جستجوی استاد راهنمای دانشگاهی

• Knowledge Management
• Uncertainty Management
• Belief Function Theory
• +۴ مورد دیگر

BEN AYED Safa is a Researcher-Lecturer at CESI, affiliated with the LINEACT research group and the Department of Engineering and Numerical Tools. Their work focuses on knowledge management, uncertainty modeling under belief function theory, decision support systems, and predictive maintenance. They hold dual PhDs in Computer and Automatic Engineering (Artois University, France, 2020) and Computer Science applied to Management (University of Tunis, Tunisia, 2020), along with advanced degrees in Business Intelligence and Data Mining. Currently collaborating on the ANR SCOPES project (2022-2025), they teach modules in computer science, networks, and electrical engineering at undergraduate levels. Their research emphasizes CBR systems maintenance, evidential fusion methods, and AI-driven predictive analytics. Recent work includes advancements in collaborative perception modeling and uncertainty quantification in industrial systems. Education : PhD in Computer and Automatic Engineering (LGI2A, Artois University, 2020) PhD in Computer Science applied to Management (LARODEC, University of Tunis, 2020) Master of Research in Business Intelligence (Institut Supérieur de Gestion, Tunisia, 2017) Master in Data Mining & Knowledge Management (Polytech'Nantes, France, 2017) Bachelor in Computer Science applied to Management (Institut Supérieur de Gestion, Tunisia, 2015) Research Interests : Belief Function Theory applications in CBR systems Evidential clustering and policy design Predictive maintenance frameworks Machine learning for uncertainty quantification Information fusion in autonomous systems Key Contributions : Recent work bridges belief function theory with industrial AI challenges, including energy forecasting, turbofan prognosis, and ITER divertor modeling. Their methods enhance case-base maintenance through evidential integration, addressing dynamic uncertainty in real-world systems. Grants & Supervision : Participating in the ANR SCOPES project (2022-2025) and planning thesis supervision by 2025. Their research spans academic-industrial collaboration in PHM frameworks and smart building analytics.

• Machine Learning
• Signal Processing
• Speech Enhancement
• +۴ مورد دیگر

Mostafa Sadeghi is a Research Fellow in the PERCEPTION team at Inria Grenoble Rhône-Alpes, where he has been conducting research since August 2018. His work bridges machine learning and signal processing with a strong emphasis on developing advanced speech enhancement techniques. Dr. Sadeghi's primary research interests include: Unsupervised probabilistic generative models, particularly variational autoencoders (VAEs) Audio-visual speech enhancement and separation systems Diffusion-based generative models for speech processing 3D face alignment and frontalization techniques for visual speech processing End-to-end multichannel speech processing architectures Analysis of his recent publications reveals a clear trajectory toward increasingly sophisticated generative models for speech processing. His work has evolved from traditional VAE approaches to cutting-edge diffusion models, with growing emphasis on multimodal (audio-visual) integration. A significant portion of his research addresses real-world challenges in conversational speech enhancement, meeting transcription, and multi-speaker environments, as evidenced by his contributions to the CHiME challenges. Dr. Sadeghi maintains an active research profile with consistent publication output in top-tier venues including IEEE ICASSP, INTERSPEECH, and IEEE Transactions on Signal Processing. His collaborative network spans multiple institutions, with frequent co-authorship with researchers from INRIA and other European research centers.

• Translation Studies
• Sociolinguistics
• Urban Youth Speech Translation
• +۷ مورد دیگر

Tiffane Levick is a Lecturer in Translation Studies at the University of Toulouse-Jean Jaurès, affiliated with the Center for Anglophone Studies (CAS). She teaches translation (theme and version) at undergraduate and master’s levels and specializes in the translation of urban youth speech, sociolinguistics, gender, and pedagogy. She co-founded the research network 'Translating Minority Voices' and holds a doctorate from Sorbonne Nouvelle University-Paris 3. Education: Doctorate (2018): 'Orality and Universality, in Search of a Global Youth Speech in Translation', Sorbonne Nouvelle University-Paris 3, supervised by Clíona Ní Ríordáin. Research Interests: Her work centers on the translation of non-standard language, particularly urban youth speech, creole, and gender-inclusive forms. She explores how sociolinguistic variation, cultural references, and multimodal elements (such as music and audiovisual media) are rendered across languages. Her research also addresses pedagogical approaches to teaching sensitive topics like non-binary language and marginalized voices in translation. Publications Trends: Her recent scholarly output spans book chapters, journal articles, and conference papers, with a strong focus on the intersection of translation, identity, and cultural representation. Key themes include the translation of slang, creole, rap, and inclusive language, often analyzing contemporary French and Anglophone literature and media. Scientific Awards: 2021 Gulf Coast Prize in Translation (for an excerpt from Sofia Aouine's Rhapsodie des oubliés ) Advising and Grants: While no specific students or grants are listed, she actively mentors through her teaching and co-supervises collaborative translation projects. She has co-edited a volume on teaching translation in Francophone contexts and leads experimental bilingual writing workshops that integrate translation and creative writing. Labs and Teams: She is a core member of the Center for Anglophone Studies (CAS) and co-founded the research network 'Translating Minority Voices' (in collaboration with PRISMES, Sorbonne Nouvelle). She also organizes and participates in interdisciplinary research seminars and conferences on translation, sociolinguistics, and minority representation.

Massimiliano Todiscoمشاهده پروفایل

مدرس

• Voice Biometrics
• Automatic Speaker Verification
• Spoofing Detection
• +۷ مورد دیگر

Massimiliano Todisco is a Lecturer in the Digital Security department at EURECOM, a leading research institute in digital sciences. His work is centered on enhancing the security and privacy of voice biometric systems, with a strong emphasis on detecting spoofing, deepfakes, and adversarial attacks in automatic speaker verification. His research interests include voice biometrics, adversarial machine learning, spoofing countermeasures, deepfake detection, and privacy-preserving speech technologies. He actively contributes to major international challenges such as ASVspoof and VoicePrivacy, driving innovation in secure and explainable biometric systems. The recent publications highlight a consistent focus on biometric security, with trends in adversarial attack modeling, voice anonymization, and large-scale evaluation of spoofing detection systems. His work bridges signal processing, machine learning, and cybersecurity. NeurIPS 2023 Scholar Award for “StressID: a multimodal dataset for stress identification” Best Paper Award at IBERSPEECH 2022 Best Paper Award in Computer Speech & Language (2017) Best Paper Award at ODYSSEY 2016 Todisco advises PhD students, as evidenced by his HDR (Habilitation à Diriger des Recherches) obtained in 2025, which qualifies him to supervise doctoral research. He has been involved in multiple collaborative research projects and challenges, including ASVspoof and VoicePrivacy, though specific grant details are not listed. His research is highly collaborative, often co-authored with researchers from institutions across Europe and beyond. He is a core member of the Digital Security research group at EURECOM, which serves as his primary research team and laboratory environment. This group focuses on cutting-edge challenges in digital security, particularly in biometrics and privacy.

Fabrice MUHLENBACHمشاهده پروفایل

مدرس

• Artificial Intelligence
• Data Mining
• Text Mining
• +۴ مورد دیگر

Fabrice MUHLENBACH is a Lecturer in Computer Science at Jean Monnet University of Saint-Étienne, where he has been working since September 2003. He conducts his research within the Hubert Curien Laboratory (UMR CNRS 5516), specifically as a member of the Connected Intelligence research team. His academic background is multidisciplinary, combining computer science with cognitive psychology and cognitive sciences. MUHLENBACH's research focuses on artificial intelligence, particularly in improving recommendation processes from intelligent systems. His work addresses ethical considerations in AI and explores ways to escape the "filter bubbles" commonly encountered in recommendation systems. He has developed innovative approaches to recommendation systems that consider complementary cultural forms when users become saturated with similar content. His research also investigates the potential usefulness of knowledge from scientific disciplines outside one's expertise. His publications demonstrate expertise in data mining, text mining, recommendation systems, and AI ethics. His work spans from theoretical foundations to practical applications, with notable contributions in clustering algorithms, semantic search, and health informatics. His research has practical implications, as evidenced by the industrial patent filed for a method of automatic multimedia content selection. Best Paper Award at ADMA 2017 conference Patent FR3046269 for "Method for automatic selection of multimedia content in a database" (2017) Contributions to Encyclopedia of Social Network Analysis and Mining (2014, 2017) MUHLENBACH has supervised doctoral theses in recommendation systems and data mining, and has been actively involved in teaching various computer science subjects including data analysis, machine learning, and computer ethics. His work bridges technical aspects of AI with human-centered considerations, reflecting his background in both computer science and cognitive psychology.

• Social Psychology
• Automatic Processes
• Embodied Cognition
• +۳ مورد دیگر

Dominique Muller is a Professor of Social Psychology at the University of Grenoble Alpes and a Senior Member of the Institut Universitaire de France. He directs the LIP/PC2S laboratory and has served as Associate Editor for multiple journals, including the European Journal of Social Psychology and Social Psychological and Personality Science. His career spans a PhD at Grenoble under Fabrizio Butera, a postdoc at the University of Colorado with Charles Judd and Vincent Yzerbyt, and academic roles at Paris Descartes and Grenoble. PhD in Social Psychology, University of Grenoble Postdoctoral Research, University of Colorado Teaching and Research Positions at Paris Descartes and Grenoble Alpes Muller’s research focuses on three domains: automatic processes (e.g., unconscious arithmetic, alcohol-related aggression), social comparison (e.g., intergroup dynamics, coaction effects on cognition), and statistical methods (e.g., mediation models, ANCOVA). His work often bridges embodied cognition with social behavior, using novel tasks like the Visual Approach/Avoidance by the Self Task (VAAST) to measure implicit tendencies. Recent publications highlight cross-cultural studies on gender identity, replication efforts in psychological science, and advancements in implicit attitude measurement. His research has been published in top journals such as Journal of Experimental Social Psychology , European Journal of Social Psychology , and Personality and Social Psychology Bulletin . Senior and Junior Member, Institut Universitaire de France Fellow, Society of Experimental Social Psychology Fellow, Association for Psychological Science Editorial Roles in Leading Journals Muller’s grants and affiliations include long-term support from the Institut Universitaire de France and collaborative projects across 62 countries. He leads the LIP/PC2S laboratory and has mentored researchers like François Ric and Charles Batailler, with methodological contributions to statistical analysis and implicit measurement tools.

Nozha Boujemaaمشاهده پروفایل

پژوهشگر

• Multimedia Content Search
• Pattern Recognition
• 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.

Sonia Mandinمشاهده پروفایل

پژوهشگر

• Educational Technologies
• Learning Sciences
• Computer-Assisted Learning
• +۵ مورد دیگر

Sonia Mandin is a Postdoctoral researcher in educational sciences specializing in educational technologies at the French Institute of Education (EducTice) at École Normale Supérieure de Lyon. She has been working as a Post-Doc researcher with the Eductice team since October 2015. Her professional background includes positions as a teaching assistant at DILIPEM, Grenoble-3 since 2014, and previous postdoctoral research with the LIRIS - CNRS SILEX team from 2013-2015. Her educational background is impressive and interdisciplinary. She earned her doctorate in educational sciences from LSE, Grenoble 2 in 2009 with 'Very honorable mention with congratulations from the jury.' Prior to this, she completed a DEA in educational sciences (2003), a Master's in Educational Sciences (2002), and a degree in educational sciences (2001), all from SEAD, Lille 3 with honors. Her technical foundation was established with a DUT in computer science engineering from IUT A, Lyon 1 in 1998. Dr. Mandin's research focuses on the complex process of learning from an interdisciplinary perspective, integrating insights from psychology, didactics, and computer science. Her work centers on assisting learners through appropriate digital activities by developing computational models that can be implemented in educational technology tools. A significant portion of her research has focused on summarization skills, exploring how to help students better understand texts through effective summarization techniques. She has developed expertise in Latent Semantic Analysis (LSA) and its application to educational contexts, particularly in the development of the Résum'Web system for improving students' summarization abilities. Analysis of Dr. Mandin's recent publications reveals a strong focus on adaptive learning systems, competency-based education, and the application of natural language processing to educational contexts. Her work demonstrates a consistent trajectory from foundational research on text summarization to broader applications in personalized learning environments. Key themes include learner modeling, knowledge representation through ontologies, and the development of feedback mechanisms that support student learning. Her research bridges cognitive science with practical educational technology applications, particularly in mathematics education and writing instruction. Dr. Mandin has been actively involved in several significant research projects including the e-education project 'OCINAEE' (2015-2016), the 'Cartographie des savoirs' project (2013-2015), the European 'Language Technologies for Lifelong Learning' project (2008-2011), and the ACI Ecole et Sciences Cognitives project (2003-2005). She has also served as a speaker for the Canopé Network (formerly CNDP), the National Agency for the Use of ICT in education. Her work spans multiple research teams and institutions, including collaborations with the Knowledge Media Institute at the Open University of Milton Keynes, and research positions at LIRIS - CNRS and LSE, Grenoble. This diverse institutional engagement has allowed her to develop a rich perspective on educational technology applications across different educational contexts.

• Computer Science
• Artificial Intelligence
• Data Mining
• +۳ مورد دیگر

Cyril De Runz is an Associate Professor at the University Institute of Technology of Blois (IUT Blois), University of Tours, France, affiliated with the Department of Multimedia and Internet Professions and the Fundamental and Applied Computer Science Laboratory of Tours (LIFAT, UR 6300). He also contributes to the Polytechnic School of the University of Tours (EPU), focusing on interdisciplinary computer science applications. His research spans Artificial Intelligence, Data Mining, Wireless Sensor Networks, Geographic Information Systems, and Human-Computer Interaction. Key areas include cycling infrastructure analysis using OpenStreetMap data, automatic dashboard generation for business intelligence, employee attrition modeling through sequential pattern mining, and optimization of sensor network coverage. His work bridges theoretical computer science with practical urban planning and human resources applications. Analysis of his 2023-2025 publications reveals strong trends in edge-AI deployment (e.g., ternarized vision-language models), advanced wireless sensor network strategies, and integration of multi-source data for transportation and workforce analytics. His methodologies often combine probabilistic modeling, fuzzy logic for imperfect geographic data, and deep learning adaptations. De Runz actively participates in LIFAT laboratory research, emphasizing interdisciplinary collaboration across civil engineering, social sciences, and energy systems. His projects frequently address real-world challenges like cycling safety, urban mobility, and business intelligence automation. No verifiable information on student advising, research grants, or scientific awards was found in the provided sources.

Nathalie Friburgerمشاهده پروفایل

دانشیار

• Natural Language Processing
• Named Entity Recognition
• Finite State Automata and Transducers
• +۳ مورد دیگر

Nathalie Friburger is an Associate Professor in Computer Science at the University Institute of Technology of Blois, affiliated with the University of Tours. She is a member of the Fundamental and Applied Computer Science Laboratory of Tours (LIFAT) and the BDTLN Research Team since 2003. Her academic work spans teaching in algorithms, programming, web development, and operating systems, while her research focuses on Natural Language Processing with particular expertise in named entity recognition and finite state transducers. Her research interests center on Natural Language Processing, specifically the automatic extraction of named entities using finite state automata and transducers. She has developed significant tools like CasSys for working with cascades of transducers within the Unitex text processing system. Her work extends to Arabic language processing, Renaissance text analysis, and cultural heritage applications, demonstrating both theoretical depth and practical implementation across multiple languages and domains. Analysis of her recent publications reveals a consistent focus on named entity recognition systems, with increasing specialization in Arabic language processing alongside continued work on French NER. Her research integrates rule-based approaches with data-driven methods, showing evolution from foundational work on transducer cascades toward more sophisticated hybrid systems and applications in digital humanities. The development of CasSys and related tools demonstrates her commitment to creating open, reusable infrastructure for the NLP community. She has served as co-supervisor for PhD students Damien Nouvel (2009-2012) and Fatma Ben Mesmia Chaabouni (2014-2019), contributing to the next generation of researchers in computational linguistics. Her research has been supported by multiple projects including ISTEX (2014-2017), Ortolang (2013-2014), Renom (2011-2013), and others focused on named entity recognition and text processing. Friburger has been actively involved in the academic community as Program Committee Member for TALN conferences (2013-2018), director of the TAL magazine on Named Entities (2013), and reviewer for numerous conferences including EMNLP and CIAA. She has also contributed to book editing, notably for TALN 2001 proceedings and the TAL Review on Named Entities (2013).

Boris Newمشاهده پروفایل

استاد

• Cognition
• Psycholinguistics
• Reading
• +۳ مورد دیگر

Boris New is a University Professor at Université Savoie Mont Blanc, affiliated with the Laboratoire de Psychologie et Neurocognition (LPNC, CNRS UMR 5105). He is also a Junior Honorary Member of the Institut Universitaire de France. Professor New's primary research interests focus on cognition , with specific expertise in psycholinguistics and reading . His work explores how language processing occurs in the human mind, with particular attention to lexical access mechanisms and reading automaticity. His research has demonstrated that consonants play a more significant role than vowels during lexical access in reading, and that reading automaticity develops approximately 5 months after reading instruction begins in French. Short language exposition sessions can improve self-esteem Letters are perceived as taller than pseudoletters, and words as taller than pseudowords Subtitle frequencies better predict reading times than written frequencies Phonological representations are critically important during reading Professor New has been recognized with the prestigious title of Junior Honorary Member of the Institut Universitaire de France, highlighting his significant contributions to cognitive science and psycholinguistics. He has developed numerous valuable resources for researchers in psycholinguistics, including Lexicon (a French lexical database), WorldLex (lexical frequencies database), UniPseudo (a universal pseudoword generator), Lexicon-Infra (French sublexical information), Subtlex-US (English subtitle frequencies), MultiPic (standardized drawings with norms), MEGALEX (French reaction times), and Diphones-FR (French diphone database). Professor New maintains an active laboratory at LPNC, where he continues to investigate the cognitive mechanisms underlying language processing and reading. His work bridges theoretical cognitive science with practical applications for language learning and literacy development.

• Machine Learning
• Data Mining
• Text Mining
• +۳ مورد دیگر

Guillaume Cleuziou is a Full Professor at the Université d'Orléans, France, and a member of the Constraints and Machine Learning (CA) team at the LIFO laboratory (Laboratoire d'Informatique Fondamentale d'Orléans). His research focuses on machine learning, data mining, and text mining, particularly in unsupervised and semi-supervised learning methodologies for knowledge extraction from texts. He holds a master's degree in Mathematics (2000) and a MSC in Computer Science (2001), both from Université d'Orléans, where he also completed his PhD in Computer Science in 2004. Education: PhD in Computer Science, Université d'Orléans, 2004 MSC (DEA) in Computer Science, Université d'Orléans, 2001 Master's Degree in Mathematics, Université d'Orléans, 2000 Research Interests: His work emphasizes developing algorithms for text mining, including unsupervised learning techniques, semantic analysis, and the application of pretopological spaces for lexical taxonomy construction. He explores multimodal data analysis, crisis tweet categorization, and embeddings for programming education. His contributions span theoretical advancements and practical applications in data clustering, community detection, and educational technologies. Labs/Teams: He is affiliated with the LIFO laboratory and leads research within the CA team, collaborating on interdisciplinary projects involving natural language processing, machine learning, and computational linguistics. His work bridges theoretical computer science with real-world applications in disaster management, educational tools, and semantic web technologies.

• Developmental Psychology
• Cognitive Development
• Psychology of Language
• +۱۲ مورد دیگر

Pierre Largy is a Professor of Developmental Psychology at Toulouse Jean Jaurès University, affiliated with the NeuroPsychoLinguistics Laboratory (LNPL). He teaches in the UFR of Psychology and UFR SES, and has also taught at ESPE Midi-Pyrénées, the University of Geneva (Switzerland), and the University of Social and Human Sciences of Hanoi (Vietnam). His research focuses on cognitive development, language acquisition, and learning processes, particularly in written language. His research interests center on how children and students acquire written language skills, especially spelling and grammar, and the cognitive mechanisms underlying learning difficulties such as dyslexia. He investigates the interplay between orthography, reading, and writing, and has expanded his work to include digital writing (e.g., SMS and instant messaging), exploring how these forms reflect or affect linguistic competence. More recently, he has studied the impact of emotion on orthographic performance, using methods such as emotional induction via music or color. His experimental approaches include chronometric analysis, dual-task paradigms, and corpus studies, focusing on behavioral indicators like error types, reaction times, and emotional responses. The trends in his recent publications reveal a consistent focus on spelling acquisition, the cognitive load in writing, emotional influences on performance, and the linguistic characteristics of digital communication. His work bridges developmental psychology, psycholinguistics, and educational research, with a strong emphasis on empirical methods and real-world applications. Among his scientific contributions, he has organized major conferences such as “Written language disorders: from childhood to adulthood” (2012) and “Written language disorders in children: from theory to practice” (2008), and has served as an expert for the European Commission and research agencies in Quebec. He has reviewed for journals including l'Année Psychologique , British Journal of Educational Psychology , and Language and Cognitive Processes . Largy has supervised several doctoral students, including Lucille Soulier and Aurélie Simoës-Perlant. He has held significant administrative roles, including Director of the UFR of Psychology, Director of the Department of Developmental Psychology, and member of the University's Board of Directors. His research has been supported through collaborations and institutional responsibilities, though specific grants are not detailed in the text. He leads a research team within the LNPL laboratory, focusing on written language development and disorders. He is actively involved in research teams and laboratories, particularly the NeuroPsychoLinguistics Laboratory (LNPL), where he conducts experimental studies on writing, reading, and cognitive development. His ongoing work includes exploring emotional effects on learning and the evolving nature of written language in digital contexts.

• Semantic Data Integration
• Ontology-based Database Design
• Big Data & Cloud
• +۴ مورد دیگر

Ladjel Bellatreche is a Full Professor of Data Engineering at the National Engineering School for Mechanics and Aerotechnics (ENSMA) in Poitiers, France, where he has been a faculty member since September 2010. He leads the Data and Model Engineering Team at the Laboratory of Computer Science and Automatic Control for Systems (LIAS) . His educational background includes an Engineering degree in Computer Science obtained in 1992 from the Department of Computer Science at Sidi Bel Abbès, Algeria. He later held positions as Assistant and Associate Professor at the University of Poitiers, France, and served as a Visiting Professor at the University of Québec in Outaouais, Canada, and a Visiting Researcher at Purdue University and Hong Kong University of Science and Technology. His research interests span a wide range of topics in data engineering, including semantic data integration , ontology-based database design , big data and cloud computing , green computing , and database deployment . He has made significant contributions to the design and optimization of data warehouses, particularly in the context of large-scale and distributed systems. Bellatreche has an extensive publication record, including over 60 journal articles and numerous conference proceedings. His recent work focuses on scalable RDF query processing, green query optimization, and leveraging linked open data for enhancing traditional data warehouses. He has also co-authored several books and book chapters on data warehousing and big data analytics. He actively participates in the research community by serving as a reviewer for top-tier journals such as IEEE TKDE and DKE , and as an editorial board member for various international journals. He has organized and co-organized numerous conferences and workshops, including DAWAK , DASFAA , and MEDI , and has served on the program committees of over 40 international conferences. Bellatreche is deeply involved in promoting research in Africa and Asia, where he co-supervises several PhD and Master's students and organizes conferences and workshops to foster collaboration and knowledge exchange.

Denys Duchierمشاهده پروفایل

استاد

• Constraint programming
• Computational linguistics
• Programming languages
• +۳ مورد دیگر

Denys Duchier is a Professor of Computer Science at the University of Orléans, affiliated with the LIFO (Laboratoire d'Informatique Fondamentale d'Orléans) and leading the "Constraints and Learning" team. His research bridges constraint programming, computational linguistics, and programming language design. University: University of Orléans Academic Role: Professor Research Team: Constraints and Learning (LIFO) Research Interests include constraint programming, Tree Adjoining Grammars (TAG), syntax-semantics interfaces, and formal grammar modeling. His work focuses on applying constraint-based methods to natural language processing, particularly for under-resourced languages like Arabic. Publications emphasize grammar engineering, constraint-driven language modeling, and applications of formal grammars to African languages. He collaborates on meta-grammar frameworks (e.g., XMG) and constraint optimization for linguistic analysis. Contact : denys.duchier@univ-orleans.fr, Building IIIA, Rue Léonard de Vinci, BP 6759, F-45067 Orléans Cedex 2.