Science and Mathematics from UT Austin in 1995. Affiliations: ETH Zurich: Full Professor (since 2018) UC Davis: Full Professor and Chancellor’s Fellow (2003–2019) IEEE Fellow, ACM Fellow, and Member of Academia Europaea His research focuses on programming languages, compilers, software engineering, computer security, and education technologies . Key contributions include compiler validation (e.g., Project Yin-Yang for SMT solvers and DBMS testing), testing tools like SQLancer, and educational innovations such as the Algot visual programming language. Recent work emphasizes secure AI (e.g., CipherSteal for TEE-shielded models) and compiler reliability (e.g., Artemis/Apollo for JIT validation). He has pioneered techniques like metamorphic testing and equivalence modulo inputs (EMI) for compiler validation, uncovering thousands of bugs in GCC/LLVM and SMT solvers. Awards: ICSE MIP Award (2022), ACM SIGSOFT Impact Paper (2018), NSF CAREER Award, and multiple industrial awards. His students have won IEEE TCSE Rising Star and SIGSOFT Impact Paper awards, securing roles at top universities and companies like Google and NVIDIA. Service: Steering committee member of ISSTA and ESEC/FSE, ACM Distinguished Speaker, and Associate Editor for ACM TOSEM. Program chaired ISSTA 2012 and co-chaired FSE 2016. Labs/Teams: Leads research groups on compiler validation, secure AI, and education technologies. Projects include Yin-Yang (SMT testing), SQLancer (DBMS fuzzing), and Algot (visual programming for education).

• Formal Verification
• Software Testing
• Programming Languages
• +۱۲ مورد دیگر

Alastair F. Donaldson is a Professor and Director of Research in the Department of Computing at Imperial College London, where he leads the FastPL research group. His work bridges formal methods, software testing, and programming languages, with a focus on enhancing the reliability of high-performance and parallel software systems. He has held key roles including Director of Research (since 2023) and previously served as Lecturer (2011–2014), Senior Lecturer (2014–2017), and Reader (2017–2020) before being promoted to Professor in 2020. His research interests include formal verification, compiler testing, GPU programming, concurrency, and fuzzing. He has made significant contributions to the verification of GPU kernels, metamorphic testing of graphics drivers, and the development of tools like GPUVerify and GraphicsFuzz. His work combines theoretical rigor with practical impact, demonstrated by the acquisition of his startup GraphicsFuzz by Google in 2018 and his subsequent roles as Senior Software Engineer and Visiting Researcher at Google. His recent publications reflect a sustained focus on compiler and system reliability, with trends in fuzzing, formal specification, and automated testing of complex systems such as WebGPU, CXL cache coherence, and large language models for code generation. His work increasingly integrates empirical validation with formal techniques to uncover subtle bugs in real-world systems. Scientific awards and recognitions include: 2017 BCS Roger Needham Award EPSRC Early Career Fellowship Fellow of the British Computer Society Best Paper awards at EuroSys 2024, MET 2021, IISWC 2019, IWOCL 2019, and ICST 2016 Best Industry Paper at ICST 2024 ACM SIGSOFT Distinguished Paper at ISSTA 2023 ACM SIGPLAN Most Influential OOPSLA Paper Award (2012 paper), awarded in 2022 Best Student Paper at PPoPP 2014 He has advised numerous PhD students and leads a vibrant research group. He has secured significant research funding and collaborates extensively with industry and academia. His service includes leadership roles such as General Chair of PLDI 2020, PC Chair of ECOOP 2019, and Steering Committee Chair of PLDI (2022–2025). He also serves on the advisory board of PACM-PL and on program committees for top venues including POPL, OOPSLA, PLDI, ICSE, and ISSTA. He leads the FastPL research group, which focuses on the design and implementation of programming tools and techniques for reliable software. The group conducts cutting-edge research in compiler testing, formal methods, and high-performance systems, fostering collaboration across academia and industry.

Felix Brandtمشاهده پروفایل

استاد

• Algorithmic Game Theory
• Computational Social Choice
• Theoretical Computer Science
• +۲ مورد دیگر

Prof. Felix Brandt is a Professor of Algorithmic Game Theory at the Technical University of Munich (TUM), within the School of Computation, Information and Technology. His research focuses on algorithmic game theory, computational social choice, and their intersections with theoretical computer science, AI, and economics. Education: Diploma and PhD from TUM, postdoctoral research at Carnegie Mellon University and Stanford University. Habilitation from LMU Munich (2010). Research interests include social choice theory, mechanism design, and strategic behavior in multi-agent systems. Notable contributions include work on tournament solutions, probabilistic social choice, and Nash equilibrium characterizations. Recent articles explore Condorcet-consistent voting systems, stability in hedonic games, and axiomatic foundations of Nash equilibrium. Awards include the DFG Heisenberg Professorship (2010) and TUM Supervisory Award (2021). Advises over 10 PhD students and has supervised numerous postdocs. Active in editorial roles for journals like Games and Economic Behavior and Social Choice and Welfare .

• Model-Based Testing
• Automata Theory
• Machine Learning
• +۵ مورد دیگر

Bernhard Aichernig is an Associate Professor at the Institute of Software Engineering and Artificial Intelligence. His work bridges formal methods, model-based testing, and artificial intelligence, with a focus on automata learning, digital twins, and AI-assisted programming. Institution: Institute of Software Engineering and Artificial Intelligence Key Research Areas: Model-Based Testing, Automata Learning, AI-Driven Verification His research explores the integration of machine learning into formal verification, enabling scalable testing of complex systems like IoT devices and reinforcement learning agents. Recent projects include AI-Augmented DevOps frameworks (AIDOaRT) and digital twin validation (LearnTwins). Notable scientific awards include multiple best paper recognitions at SEFM (2020, 2021) and the TAYSIR Competition first place (2023). His publications emphasize hybrid approaches combining genetic programming, SMT solving, and neural networks for system modeling. 2025 : AI-assisted programming, timed automata via domain knowledge 2024 : Stochastic environment modeling, Git system learning 2023 : Reinforcement learning under partial observability, digital twins for VPN servers He actively contributes to testing frameworks like AALpy and investigates explainable AI for fault diagnosis in cyber-physical systems.

• Formal Verification
• Software Testing
• Programming Languages
• +۶ مورد دیگر

Alastair F. Donaldson is a Professor and Director of Research in the Department of Computing at Imperial College London, where he leads the FastPL research group. His academic career spans over a decade at Imperial, progressing from Lecturer (2011-2014) to Senior Lecturer (2014-2017), Reader (2017-2020), and Professor (2020-present). He has also held significant industry positions, including Founder and Director of GraphicsFuzz Ltd. (acquired by Google in 2018), Senior Software Engineer at Google (2018-2021), and Visiting Researcher at both Google and Microsoft Research Redmond. Donaldson earned his PhD from the University of Glasgow under Alice Miller, following a BSc (hons, First Class) in Computing Science and Mathematics. His postdoctoral work included an EPSRC Postdoctoral Research Fellowship at the University of Oxford and a Research Fellowship at Wolfson College Oxford. His research focuses on formal analysis, software testing and programming languages techniques for improving software reliability, with special emphasis on high-performance systems. Donaldson's work bridges theoretical foundations with practical applications, particularly in compiler testing, GPU programming verification, and metamorphic testing. His research has significantly influenced both academia and industry, as evidenced by the acquisition of his startup GraphicsFuzz by Google. Analysis of his recent publications reveals a strong focus on fuzz testing techniques applied across diverse domains including compilers, GPUs, cryptographic protocols, and large language models. His work consistently combines formal methods with practical testing approaches, addressing challenges in compiler correctness, memory models, and API verification across multiple platforms. 2017 BCS Roger Needham Award EPSRC Early Career Fellowship Best Paper Award, EuroSys 2024 Best Paper Award, MET 2021 Best Paper Award, IWOCL 2019 Best Paper Award, IISWC 2019 Best Paper Award, ICST 2016 ACM SIGSOFT Distinguished Paper Award, ISSTA 2023 ACM SIGSOFT Distinguished Paper Award, FSE 2017 ACM SIGPLAN Most Influential OOPSLA Paper Award, 2022 (for GPUVerify) As Director of Research in the Department of Computing, Donaldson oversees research strategy and development. His FastPL research group investigates novel techniques for programming, testing and reasoning about high performance systems. He has served on numerous program committees and held leadership roles including PLDI Steering Committee Chair (2022-2025) and PACM-PL Advisory Board member. His industry engagement includes testifying as an Expert Witness in the IBM UK Ltd v LzLabs GmbH & Ors case. The FastPL research group, which Donaldson leads, focuses on formal analysis, software testing and programming languages. The group has made significant contributions to compiler testing, GPU verification, and metamorphic testing techniques, with practical impact demonstrated by the acquisition of GraphicsFuzz. Current research directions include fuzzing for zero-knowledge proof circuits, randomized testing of decompilers, and systematic testing of large language models for code generation.

Fei Heمشاهده پروفایل

دانشیار

• formal methods
• program analysis
• automated reasoning
• +۲ مورد دیگر

Fei He is an Associate Professor at Tsinghua University's School of Software, where he leads the THUFV research lab focused on formal verification and program analysis. His research spans formal methods, automated reasoning, and program verification, with applications in concurrent systems, networking (P4 programs), and probabilistic systems. Education & Employment: PhD from Tsinghua University (2008) Visiting Scholar at Carnegie Mellon University (2010-2011) and Politecnico di Milano (2006-2007) Faculty positions at Tsinghua since 2008 (Assistant Professor 2008-2011, Associate Professor 2011-present) Research: He's developed innovative techniques in SMT solving for concurrency verification, termination analysis, and regression verification. His tools like Deagle have won gold medals at SV-COMP. Current work focuses on probabilistic program verification and network program analysis. Publications: His 80+ publications demonstrate consistent contributions across formal methods (PLDI, OOPSLA, ICSE), networking (NSDI, INFOCOM), and software engineering (TSE, TOSEM), with recent emphasis on data-driven verification and automated invariant inference. Awards: Gold Medals in SV-COMP ConcurrencySafety (2022, 2023, 2025) Best Paper Awards at PPoPP 2022 and SETTA 2022 Advising: Mentors 13 PhD/Master's students in THUFV lab, with graduates joining Huawei, MPI-SP, and research institutions. Secured multiple NSF China grants for trustworthy software research. Service: Associate Editor for Theory of Computing Systems, program committees for PLDI/ICSE/OOPSLA, and former Local Chair for ISSTA 2019.

• Compilers
• Automatic Software Verification
• Compiler Optimization
• +۷ مورد دیگر

Nuno Pereira Lopes is an Associate Professor at Instituto Superior Técnico , part of Universidade de Lisboa , and a researcher at INESC-ID . He also serves as an advisor at FuriosaAI , focusing on tensor contraction processors for AI workloads. Research Interests : Compilers, formal verification of LLVM optimizations, machine learning frameworks, undefined behavior exploitation, probabilistic model checking, blockchain security, and many-core code generation. Teaching : Compilers and Computer/Informatics Engineering projects. Funding : Supported by Google, Matter Labs, NLnet, Oracle, PRACE, RNCA, and Woven by Toyota. Recent Publications focus on LLVM backend validation , PyTorch pipeline parallelism , C++ dynamic cast optimization , undefined behavior in C/C++ , and AI tensor processors . His work bridges compiler design, formal methods, and AI hardware. Academic Service includes representing Portugal in ISO/IEC JTC 1/SC 22 (C++), organizing FLoC'26 , and serving on program committees for PLDI, EuroLLVM, and CGO.

Omar Haider Chowdhuryمشاهده پروفایل

دانشیار

• Computer Security
• Network Security
• Software Security
• +۱۳ مورد دیگر

Omar Haider Chowdhury is a SUNY Empire Innovation Scholar and Associate Professor in the Department of Computer Science at Stony Brook University. Previously, he was an Assistant Professor at the University of Iowa where he received the Dean's Scholar Award. He completed his postdoctoral research at Cylab, Carnegie Mellon University and Purdue University. His educational background includes a Ph.D. in Computer Science from the University of Texas at San Antonio under the supervision of Prof. Jianwei Niu and Prof. William H. Winsborough (deceased), and undergraduate education in Computer Science and Engineering at the Bangladesh University of Engineering and Technology (BUET). Chowdhury's research focuses on Computer Security and Privacy, with particular emphasis on applying formal verification, automated reasoning, runtime verification, programming languages, software engineering, and human-computer interaction techniques to solve practical security problems. His work addresses security challenges in SSL/TLS, X.509 PKI, Cellular Networks, Wi-Fi, Internet-of-Things (IoT), and Regulatory Compliance. He is also interested in fundamental problems in automated reasoning and formal verification. His recent publications demonstrate a strong focus on applying formal methods to practical security problems, with particular emphasis on cellular networks (4G/5G), IoT systems, and cryptographic protocols. His research shows a consistent pattern of bridging theoretical verification techniques with real-world security implementations, resulting in enhancements to widely used protocols like 4G LTE, 5G, and WPA2 enterprise. His scientific contributions have been recognized with numerous awards including: 2023 Test of Time Award, ACM SACMAT 2022 Dean's Scholar Award, University of Iowa 2021 Best Paper Award (Runner Up), ACM CCS 2020 Best Paper Award, ACNS 2019 DARPA Young Faculty Award Multiple Best Paper Awards at IEEE DASC, ACSAC, and NDSS Chowdhury has successfully mentored several PhD students including Dr. Moosa Yahyazadeh (now at Apple Inc.), and currently advises students including Joyanta Debnath, Muhammad Daniyal Pirwani, and Aliakbar Sadeghi. His research has been funded by both National Science Foundation (NSF) and Defense Advanced Research Projects Agency (DARPA), including a prestigious DARPA Young Faculty Award. His group's findings have directly influenced improvements in widely used security protocols and cryptographic libraries. He leads a research group focused on high-assurance software design and implementation, recently teaching courses on these topics at Stony Brook University. His research group combines expertise in formal methods, security analysis, and practical implementation to tackle emerging security challenges in modern computing systems.

• Theorem Proving
• Automated Reasoning
• Formal Methods
• +۱۴ مورد دیگر

Jasmin Blanchette is a Professor of Theoretical Computer Science and Theorem Proving at the Institute for Informatics, Ludwig-Maximilians-Universität München (LMU), where he also serves as Dean of Studies for Computer Science since January 2024. He is additionally affiliated as a guest researcher with the VeriDis group at Loria in Nancy, France. His research lies at the intersection of automated and interactive theorem proving, with a focus on higher-order logic and proof automation. Key projects include the development of tools like Sledgehammer, Nitpick, and Zipperposition, and foundational work on (co)datatypes and higher-order superposition. His recent publications reflect a strong trend in formalizing and verifying automated reasoning techniques, especially in higher-order logic, with applications in proof automation, SMT solving, and logical verification. Articles frequently appear in top venues such as CADE, ITP, and the Journal of Automated Reasoning. CADE 2023 Best Paper Award for 'Verified given clause procedures' FroCoS 2023 Best Paper Award (with Visa Nummelin and Sander Dahmen) IPA Dissertation Award (awarded to his student Petar Vukmirović) Dutch 'cum laude' distinction (awarded to his student Anne Baanen) Dutch Prize for ICT Research 2022 Blanchette has advised numerous PhD and postdoctoral researchers, many of whom are now active contributors to the formal methods community. He has received significant research grants through projects like Matryoshka and Nekoka. He is also the editor-in-chief of the Journal of Automated Reasoning and plays a central role in organizing key conferences such as ITP, CADE, and CPP. He leads an active research group at LMU, consisting of postdocs and PhD students working on topics such as higher-order superposition, formalization of voting systems, categorical logic, and proof search heuristics. The team collaborates closely with international groups, including those at Inria and TU Wien.

Jürgen Gieslمشاهده پروفایل

استاد

• Program Verification
• Automated Deduction
• Termination Analysis
• +۱۲ مورد دیگر

Jürgen Giesl is a Professor at the Teaching and Research Area Computer Science 2 within the Department of Computer Science at RWTH Aachen University , Germany. He leads research in programming languages, formal verification, automated deduction, and term rewriting systems. Research Interests: Automated Termination and Complexity Analysis of Programs Dependency Pairs and Term Rewriting Systems Verification of Probabilistic and Integer Programs Static Analysis and Symbolic Execution Model Checking and Constrained Horn Clauses Development of Automated Tools (AProVE, LoAT) His recent research, reflected in the latest publications, focuses on termination and complexity analysis for probabilistic programs, polynomial loops, and integer programs, using advanced techniques such as dependency pairs, loop acceleration, and semiring semantics. He also contributes to SMT solving and transitive relation learning for infinite-state model checking. Scientific Awards: Best Tool Paper Award at iFM 2017 Silver Medal (Second Best Paper) at SEFM '16 Best Paper Honourable Mention at IJCAR 2024 Best Student Paper Honourable Mention at IJCAR 2024 Advising and Grants: Giesl has supervised numerous PhD and Master’s students, including prominent researchers such as Fabian Frohn, Jens Hensel, Nils Lommen, and Marcel Hark. He leads a large research group focused on automated verification and has contributed extensively to international verification competitions. His work is supported by ongoing research grants and collaborations with leading institutions in formal methods. Labs and Teams: He leads the Programming Languages and Verification research group at RWTH Aachen, which develops and maintains the AProVE and LoAT tools. These tools are central to automated termination and complexity analysis and are regularly submitted to international competitions such as TERMCOMP and VBS.