جستجوی استاد راهنمای دانشگاهی

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

Pascal PAILLE is Full Professor in the People & Organisations department at NEOMA Business School , France. Previously, he served as Full Professor and PhD Program Director at Laval University in Canada. Education Doctorat en Sciences de gestion Habilitation à Diriger des Recherches en Sciences humaines Research Interests Professor PAILLE’s scholarship centers on the micro-level greening of the workplace . He investigates how individual behaviors, human resource systems, and organizational contexts interact to foster environmental sustainability. His work integrates quantitative methods with theories from green HRM , organizational behavior , and environmental psychology to understand what drives employees to adopt pro-environmental actions on and off the job. Recent Research Trajectory Across more than 80 peer-reviewed articles since 2015, PAILLE has consistently advanced the field of green human resource management . His 2024 publications reveal a dual focus: (1) refining meta-analytic insights on the link between green HR practices and individual environmental performance, and (2) deploying fuzzy-set and configurational methods to uncover complex causal recipes that explain green behaviors in family firms and entrepreneurial settings. A growing sub-stream explores the emotional side of sustainability, including workplace eco-anxiety and the supportive mechanisms that mitigate its negative consequences. Books & Scholarly Recognition La gestion environnementale des ressources humaines (2024, EMS) Green Behaviors in the Workplace (2022, Palgrave Macmillan) Greening the Workplace: Theories, Methods, and Research (2020, Palgrave Macmillan) Le leadership machiavélique (2018, PUL) La fidélisation des ressources humaines (2004, Economica) Changement organisationnel et mobilisation des ressources humaines (2003, L’Harmattan) Teaching & Doctoral Supervision At NEOMA, Professor PAILLE teaches green human resource management , sustainable HRM , and organizational theory . During his tenure at Laval University, he directed the PhD program, indicating substantial experience in doctoral advising and mentorship, although specific student names are not provided in the source material.

• Green Human Resource Management
• Sustainable HRM
• Environmental Behavior in Organizations
• +۲ مورد دیگر

Patrick VALEAU is a Full Professor specializing in Human Resources Management at the University of Rennes, affiliated with the CREM UMR CNRS 6211 research center. He serves as Director of Studies for the DU Recherche en Management program and contributes to the Formation continue initiatives. His research focuses on HR practices in nonprofit organizations (NPOs), environmental management within organizations, entrepreneurial persistence, and the intersection of organizational behavior and sustainability. Key research themes include mission-based HR strategies in NPOs, green HR practices for environmental performance, and the role of commitment in sustaining ventures during decline. He has also explored governance structures in religious associations and pandemic-era workplace safety behaviors. His work integrates qualitative and quantitative methods, including fuzzy-set qualitative comparative analysis (fsQCA) and longitudinal studies. Recent publications highlight innovations in HRM for environmental initiatives, the mediating effects of perceived organizational support, and the strategic orientations influencing high-commitment HR adoption. His research often bridges theory and practice, offering actionable insights for nonprofit governance, sustainable business practices, and entrepreneurial resilience. Patrick VALEAU collaborates with international scholars and contributes to journals such as Employee Relations , Journal of Environmental Planning and Management , and Nonprofit and Voluntary Sector Quarterly . His work addresses contemporary challenges in organizational management, emphasizing adaptability and ethical practices across diverse sectors.

• Human Resources Management
• Nonprofit Organizations
• Environmental Management
• +۳ مورد دیگر

Patrice Terrier is a Professor of Cognitive Psychology and Ergonomics at Toulouse Jean Jaurès University since 2008, affiliated with the Cognition, Languages, Language, Ergonomics (CLLE) laboratory. He has held significant leadership roles including Head of the 'compatibility between human and artificial systems' axis (2008-2014), Co-head of the 'cognitive ergonomics: memory, aging, rhythms' axis (2014-2016), Deputy Director of the doctoral school of aeronautics and astronautics site (2010-2015), and Scientific Director at the National Research Agency (2014-2017). He was appointed to the National Council of Universities (16th section) from 2012-2015 and has represented UT2J on various steering committees including the Graduate School ANITI and Toulouse Hybridation Education Campus projects. Terrier's research focuses on memory phenomena and consciousness in relation to person-system interaction. His work conceptualizes memory as a set of procedures and operations rather than a storage place, employing frameworks such as the attributive approach to memory, appropriate processing for transfer, and dual conceptions of memory processes. His research spans diverse application contexts including air traffic control, nuclear power operations, human-machine dialogue, internet information retrieval, risk perception, and decision-making problems. He has developed significant expertise in distinguishing between implicit (automatic) and explicit (controlled) memory use and characterizing gist versus verbatim representations. His publication record shows consistent output across cognitive psychology, ergonomics, and human-computer interaction, with recent work focusing on conspiracy theories, truth effects, humor appreciation, and unconscious thought processes in decision making. His research demonstrates strong interdisciplinary connections between cognitive theory and practical applications in complex systems. Terrier has been actively involved in academic governance, serving on the training commission of university life (2018-2022), as vice-president delegated to digital technology development (2019-2022), and as an elected member of the CFVU. He has contributed to numerous research groups including the European Association of Cognitive Ergonomics and has been an associate editor for the International Journal of Human Factors and Ergonomics since 2018. He has supervised 10 doctoral theses since qualifying to direct research in 2006, with his work supported by various research grants through the National Research Agency where he served as a scientific manager. His laboratory work within CLLE focuses on cognition in complex situations, particularly examining how memory processes operate in real-world contexts.

• Cognitive Psychology
• Ergonomics
• Human-Computer Interaction
• +۴ مورد دیگر

Allel Hadjali is a Full Professor in Computer Science specializing in Data Engineering at ISAE-ENSMA (École Nationale Supérieure de Mécanique et d'Aérotechnique) in Poitiers, France. He is affiliated with the Laboratory LIAS (Laboratoire d'Ingénierie des Applications de la Connaissance et des Systèmes) at ISAE-ENSMA. His academic career includes progression from Associate Professor to his current Full Professor position, with extensive teaching experience across multiple computer science domains. Professor Hadjali's research falls within the data science domain, with particular focus on Exploitation, Extraction, and Recommendation (E2R). His work applies Computational Intelligence and Soft Computing techniques to massive data exploitation and analysis, including flexible querying approaches (Skyline, Gradual, and Bipolar queries), modeling and querying uncertain/incomplete data, cooperative answering techniques, and data reduction through linguistic summaries. He also conducts research in recommendation systems (learning-based and group recommendation) and extraction techniques (mining gradual patterns), along with related interests in data quality, intelligent systems, and crowdsourced data management. His publication record demonstrates consistent contributions to top-tier journals and conferences, with recent work focusing on skyline query processing, uncertain data management, RDF knowledge bases, and explainable AI. His research shows a clear trajectory from foundational work in fuzzy logic and uncertain databases toward more applied research in semantic web technologies and machine learning explainability. Professor Hadjali serves on the editorial boards of several prestigious journals including the Journal of Smart Environments and Green Computing, Sensors Journal, and the Universal Journal of Aeronautics and Aerospace Research. He has also organized special issues on topics such as uncertainty in cloud computing and managing uncertain data. At ISAE-ENSMA, Professor Hadjali teaches courses including Formal aspects of software engineering, Language interpretations and compilation, Programming languages, and Data management and exploitation. Previously as an Associate Professor, he taught courses on object modeling, distributed algorithms, operating systems, and advanced databases focusing on preferences and uncertainty. He leads the Data Engineering team within the Laboratory LIAS, which focuses on developing computational intelligence approaches for modern data challenges. His current projects include work on data quality (QDoSSI project funded by CNRS Mastodons 2016-2018) and research actions in GDR MADICS 2018 related to scientific data quality.

• Data Science
• Computational Intelligence
• Soft Computing
• +۱۲ مورد دیگر

Isabelle Bloch is a full Professor at Télécom Paris (Institut Polytechnique de Paris) and Emeritus Professor at the University of Bordeaux . She heads the Image, Modeling, Analysis, Geometry, Synthesis (IMAGES) research team within the Information Processing and Communication Laboratory (LTCI) in the Image, Data, Signal (IDS) Department . Education & Affiliations Professor – Télécom Paris, Institut Polytechnique de Paris (current) Professeure Émérite – University of Bordeaux (honorary) Research Interests Her work lies at the intersection of computer science, applied mathematics and medicine . Core themes include mathematical morphology , fuzzy and bipolar logics , 3-D image interpretation , discrete 3-D geometry & topology , information fusion , structural pattern recognition , spatial reasoning and medical imaging . Recent projects extend these concepts to explainable AI , argumentation theory , computational musicology and robotic surgery guidance . Scientific Awards Blondel Medal (2008) – awarded by the French Electrical & Electronics Engineering Society to outstanding young scientists. Grants & Collaborative Projects While specific grant numbers are not listed in the text, Prof. Bloch coordinates and participates in large-scale interdisciplinary projects funded by national (ANR) and European programs, spanning medical AI, pediatric oncology imaging, neuro-informatics and ethical AI. Labs & Teams She leads the IMAGES team (≈ 25 researchers) inside the LTCI – a joint research unit of Télécom Paris and CNRS. The group develops theory and open-source software in mathematical morphology, deep learning and symbolic AI, and collaborates closely with clinical partners at Necker–Enfants Malades Hospital, AP-HP and Gustave Roussy.

• Mathematical morphology
• Fuzzy set theory and bipolar fuzzy sets
• 3D image interpretation and computer vision
• +۷ مورد دیگر

Thomas Le Barbanchon is a Professor of Economics at Bocconi University, holding the Rodolfo Debenedetti Chair in Labor Economics since 2024. He serves as Director of the research center IGIER since January 2025 and maintains affiliations with CEPR, CREST, J-PAL, IZA, and IFS. His research focuses on labor economics, public finance, and econometrics, with significant contributions to understanding unemployment insurance, job search behavior, gender disparities, and labor market responses to pandemics. PhD in Economics from École Polytechnique (CREST-ENSAE), France M.Sc. in Economics from Universitat Pompeu Fabra, Spain His research explores labor economics through empirical and methodological lenses. Key areas include unemployment insurance effects , job search dynamics , and gender wage gap mechanisms . Recent work investigates AI-driven job matching, hiring difficulties, and wage-setting through his ERC-funded WeSET project (2025-2030). Articles span top journals like American Economic Journal: Applied Economics, Quarterly Journal of Economics, and Journal of Public Economics. Scientific awards include the 2022 Bocconi Impact Award , ERC Consolidator Grant (2024-2029) , and ERC Starting Grant (2018-2023) . He has advised numerous PhD students and led institutional roles at Bocconi, including hiring committees and program leadership. His work bridges rigorous econometric methods with real-world policy evaluation for France Travail, public employment service reforms, and education initiatives.

• Labor Economics
• Public Finance
• Econometrics
• +۵ مورد دیگر

Frédéric Pichon is a Full Professor at Artois University's Laboratory of Computer Engineering and Automation of Artois (LGI2A), part of the Faculty of Applied Sciences in Béthune, France. He holds a Ph.D. in Information and Communication Systems (2009) and an H.D.R. (2018) from Artois University. His research focuses on uncertain reasoning, information fusion (particularly belief functions theory), and machine learning applications in decision-making under uncertainty. Education: B.Eng. (Hons) in Computer Networks and Distributed Systems, Edinburgh Napier University, 2003 M.Sc. in Information Technology, Aalborg University Esbjerg, 2005 Ph.D., University of Technology of Compiègne, 2009 H.D.R., Artois University, 2018 Research Interests: Belief functions theory and applications Optimization under severe uncertainty Machine learning with uncertain data Information fusion for decision support Articles Trends: Recent work emphasizes belief function-based solutions for optimization problems (e.g., shortest path, vehicle routing) and deep learning integration with uncertainty quantification. Early-career contributions include foundational work on Dempster-Shafer theory and conflict analysis. Awards: Notable recognitions include the IJAR Early Career Researcher Award (2022), multiple best paper awards at LFA and BELIEF conferences, and distinctions for student research supervision. Advising & Grants: Supervised 9 PhD students (3 in progress). Active in organizing international conferences (BELIEF, LFA) and editorial roles (Area Editor for International Journal of Approximate Reasoning). Research spans theoretical advancements and applied projects in logistics, image processing, and simulation. Labs/Teams: Core member of LGI2A, collaborating with institutions like Heudiasyc and IBISC labs on uncertainty modeling and fusion systems.

• Uncertain Reasoning
• Information Fusion
• Machine Learning
• +۳ مورد دیگر

Nozha Boujemaa is a Research Director at Inria and Director of DATAIA Institute, leading projects in Data Sciences, Algorithmic Transparency, and Societal Impact. She co-founded the Digital Society Institute (ISN) and serves as a Senior Scientific Advisor for AI initiatives. Expert in Large Scale Multimedia Content Search, Pattern Recognition, and Machine Learning Developed methods for visual content enrichment, interactive retrieval, and satellite image analysis Scientific leader of Pl@ntNet (plant identification), CHORUS (multimedia search engines), VITALAS, MUSCLE, and TRENDS projects Her research spans Multimedia Retrieval , Big Data Applications , and Algorithmic Transparency , with over 150 publications. She has supervised 25+ PhD/Master's students and organized conferences like ACM Multimedia 2013 and European Big Data Value Forum 2017. Key scientific awards include: Knight of the National Order of Merit (France) She has contributed to international projects (NSF, European Commission), served on editorial boards for Multimedia Tools and Applications , and co-chaired workshops on visual digital libraries and AI ethics. Her work impacts web search, cybersecurity, biodiversity, and earth observation.

• Multimedia Content Search
• Pattern Recognition
• Machine Learning
• +۳ مورد دیگر

Joseph SIANI is an Associate Professor at IÉSEG School of Management in France, where he serves as Track Coordinator for the Quantitative Methods program. He holds a Ph.D. in Economics from the University of Caen Basse-Normandie, France. His professional experience includes roles as a Professor at Ecole de Management de Normandie (2014–2015), University of Le Havre (2014–2016), and University of Caen Basse-Normandie (2011–2014). He is a member of LEM (Laboratoire d'Economie Moderne). His research focuses on Economics, Quantitative Methods, and Political Philosophy. Key areas include voting theory, game theory applications, poverty analysis, and development economics. His work often employs advanced econometric techniques such as panel data analysis and cointegration methods. Teaching responsibilities span advanced quantitative methods, optimization, and business games across undergraduate and graduate programs. He contributes to courses like 'Advanced Quantitative Methods' and 'Mathematics Calculus' at the undergraduate level, and 'Business Game' in the Master’s program. Dr. SIANI’s publications in peer-reviewed journals address topics such as power indices in voting systems, remittances’ impact on human development, and multidimensional poverty measurement. His research bridges theoretical frameworks with empirical analysis, particularly in development economics and social choice theory.

• Economics
• Quantitative Methods
• Political Philosophy

Gilles MAURIS is a Lecturer at Polytech Annecy-Chambéry, part of Savoie Mont-Blanc University. He holds a position in the IUT Annecy department of Electrical Engineering and Industrial Computing. His research focuses on uncertainty representation using possibility theory and fuzzy logic applications in information fusion. He has supervised PhD theses including Fanny Pagnier's work on avalanche risk decision-making and Charles Lesniewska-Choquet's study on stochastic processes. He participates in major research projects like the INTERREG Franco-Swiss CIME project (2018-2022) and previously led the FUI MISAC Project (2011-2015) as LISTIC's Scientific Manager. His teaching responsibilities include courses in Signal Mathematics, Probability and Statistics, and Electronics at IUT Annecy. He serves as Head of adapted sections (sports and music) at IUT Annecy and has organized conferences including the 2017 IEEE CIVEMSA as Chair of the Organizing Committee. He contributes to academic评审 for journals like IEEE Trans. on Fuzzy Systems and Fuzzy Sets and Systems.

• Uncertainty representation (possibility theory)
• Fuzzy methods in information fusion
• Signal Mathematics
• +۵ مورد دیگر

Thierry Denoeux is a Full Professor (Exceptional Class) at the Department of Information Processing Engineering, Université de Technologie de Compiègne, France. He holds senior membership in the Institut Universitaire de France (since 2019, reconducted 2024) and serves as Editor-in-Chief of the International Journal of Approximate Reasoning . His research focuses on reasoning and decision-making under uncertainty, with major contributions to the theory of belief functions and its applications in machine learning, statistical inference, and information fusion. Denoeux has authored over 350 publications and supervised 30+ PhD theses. Education : Graduated from École nationale des ponts et chaussées (PhD from same institution). Roles : President of the Belief Functions and Applications Society, Associate Editor of Fuzzy Sets and Systems , and other journals. His research interests emphasize managing uncertainty in intelligent systems, with applications in medical imaging, data mining, and econometrics. Recent work includes evidential machine learning frameworks, uncertainty quantification in neural networks, and fusion of multimodal medical data. Publications span topics like evidential clustering, fusion of uncertain data, and applications in hydrology and materials science. Over 150 journal articles and conference papers since 2020 alone reflect his prolific output in belief functions theory and its practical implementations. Awards : Senior IUF Membership (2019–present). Grants/Advising : Extensive supervisory experience in PhD and postdoctoral research, with notable contributions to interdisciplinary projects involving healthcare and environmental applications. Denoeux collaborates internationally, leading initiatives in evidential AI and uncertainty-aware decision systems through his editorial and society leadership roles.

• Reasoning under Uncertainty
• Decision-Making under Uncertainty
• Belief Functions Theory
• +۵ مورد دیگر

Sabine FRITTELLA is a Lecturer with HDR at INSA Centre Val de Loire, affiliated with the Laboratoire d'Informatique Fondamentale (LIFO). She is an active researcher in theoretical computer science, focusing on logic and privacy-preserving technologies. Her work bridges formal methods and practical applications in data privacy and reasoning under uncertainty. Her primary research areas include paraconsistent logic, Dempster-Shafer theory, and privacy-enhancing technologies. She investigates how to model contradiction and uncertainty in evidence, and develops formal frameworks for data minimization and informed consent in administrative forms. Her work often combines logical foundations with real-world privacy challenges. Analysis of her recent publications (2020-2025) reveals a strong focus on privacy-preserving technologies, particularly data minimization and consent management, alongside theoretical work in non-classical logics. She has made significant contributions to paraconsistent reasoning and the application of belief function theory to concept representation. Her research consistently addresses the challenge of handling inconsistent information in practical settings. She is a member of the LIFO laboratory (Laboratoire d'Informatique Fondamentale d'Orléans), a joint research unit of the University of Orléans and INSA Centre Val de Loire, where she collaborates on projects in theoretical computer science and its applications.

• Theoretical Computer Science
• Logic in Computer Science
• Artificial Intelligence
• +۳ مورد دیگر

André Bigand is a Lecturer at Université du Littoral Côte d'Opale (ULCO) and leads the IMAP research team. His work focuses on uncertainty modeling with fuzzy sets, image processing, and deep learning applications in art analysis. 1981: Aggregation of Applied Physics 1987: DEA in Electronics-Instrumentation (Univ. Paris6) 1993: Doctorate in Electronics (Univ. Paris6) 2001: Authorization to Direct Research (ULCO) His research spans image processing , deep learning , and time series analysis , with applications in phytoplankton dynamics , face detection in paintings , and explainable AI . He has published 11 international peer-reviewed articles and 41 communications with proceedings. Bigand collaborates with international institutions like the University of Waterloo (Canada) and the Lebanese University. He has served as Jury President for the 'Electronics-Instrumentation' Master's Degree and co-led ERASMUS+ programs. His recent publications emphasize visual art analysis , plant disease detection , and environmental time series imputation . He supervises 2 ongoing theses and has directed 5 thesis projects.

• Uncertainty Modeling
• Fuzzy Sets
• Image Processing
• +۴ مورد دیگر

Didier DUMUR is a Professor and Dean of the Engineering curriculum at CentraleSupélec. He is affiliated with the Laboratoire des signaux et systèmes (L2S) and specializes in control systems, robotics, and bioprocess engineering. His research focuses on advanced control strategies for complex systems, including robotic manipulators, bioreactors, and energy systems. He has contributed to over 100 publications, patents, and book chapters, emphasizing robust control, fault-tolerant systems, and model predictive control applications. His work bridges academic research and industrial challenges, such as optimizing renewable energy systems and improving manufacturing precision through advanced control methodologies. Education details are not explicitly listed, but his extensive publications indicate expertise in systems engineering and automation. He chairs initiatives like the COMEDY and MODESTY groups at L2S, addressing dynamical systems modeling and control. His recent work (2022–2025) explores biomethane productivity optimization, collaborative robotics evaluation, and spacecraft vibration control, reflecting a commitment to cutting-edge applications in control engineering. Didier Dumur’s academic leadership includes curriculum development for complex systems education, as highlighted in his 2019 chapter on CentraleSupélec’s engineering programs. He collaborates with institutions globally, evidenced by international conference participations and co-authored works with researchers across Europe and Latin America.

• Control Systems
• Robotics
• Bioprocess Control
• +۴ مورد دیگر