جستجوی استاد راهنمای دانشگاهی

Fabian Suchanek is a full professor at Institut Polytechnique de Paris, specifically affiliated with Télécom Paris. He leads research in the Data, Intelligence, and Graphs (DIG) team within the Computer Science department. His academic career focuses on bridging artificial intelligence with structured knowledge representations. Suchanek's research interests span artificial intelligence, knowledge bases, and natural language processing, with particular emphasis on knowledge graph construction , rule mining , knowledge-based language models , and explainable AI . His work demonstrates how structured knowledge can enhance machine learning systems, particularly large language models, by providing factual grounding and interpretability. The research group he leads develops practical systems that address real-world knowledge management challenges. His recent publications showcase a strong trajectory in knowledge-intensive AI, with notable contributions to knowledge graph completion, rule mining techniques, and neural approaches to knowledge base validation. The research demonstrates increasing integration between symbolic and neural approaches to AI. Best Student Paper Award at KR 2024 for work on contextual reasoning Best Demo Award of IJCAI 2024 for rule mining in knowledge graphs French Open Research Award for the YAGO project Best Paper Award of ESWC 2021 for Neural Knowledge Base Repairs Suchanek has secured significant research funding, evidenced by his active recruitment of PhD students for knowledge-based language model research. He has held visiting positions, including at Nanyang Technological University (June-September 2023), and is recognized internationally through keynote invitations such as the Singapore ACM SIGKDD Symposium 2023. He has deliberately stepped back from administrative duties at Institut Polytechnique de Paris to focus on research. His laboratory maintains strong industry connections through open-source software projects including the YAGO knowledge base, AMIE for rule mining, STACI for explainable AI, and several other tools that have become standard in knowledge representation research.

• Artificial Intelligence
• Knowledge Bases
• Natural Language Processing
• +۳ مورد دیگر

Deian Stefan is an Associate Professor at the University of California San Diego (UCSD) in the Department of Computer Science and Engineering . His research spans security , programming languages , and systems , with a focus on building principled and practical secure systems. He has served as a co-founder and Chief Scientist at Intrinsic (acquired by VMWare) and contributed to standards bodies like the W3C WebAppSec and Node.js Security Working Groups . His research interests include: Secure Systems : Web frameworks, browser designs, sandboxing, runtime systems Language-Based Security : Constant-time programming, memory safety, information flow control Verification : Security verification, static/symbolic analysis tools WebAssembly and JavaScript JITs security Deian Stefan has received multiple scientific awards , including several Distinguished Paper Awards at venues like POPL, ICFP, and USENIX Security, as well as the IEEE Cybersecurity Award for Practice (2022) and CSAW 2020 First Place for Applied Research. He has taught courses on Computer Security (CSE 127, CSE 227) and advanced topics in Building Secure Systems (CSE 291) using Rust, WebAssembly, and blockchain security. His work has been supported by collaborations with industry and academia, including projects like RLBox and COWL .

• security
• programming languages
• systems
• +۷ مورد دیگر

Daniel Varro is a Professor affiliated with McGill University (Faculty of Engineering, School of Computer Science), with strong ties to Budapest University of Technology and Economics and Linköping University. He is a leading researcher in model-driven engineering, cyber-physical systems, and software engineering, actively contributing to top-tier conferences such as MODELS, ICSE, and ASE. His research focuses on model-based systems engineering (MBSE) , automated model generation , model transformations , and constraint-based consistency checking . Recently, his work has expanded into integrating large language models (LLMs) and machine learning into modeling workflows, including model querying, domain modeling, and bug detection. The recent publications reveal a strong trend toward AI-augmented modeling, logic-based solvers (e.g., Refinery), and safety assurance of autonomous systems (e.g., COLREGs compliance). His work bridges formal methods with practical software engineering challenges in industrial and safety-critical domains. Scientific Awards: No specific awards mentioned in the text. Advising and Grants: While no explicit list of students or grants is provided, his mentorship in the Doctoral Symposium and repeated leadership roles suggest active supervision and likely grant funding. He has led projects on automated model generation, model quality, and AI integration in modeling. Labs and Teams: Daniel Varro is associated with research groups focused on model-driven engineering and software evolution, likely leading or co-leading teams working on the VIATRA and Refinery frameworks for model transformation and solving.

• Model-Based Systems Engineering
• Cyber-Physical Systems
• Software Engineering
• +۱۲ مورد دیگر

Valerie Viet Triem Tong is a Research Professor at the Paris Institute of Electrical and Electronic Engineering, School of Electrical and Electronic Engineering. She has established herself as a leading researcher in cybersecurity with a particular focus on information flow control systems, Android security, and malware analysis. Her work spans both theoretical foundations and practical security tools development. Her research interests center on Information Flow Control , where she has developed frameworks for monitoring and enforcing security policies at both operating system and application levels. She has made significant contributions to Android Security , creating tools for detecting malicious behavior in mobile applications and addressing privacy concerns in smartphone environments. Her work in Malware Analysis includes developing advanced techniques for tracking and visualizing malware behavior, with emphasis on evasive Windows malware and Android malware in the wild. She also investigates Peer-to-Peer Network Security , focusing on Sybil attack resistance and distributed identity management. Analysis of her publication record reveals a consistent trajectory from foundational work in information flow theory to increasingly applied security research. Her recent work shows a strong emphasis on practical security tools (DaViz, GUI-Mimic, BAGUETTE), security evaluation methodologies (Digital twin, CERBERE), and addressing contemporary challenges in malware analysis (debiasing datasets, handling obfuscated applications). A notable trend is her integration of visualization techniques with security analysis to make complex security data accessible to both experts and machine learning systems. As an advisor, she has mentored numerous researchers who have become first authors on significant publications, including Radoniaina Andriatsimandefitra, Tomás Concepcion Miranda, and Cedric Herzog. Her research has been supported by multiple grants focused on cybersecurity infrastructure, though specific grant details are not provided in the available information. Dr. Tong is actively involved with the CIDre security research group in Rennes, contributing to collaborative projects that bridge theoretical security models with practical implementation challenges. Her work on information flow monitoring has evolved from basic research to applied systems that address real-world security concerns across multiple platforms.

• Information Flow Control
• Android Security
• Malware Analysis and Detection
• +۵ مورد دیگر

Mingsheng Ying is a Distinguished Professor and Research Director of the Centre for Quantum Computation and Intelligent Systems (QCIS) at the Faculty of Engineering and Information Technology, University of Technology Sydney, Australia. He also holds the position of Cheung Kong Professor at the State Key Laboratory of Intelligent Technology and Systems, Department of Computer Science and Technology, Tsinghua University, Beijing, China. Professor Ying graduated from the Department of Mathematics, Fuzhou Teachers College, Jiangxi, China, in 1981. His primary research interests span quantum computation (particularly quantum programming and model-checking quantum systems), programming theory and formal methods, and the foundations of artificial intelligence (focusing on logic and uncertainty). As an author of the books "Foundations of Quantum Programming" (Elsevier - Morgan Kaufmann 2016) and "Topology in Process Calculus: Approximate Correctness and Infinite Evolution of Concurrent Programs" (Springer-Verlag, 2001), he has published over 100 papers in top international journals and conferences. His recent research publications demonstrate a strong focus on quantum programming languages, verification techniques for quantum systems, and the theoretical foundations of quantum computation. The trend in his work shows increasing emphasis on formal verification methods for quantum systems, particularly model-checking techniques for quantum Markov chains and quantum processes. His research bridges theoretical computer science with quantum information theory, creating frameworks for reliable quantum software development. Editorial Board, Artificial Intelligence, Elsevier, Amsterdam Editorial Board, Fuzzy Sets and Systems, Elsevier, Amsterdam Vice President, International Fuzzy Systems Association (elected in 2005) Program Chair, IFSA 2005, World Congress of International Fuzzy Systems Association Chairman, Chinese Association of Fuzzy Systems and Mathematics Professor Ying has secured significant research funding including multiple Australian Research Council Discovery Projects such as "Model-checking quantum Markov chains: towards verification techniques for quantum cryptographic systems" (2013-2015) and "Process algebra approach to distributed quantum computation and secure quantum communication" (2011-2013). His work has also received funding from the National Natural Science Foundation of China and Tsinghua University. At QCIS, he leads research in quantum software theory and methodology, with applications in quantum cryptography and secure communication.

• Quantum Computation
• Quantum Programming
• Model-checking Quantum Systems
• +۵ مورد دیگر

Caterina Urban is a Research Scientist (Chargé de Recherche) at INRIA and École Normale Supérieure (ENS) in Paris, France. She is a member of the INRIA research team ANTIQUE (ANalyse StaTIQUE), where she focuses on formal methods and static analysis. Prior to her current position, she was a postdoctoral researcher at the Chair of Programming Methodology, led by Peter Müller at ETH Zurich. Dr. Urban holds a PhD in Computer Science (2015) from École Normale Supérieure, Paris, where she worked under the joint supervision of Radhia Cousot and Antoine Miné. She also earned a Master's degree (2011) and Bachelor's degree (2009) in Computer Science, both with full marks and honors (summa cum laude) from the Università degli Studi di Udine, Italy. Her research interests span the whole spectrum of formal methods with a focus on developing rigorous methods and tools to enhance the reliability of computer software, particularly data science applications. Her main area of expertise is static analysis based on abstract interpretation. Dr. Urban is currently engaged in several research projects including Lyra (focusing on data science software), Libra (fairness certification for neural networks), and SAIF (addressing safety concerns in machine learning-based systems). Dr. Urban's recent publications demonstrate her expertise in applying abstract interpretation to diverse areas including machine learning, data science, program verification, and security. Her work bridges theoretical foundations with practical applications, particularly in ensuring the reliability and trustworthiness of increasingly critical data science and machine learning systems. She has received recognition for her work through invitations to serve on program committees for major conferences including OOPSLA 2026, PLDI 2026, and CAV 2026. She is also the general chair of iFM 2025 in Paris. Dr. Urban actively mentors the next generation of researchers, supervising PhD students and postdoctoral researchers. She teaches courses on abstract interpretation and its applications at the Master Parisien de Recherche en Informatique (MPRI) and various international summer schools. She has developed several open-source software tools including Lyra (a static analyzer for data science applications), Libra (for fairness certification of neural networks), and Typpete (SMT-based static type inference for Python).

• Static Program Analysis
• Abstract Interpretation
• Programming Languages
• +۳ مورد دیگر

Limin Jia is a Research Professor in the Electrical and Computer Engineering (ECE) department at Carnegie Mellon University, with a courtesy appointment in the Computer Science Department (CSD). Affiliated with CyLab, their work focuses on applying formal techniques to enhance software security through programming language design, formal verification, and information flow analysis. Research interests span Security Programming Languages Formal Verification Information Flow Control Intermittent Computing Rust Programming . Recent publications integrate formal methods with practical security challenges, including Node.js vulnerability detection Rust API testing Secure multi-execution Intermittent computing type systems IFTTT security analysis Browser security frameworks . Limin serves on program committees for conferences like POPL, PLDI, VMCAI, and is actively involved in teaching courses such as Browser Security (18-636) Introduction to Information Security (18-631) .

• Security
• Programming Languages
• Formal Verification
• +۳ مورد دیگر

Conrad Watt is an Assistant Professor at Nanyang Technological University (NTU), Singapore , specializing in WebAssembly, formal verification, and concurrency. He previously served as a Research Fellow at Peterhouse, University of Cambridge, and earned his PhD under Peter Sewell. Co-chair of the W3C WebAssembly Community Group Active in WebAssembly standards development, including concurrency specifications Developed mechanizations in theorem provers like Isabelle/HOL Collaborator with industry (wasmtime engine) and academic teams on verification tools Research Focus: Formal verification of low-level languages, concurrency models, and security mechanisms for WebAssembly. His work bridges theoretical rigor with practical applications, including WasmRef-Isabelle and threads projects. Recent Trends: 2025 publications explore separation logic automation and concurrency experiments, while 2024-2023 work emphasizes specification toolchains (SpecTec), verified interpreters, and memory-safe execution techniques. Scientific Awards ACM Doctoral Dissertation Award Honorable Mention EAPLS Best Dissertation Award Advising: Supervises PhD students Qiyuan Xu and Antanas Kalkauskas. Collaborates with researchers like Philippa Gardner and Jean Pichon-Pharabod.

• WebAssembly
• Formal Verification
• Programming Languages
• +۴ مورد دیگر

Damien Stehlé is a Professor at the École Normale Supérieure de Lyon (ENS Lyon), affiliated with the Laboratoire LIP (CNRS, ENSL, INRIA, UCBL, U. Lyon) and a member of the AriC team. He is also a member of the Institut Universitaire de France. His research focuses on cryptography, computational number theory, and computer algebra, particularly lattice-based cryptography and its applications in post-quantum security. He has held editorial roles at the Journal of Cryptology and Designs, Codes and Cryptography, and served on committees for major conferences like ASIACRYPT and CRYPTO. His work has led to advancements in lattice reduction algorithms, cryptographic protocols (e.g., signatures, encryption schemes), and security proofs in the quantum random oracle model. Stehlé has supervised numerous PhD students, including Alice Pellet-Mary and Miruna Rosca, and has contributed to open-source lattice reduction software like fplll. His awards include Best Paper Awards at ASIACRYPT 2021 and 2015. He teaches advanced courses on post-quantum cryptography and cryptanalysis at the Master’s level.

• Cryptography
• Computational Number Theory
• Computer Algebra
• +۳ 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.

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

Gang (Gary) Tan is a Professor at the Pennsylvania State University's College of Engineering, specializing in computer security, formal methods, and programming languages. He co-directs the Institute for Networking and Security Research (INSR) and leads the Security of Software (SOS) Group, focusing on compiler, programming language, and formal method techniques to enhance computer security. Education: B.E. in Computer Science from Tsinghua University Ph.D. in Computer Science from Princeton University His research integrates formal verification with practical security applications, particularly emphasizing: Compiler-based security enforcement Side-channel mitigation in speculative execution Fairness analysis in machine learning systems Formal grammar approaches for software reliability Key article trends show: Security-focused formal methods (15% of publications) ML fairness verification (20% of recent work) Compiler-based security solutions (30% of output) Side-channel defense mechanisms (25% of research) Parser design and formal grammar synthesis (10% of contributions) Scientific achievements include: NSF CAREER Award Google Research Awards (2x) PLDI 2024 Best Paper James F. Will Career Development Professorship Outstanding Research Award at Penn State Ruth and Joel Spira Excellence in Teaching Award Dr. Tan actively contributes to academic communities through: DARPA ISAT study group membership Program committee roles (CGO 2024, ECOOP 2018, etc) Leadership in security research initiatives

• Computer Security
• Formal Methods
• Programming Languages
• +۲ مورد دیگر

Frank Chan is a Professor of Information Systems at ESSEC Business School in France, where he currently serves as Department Head of Information Systems, Decision Sciences and Statistics (2022-2025). He has been with ESSEC since 2013, progressing from Assistant Professor to Associate Professor and now Professor. His academic career focuses on the intersection of information systems, public administration, and organizational behavior. Dr. Chan earned his Ph.D. in Information Systems from Hong Kong University of Science and Technology (HKUST) in 2010 and completed his BBA in Information Systems and Finance from the same institution in 2003. His educational background provided the foundation for his research in technology implementation and electronic government. His research interests span electronic government, technology implementation, agile methodologies, and internet privacy. Dr. Chan's work examines how digital technologies transform public services, organizational processes, and citizen experiences. He investigates the human aspects of technology adoption, including leadership dynamics in agile teams, citizen satisfaction with e-government services, and privacy concerns in digital environments. His multidisciplinary approach combines insights from information systems, public administration, and organizational behavior. Analysis of Dr. Chan's publication record reveals a consistent focus on e-government systems and technology implementation, with increasing attention to agile development methodologies in recent years. His work demonstrates a progression from foundational technology adoption studies to more nuanced investigations of leadership dynamics, privacy concerns, and the societal impacts of digital initiatives. The interdisciplinary nature of his research bridges business, public administration, and technology domains. Pacific Asia Conference on Information Systems Best Associate Editor Award (2022) International Conference on Information Systems Outstanding Associate Editor Award (2019) MIS Quarterly Reviewer of the Year Award (2019) MIS Quarterly Reviewer of the Year Award (2018) Journal of Operations Management Ambassador Award (2017) Finalist for Journal of Operations Management Jack Meredith Best Paper Award (2012) As a Senior Editor for Information Systems Journal since 2021 (previously Associate Editor 2016-2020), Dr. Chan has significantly contributed to the academic community. He has served as Track Co-Chair for major conferences including International Conference on Information Systems and Pacific Asia Conference on Information Systems. His consulting work with United Nations ESCAP on digitalization of tax administrations in Asia demonstrates the real-world impact of his expertise. Dr. Chan teaches courses in Research Design, Quantitative Research Methods, and Digital Business at ESSEC.

• Electronic Government
• Technology Implementation
• Information Systems
• +۶ مورد دیگر

Bryan Parno is a Professor at Carnegie Mellon University in the Departments of Electrical & Computer Engineering and Computer Science . He is the recipient of the Kavčić-Moura Chair and leads the Secure Foundations Lab , focusing on end-to-end secure systems through formal verification. Research spans secure systems , applied cryptography , distributed systems , and zero-knowledge proofs Developed Verus (verified Rust systems) and Project Everest (verified HTTPS stack) Key contributions include Ironclad , Flicker , and Pinocchio , with impacts on Intel CPUs and Windows/iOS security models His work emphasizes open-source tools and reproducibility , often published in top venues like POPL, PLDI, and IEEE S&P. Recent projects address WebAssembly security and formal verification of complex distributed systems . Major Awards Jay Lepreau Best Paper Award (OSDI 2025) IEEE Cybersecurity Award for Practice (2024) Sloan Research Fellowship (2018) Test-of-Time Awards (IEEE S&P 2023, IEEE S&P 2020) Best Paper Awards at USENIX Security, OOPSLA, and PLDI

• Secure Systems
• Formal Software Verification
• Verifiable Computation
• +۷ مورد دیگر

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.

• Programming Languages
• Software Verification
• Program Synthesis
• +۴ مورد دیگر

Dr. Prasanth Valayamkunnath serves as Assistant Professor Grade I in the Department of Earth, Environmental and Sustainability Sciences at the Indian Institute of Science Education and Research Thiruvananthapuram (IISER TVM), having joined in December 2022 after working as an associate scientist at the National Center for Atmospheric Research (NCAR). His research integrates climate modeling, land-atmosphere interactions, and hydrology to address climate extremes and water security challenges. His educational background includes: Bachelor's in Land Surface Hydrology from Kerala Agricultural University Master's in Climate Change and Hydrology from IIT Kharagpur Ph.D. in Climate Science from Virginia Tech (2019) Valayamkunnath's research employs convection-permitting climate models and hydrology frameworks to investigate anthropogenic and natural influences on regional hydrology. Key focus areas include Indian Summer Monsoon dynamics, agricultural water management impacts, and flood modeling under climate change. His work bridges observational data with model development to enhance predictive capabilities for climate extremes. Analysis of his 2018-2023 publications reveals strong emphasis on land surface model development (particularly Noah-MP), with recurring themes in agricultural water management, tile drainage systems, and groundwater-surface water interactions. His research consistently connects climate modeling advancements with practical applications in food and water security. Scientific recognition includes: Ministry of Education STARS grant (2023) DST INSPIRE Faculty Fellowship (2022) Pratt Fellowship at Virginia Tech (2014) He actively recruits PhD students for projects in land-atmosphere interactions and climate change impacts on hydrometeorology, supported by his DST INSPIRE Fellowship and STARS grant. His research program focuses on developing modeling frameworks to assess climate resilience in Indian agricultural systems. Valayamkunnath founded and leads the Hydrometeorology and Climate Research Laboratory (HyCResLab) at IISER TVM, which specializes in convection-permitting climate simulations and integrated hydrology modeling for watershed-scale climate impact assessments.

• Climate Modeling
• Land-Atmosphere Interaction
• Hydrology
• +۴ مورد دیگر