جستجوی استاد راهنمای دانشگاهی

Mingsheng Yingمشاهده پروفایل

استاد

• Quantum Computation
• Quantum Programming
• Model-checking Quantum Systems
• +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.

• Language Acquisition
• Second Language Acquisition (SLA)
• Third Language Acquisition (L3)
• +۷ مورد دیگر

Pascale Trevisiol Okamura is an Associate Professor in Language Sciences and Language Teaching at Sorbonne Nouvelle University, affiliated with the DILTEC research team (EA 2288). Her primary role includes teaching language acquisition and foreign language didactics within the UFR of Literature, Linguistics, and Didactics (LLD). She co-heads the Master 2 program in Language Teaching (FLE/FLS) and holds administrative roles in departmental councils and educational committees. Education Background: Lecturer at Sorbonne Nouvelle University since 2015 Previously taught at Université de Poitiers (2010–2015) and Université Paris 8 (2007–2010) French teaching assistant at Hokkaido University, Japan Research Focus: Specializes in third language acquisition (L3), crosslinguistic influence, and the interface between language acquisition and didactics. Key themes include: Discourse construction in L3 French Input processing and initial language exposure Development of teaching materials for FLE Plurilingual practices among language teachers Current projects involve multilingualism in primary education, Tamil-speaking learners' L3 French acquisition, and reflexive training in research. Teaching & Supervision: Co-supervises doctoral research on topics such as L3 French acquisition in Chinese contexts, translinguistic discourse influences, and plurilingual teacher practices. Teaches advanced courses on language acquisition theories and FLE methodology. Labs/Teams: Member of the Second Language Acquisition Network (ReAL2) and part of the DILTEC team, focusing on language didactics and multilingualism research.

Conrad Wattمشاهده پروفایل

استادیار

• WebAssembly
• Formal Verification
• Programming Languages
• +۴ 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.

• 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.

• National and European Identities
• Social Identity Change
• Political Perceptions in Identity Formation
• +۵ مورد دیگر

Ronja Sczepanski is an Assistant Professor at the Centre for European Studies and Comparative Politics (CEE) at Sciences Po. Her research explores the intersection of national and European identities, focusing on how political perceptions, social sorting, and behavioral processes drive identity change. Specializes in identity formation through political events like referenda Analyzes neighborhood effects and ethnic diversity on identity dynamics Investigates political party framing of social groups Her recent work examines how differentiated integration impacts EU policy compliance and validates open-source machine translation for text analysis. She teaches courses on European integration at institutions including ETH Zurich and the University of Cologne. Recipient of the PolMeth Europe Best Poster Award (2023) Published in journals like Comparative Political Studies and European Union Politics

Delphine Allèsمشاهده پروفایل

استاد

• Southeast Asia and International Relations
• Global International Relations and Area Studies
• Religion and International Relations
• +۵ مورد دیگر

Delphine Allès is a University Professor at the National Institute of Oriental Languages and Civilizations (INALCO) in Paris, France, where she serves as Vice-President responsible for board of directors, organization and resources. She is a leading scholar in International Relations with a focus on Southeast Asia, particularly Indonesia, and specializes in non-Western approaches to international relations, religion in global politics, and Indo-Pacific security dynamics. Her research interests span multiple interconnected domains: Religion and International Relations Non-Western Approaches to International Relations Diplomacy, Security and Multilateral Cooperation in Southeast Asia (Indonesia / Indo-Pacific) Civilizational Narratives Global International Relations and Area Studies Allès's scholarly work demonstrates a consistent focus on decentralizing International Relations theory through empirical studies of Southeast Asian practices. Her recent publications examine the Indo-Pacific concept, religious diplomacy between Russia and Indonesia, and critiques of Western-centric security frameworks. She has pioneered research on how non-Western civilizations conceptualize international order, particularly through religious frameworks. Professor Allès serves on the editorial boards of multiple prestigious journals including European Journal of East Asian Affairs, Global: Jurnal politik internasional, and Archipel. She is also Scientific manager of the AMI-SHS DECRIPT program focused on crises and civilizational narratives. Her administrative leadership includes membership on the Scientific and Strategic Council of Pôle Asie (MEAE) and the board of the French Political Science Association. Previously, she directed the International Relations department at INALCO (2018-2023) and co-edited the journal Etudes internationales (2021-2024).

Joseph Salmonمشاهده پروفایل

پژوهشگر

• Machine Learning
• Optimization
• Data Science
• +۳ مورد دیگر

Joseph Salmon is a Senior Researcher at Inria (Team Iroko) in Montpellier, working with the Pl@nNet team. He previously served as a Full Professor at Université de Montpellier from 2018 to 2024 and was a Junior member of the Institut Universitaire de France (IUF) from 2021 to 2024. His research focuses on machine learning, optimization, and data science, with applications in citizen science and crowd-sourcing. He leads the doctoral program 'Statistics and Data Science' at Université de Montpellier. Education: Ph.D. in Statistics and Image Processing (2010) from Université Paris Diderot, under supervision of Dominique Picard and Erwan Le Pennec. Earlier roles include Assistant Professor at Telecom Paris (2012-2018), postdoctoral work at Duke University (2011-2012), and visiting positions at UW Statistics (2018) and the Simons Institute (2022). Research interests span isotonic regression, convex optimization algorithms (e.g., PAVA), statistical learning theory, and applications in environmental AI (Pl@ntNet). His work bridges theory and practice, emphasizing scalable algorithms for high-dimensional problems. Key contributions include advancements in PAVA convergence analysis, Slope penalty optimization, and peer-reviewed frameworks for crowdsourced data. Grants include ANR VITE (variable importance/explainability) and CaMeLOt (Cooperative Machine Learning Optimization). Labs/Teams: Active in Inria's Iroko team and collaborates with Pl@ntNet's AI development. Maintains the STATLEARN conference and ML-MTP initiative in Montpellier.

• Marketing
• Consumer Behavior
• Digital Marketing
• +۳ مورد دیگر

Amir SEPEHRI is an Assistant Professor in the Department of Marketing at ESSEC Business School, France. He holds a PhD in Marketing from Ivey Business School, Canada (2021). His research focuses on consumer behavior, digital marketing strategies, and text analysis, addressing topics such as online retailing dynamics, deception detection in communication, and the psychological impacts of narrative framing. He has developed tools like PassivePy for automated text analysis, and his work bridges consumer psychology with practical industry applications. Key research areas include the unintended consequences of product tagging in e-commerce, the role of information load in online talk popularity, and the strategic use of third-person narratives in fundraising. His findings have been published in journals like Journal of Personality and Social Psychology and Journal of Consumer Psychology . SEPEHRI also explores emerging technologies, such as voicebots' anthropomorphism and user engagement, as seen in his 2024 conference presentation. No scientific awards are listed, though his contributions to consumer behavior research are notable. He advises on grants related to text analytics and marketing strategies, though specific grant details are not provided. His academic activities include teaching marketing and consumer behavior courses, though course specifics are not detailed here.

Laurent Daudetمشاهده پروفایل

استاد

• Machine Learning
• Optics
• Signal Processing
• +۳ مورد دیگر

Laurent Daudet is a Professor of Physics at Université Paris Cité (on leave) and CTO & co-founder of LightOn, a startup developing optical computing technologies. His research spans signal processing, wave physics, and machine learning, with a focus on scalable AI solutions. He holds a PhD in Applied Mathematics from Marseille University and is a graduate of École Normale Supérieure in Paris. Research Interests: Laurent’s work bridges academia and industry, addressing challenges in massive-scale AI, optical computing, and hardware optimization. He leads cross-disciplinary R&D projects at LightOn, advancing technologies like the Optical Processing Unit (OPU) for low-power, parallel computing. Awards: Fellow of the Institut Universitaire de France Grants & Advising: Over 200 scientific publications and patents; collaborates globally with researchers and engineers. Former academic roles include Visiting Senior Lecturer at Queen Mary University of London and Visiting Professor at the National Institute for Informatics (Tokyo). Labs & Teams: Leads LightOn’s R&D initiatives, integrating optics, ML, electronics, and software engineering to tackle AI scalability challenges.

Gang (Gary) Tanمشاهده پروفایل

استاد

• Computer Security
• Formal Methods
• Programming Languages
• +۲ 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 Vision
• Natural Language Processing
• 3D Human Motion Synthesis
• +۳ مورد دیگر

Gül Varol is a permanent researcher at École des Ponts ParisTech's IMAGINE group, an ELLIS Scholar, and Guest Scientist at Max Planck Institute. She holds a PhD from Inria Paris/ENS with awards from ELLIS and AFRIF. Her academic service includes Program Chair at ECCV'24 and Area Chair roles at major conferences. Current affiliations: IMAGINE group (École des Ponts ParisTech), Max Planck Institute Previous roles: Postdoctoral researcher at University of Oxford Her research focuses on vision-language applications, particularly in 3D human motion synthesis, sign language technology, and audio description generation. Key techniques include text-conditioned diffusion models, temporal context modeling, and synthetic data utilization. Scientific contributions recognized through: Google Research Scholar award (2023) ELLIS PhD Award (2020) AFRIF PhD thesis award (2020) Best application paper at ACCV'20 Recent publications demonstrate expertise in: Text-driven 3D motion editing (MotionFix, 2024) Cross-dataset generalization studies (TMR++, 2024) Temporal action composition frameworks (TEACH, 2022) Sign language dense annotation methods (BOBSL, 2022) Zero-shot audio description generation (AutoAD-Zero, 2024) She actively contributes to dataset development including BOBSL (British Sign Language corpus) and SURREACT synthetic action dataset, while pioneering new evaluation metrics for audio description quality and motion retrieval benchmarks.

Benoît Sagotمشاهده پروفایل

پژوهشگر

• Natural Language Processing
• Computational Linguistics
• Machine Translation
• +۷ مورد دیگر

Benoît Sagot is a Senior Researcher in Natural Language Processing and Computational Linguistics at Inria , currently holding the 2023-2024 Informatics and Digital Sciences Annual Chair at Collège de France. He directs the ALMAnaCH research team and contributes to the PRAIRIE Institute for AI research. Research Focus: His work spans neural language models, machine translation, text simplification, multimodal NLP, and lexical resource development for French and low-resource languages. He explores computational morphology, etymology, and historical linguistics, with applications in opinion mining and computational oenology. Recent Articles emphasize language model interpretability, cross-lingual transfer, and multimodal integration (speech, image). Tools & Resources: He has developed morphological lexicons (Le fff, Alexina), corpora (OSCAR, CAMEMBERT), and parsing pipelines (SxPipe). Projects: Involved in initiatives like ANR BASNUM (Furetière's dictionary digitization) and 3IA PRAIRIE (AI research). His career combines foundational work in syntactic analysis with evolving deep learning approaches.

• Social Stratification
• Social Demography
• Health and Wellbeing
• +۳ مورد دیگر

Patrick Präg serves as an Associate Professor of Sociology at CREST/ENSAE (part of the Institut Polytechnique de Paris) and holds an associate faculty position at Oxford University’s Nuffield College. His research integrates quantitative methods and survey data to address social stratification, demography, health, and work-family dynamics. He earned his PhD in Sociology from the ICS/University of Groningen in 2015. His work has been recognized with the Aage B. Sørensen Award (2014). Education: PhD in Sociology, ICS/University of Groningen (2015) Master’s Thesis: Nonresponse to Items on Self-Reported Delinquency, University of Hamburg Research Interests: Patrick’s work explores the interplay between social structure and individual wellbeing. Key topics include: Intergenerational mobility and health outcomes Work-life balance and gender inequalities Pandemic-driven societal changes Algorithmic bias in social science Subjective socioeconomic status measurement Grants & Collaborations: He contributed to the EU-funded ‘Families and Societies’ project, producing deliverables on assisted reproduction and demographic consequences. His research often involves cross-national datasets and methodological innovation, with replication materials shared via Open Science Framework (OSF). Labs & Teams: He is affiliated with CREST (Center for Research in Economics and Statistics) and collaborates with institutions like the Max Planck Institute for Demographic Research (MPIDR) and the Nuffield College. His work frequently intersects with interdisciplinary teams addressing health, education, and labor market policies.

Bernhard Rumpeمشاهده پروفایل

استاد

• Software Engineering
• Model-Based Software Engineering (MBSE)
• Domain-Specific Languages (DSLs)
• +۱۶ مورد دیگر

Bernhard Rumpe is a Professor and Chair of Software Engineering at the Department of Computer Science 3, RWTH Aachen University, Germany. He leads a research group focused on model-based software engineering, domain-specific languages, and digital twins, with strong industrial collaborations and applications in embedded systems, AI, IoT, and autonomous vehicles. His research centers on improving software development through model-driven engineering, generative techniques, and formal modeling using UML, SysML, and the MontiCore language workbench. Key interests include digital twins, variability modeling, model composition, and the integration of cyber-physical systems with information systems. The recent publications highlight a consistent focus on model-driven digitalization, language workbenches, and system integration. Trends show increasing emphasis on digital twins in manufacturing and societal systems, formal verification of model transformations, and educational applications of model-driven low-code platforms. His work bridges theoretical foundations with industrial applicability. Keynote Speaker, OOPSLE 2025 General Chair, GPCE 2023 Session Chair, MODELS 2020 Program Committee Member, SLE, GPCE, ICSE, ECMFA He advises master’s and doctoral students and leads a vibrant research team that has successfully executed over 100 research projects. His group develops foundational tools like MontiCore and applies them in industrial contexts, contributing to software quality and developer efficiency. No formal grants are listed, but sustained project funding is evident. He is involved in several research labs and teams centered around the Software Engineering Chair at RWTH Aachen, focusing on language workbenches, model-driven development, and digital twin systems. The team actively contributes to open research through publications, tools, and industrial partnerships.

Pierre-Henri Parisمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Knowledge Graphs
• Information Extraction
• +۲ مورد دیگر

Pierre-Henri Paris is an Associate Professor (Maître de Conférences) at Paris-Saclay University since September 2024. Previously, he worked as a Postdoctoral Researcher at Telecom Paris (Institut Polytechnique de Paris) from September 2020 to August 2024. His academic journey includes a PhD in Artificial Intelligence from Sorbonne University and CNAM (Conservatoire National des Arts et Métiers) completed in 2020. Education: PhD in Artificial Intelligence, 2020, Sorbonne University and CNAM M.Sc. in Artificial Intelligence, 2016, CNAM M.Sc. in Mathematics, 2008, CY Cergy Paris University (incomplete) Pierre-Henri Paris's research focuses on the intersection of artificial intelligence, knowledge representation, and natural language processing. His work particularly emphasizes knowledge graphs, entity linking, and data quality. He has made significant contributions to projects like YAGO 4.5, which enhances knowledge bases with cleaner, logically consistent structures, and MAFALDA, a benchmark for fallacy classification. His research often bridges theoretical foundations with practical applications, particularly in how knowledge can be effectively represented, extracted, and utilized in complex systems. His recent publications reveal a strong focus on knowledge graph enhancement, semantic representation, and natural language understanding. The work on YAGO 4.5 demonstrates his commitment to creating more robust knowledge bases, while MAFALDA shows his interest in the intersection of language understanding and logical reasoning. His research trajectory indicates a consistent exploration of how structured knowledge can be integrated with linguistic analysis to create more intelligent systems. Advising: PhD students: Simon Coumes (2022-), Chadi Helwe (2022-2024), François Amat (2022-) Master's students: Syrine El Aoud (2021), Ayoub Mountassir (2013-2015) Bachelor's students: Khalil Halloul (2013-2014) Pierre-Henri Paris is actively involved in teaching at Paris-Saclay University, where he instructs courses including Introduction to Machine Learning, Introduction to Neural Networks, Algorithms for Data Science, Databases, and Data Warehousing. His teaching reflects his research expertise, providing students with both theoretical foundations and practical applications in artificial intelligence and data science.