جست‌وجوی استاد و پژوهشگر

• Middle East Studies
• Contemporary Islam
• Arab World
• +۳ مورد دیگر

Jean-Pierre Filiu is a Full Professor of Middle East Studies at Sciences Po (Paris) , affiliated with the CERI research center since 2009. A historian and Arabist, he combines academic research with diplomatic experience, having served in Jordan, Syria, Tunisia, and the USA during his 18-year tenure at the French Ministry of Foreign Affairs, including advisory roles to three French ministers. Current affiliation: Sciences Po (Professor of Middle East Studies) Research affiliation: CERI (Centre d'études et de recherches internationales) Visiting professorships: Columbia University (New York), Georgetown University (Washington) Media presence: Weekly columnist at Le Monde since 2015 Research Focus : Filiu's scholarship centers on contemporary Islamic movements, Middle Eastern geopolitics, and Arab world history. His work examines: Radicalization processes and extremist ideologies French-Middle East diplomatic relations Regional conflict dynamics Religious apocalyptic narratives Post-conflict state structures Digital media's role in revolutions Publication Trends : Recent works emphasize the Middle East's evolving political landscape, with special attention to: ISIS emergence and deep state connections French secularism (laïcité) debates Arab historiography approaches Visual storytelling through graphic novels Regional power networks Humanitarian crisis analysis Scientific Recognition : Palestine Book Award (2014) for Gaza, A History International acclaim for Apocalypse in Islam Regular policy commentary in prestigious outlets Professional Activities : Filiu maintains active diplomatic analysis, including his Le Monde blog since 2015, and has conducted specialized teaching programs like the Conflicts and negotiations in the Middle East master's course.

• Explainable Artificial Intelligence
• Machine Learning
• Data Clustering
• +۴ مورد دیگر

Nicolas Labroche serves as a Researcher in the Department of Computer Science at the Polytechnic School of the University of Tours. He is affiliated with the Fundamental and Applied Computer Science Laboratory of Tours (LIFAT) within the UFR of Sciences and Technology. His academic work spans multiple research domains with significant contributions to machine learning methodology and applications. His primary research focuses on Explainable Artificial Intelligence , particularly for medical applications where model interpretability is critical. He has pioneered methods in clustering of local attributive explanations and discernibility in medical ML models . Additional expertise includes exploratory data analysis through mathematical programming for comparison queries, time series forecasting for environmental monitoring, and preference-based explanations in recommender systems. His work bridges theoretical computer science with practical applications in healthcare, environmental science, and business intelligence. Analysis of his publication trends reveals consistent innovation in making data exploration more efficient and interpretable. Recent work emphasizes user-centric explainability (2024-2025), mathematical optimization for analytics (2022-2023), and synthetic data generation (2022). His research demonstrates strong interdisciplinary connections between computer science, medicine, and environmental science. His laboratory affiliation with LIFAT provides the infrastructure for his computational research. While specific grant details aren't public, his publication record indicates sustained research productivity across multiple European-funded projects focused on data science applications.

Romain Raveauxمشاهده پروفایل

دانشیار

• Image Analysis
• Machine Learning
• Structural Pattern Recognition
• +۵ مورد دیگر

Romain Raveaux is an Associate Professor at the LIFAT Computer Science Laboratory, University of Tours, affiliated with Polytech Tours. His research focuses on Image Analysis, Machine Learning, Structural Pattern Recognition, Graph Matching, Graph Neural Networks, Discrete Optimization, Reinforcement Learning, and Transfer Learning . Email: romain.raveaux@gmail.com , romain.raveaux@laposte.net Address: 64 av. Jean Portalis, Tours, France, 37200 Phone: +33 (0)2 47 36 14 27 Research Interests Graph Matching and Neural Networks Discrete Optimization for Pattern Recognition Transfer Learning in Graph-Based Models Historical Document Analysis Scientific Trends His recent work bridges Graph Neural Networks with Mixed-Integer Programming , focusing on Image Semantic Segmentation and Graph Cycle Detection . Earlier studies emphasize Genetic Algorithms for graph classification and Graph Edit Distance optimization in pattern recognition.

Kevin Hjortshøj O'Rourkeمشاهده پروفایل

استاد

• Economic History
• International Economics
• Globalization Studies
• +۳ مورد دیگر

Kevin Hjortshøj O'Rourke is a CNRS Research Professor and Professor of Economics at Sciences Po Paris, with affiliations at Oxford University and other institutions. He specializes in economic history and international economics, focusing on globalization and deglobalization. His research bridges historical and contemporary issues, notably Brexit and trade policy. He holds honorary positions at Oxford, Trinity College Dublin, University College Dublin, and CAGE in Warwick, and is a Fellow of prestigious academies like the British Academy. O'Rourke earned his PhD from Harvard in 1989 and previously served as Chichele Professor of Economic History at Oxford. His work explores the intersection of trade, conflict, and economic development, with major publications including Globalization and History and Power and Plenty . He has received significant awards, including an ERC Advanced Grant (2010). Recent research includes analysis of historical trade patterns, Brexit implications, and interwar economic policies. Education: PhD in Economics from Harvard University (1989). Research Interests: Economic history, international trade dynamics, historical globalization trends, and policy impacts of trade. His work combines quantitative and qualitative approaches to understand long-term economic shifts and their societal implications. Publications & Awards: Over 50 peer-reviewed articles and books, including seminal works on globalization and Brexit. Awards include the 1999 PSP Award for Globalization and History , and recognition as a Fellow of the Cliometric Society. Grants & Roles: Directed the Economic History Program at CEPR and served on editorial boards of leading journals. Current projects include analysis of historical trade collapses and the political economy of globalization.

Nicolas Ballierمشاهده پروفایل

استاد

• Corpus prosody
• Neural machine translation
• Automatic analysis of learner corpora
• +۵ مورد دیگر

Nicolas Ballier is a Professor at Université Paris Cité (formerly Université Paris Diderot), where he teaches and conducts research in linguistics and digital humanities. Previously, he taught at the Université de Rouen and Paris 13. His work focuses on the intersection of linguistics, computational methods, and language learning technologies, with particular expertise in neural machine translation and speech processing. His primary research interests include: Corpus prosody Neural machine translation Automatic analysis of learner corpora Digital humanities Epistemology of linguistics (third revolution of grammatisation) Interpretability of neural machine translation systems Representation of speech in Whisper audio models Dr. Ballier's recent work explores how computers transform linguistic data (the 'third revolution of grammatisation'), with a focus on neural machine translation interpretability and speech analysis using large language models like Whisper. His research bridges theoretical linguistics with practical applications in language learning and translation technologies, particularly focusing on how these technologies can be made transparent and useful for translators and language learners. His 15 most recent publications (2022-2024) demonstrate a strong focus on neural machine translation interpretability, Whisper applications for language assessment, and learner corpus analysis. The publications span multiple prestigious venues including EAMT, ACL, LREC-COLING, and specialized journals in speech technology and computational linguistics, showing consistent productivity and impact in his fields. Dr. Ballier has been PI or team member on numerous European-funded projects including DOKTORAND (2012-2016), KVARK project (2014-2026), PHC Ulysses (2019), multitraiNMT (2021), and LT-LIder project (2024-Nov 2026). He has developed platforms like PAPTAN for neural machine translation experiments and MAKE-NMT VIZ for investigating machine translation interpretability. He has supervised PhD students through collaborative projects and has been involved in research initiatives like DLLA (Deep Learning for Language Assessment) exploring CEFR levels with keylog data, Neuroviz (2021-2022), and SPECTRANS (2020-2022) focusing on specialized neural translation and probing information flow in neural networks.

• Distributed Computing
• Self-stabilizing Algorithms
• Network Algorithms
• +۱ مورد دیگر

Alain Cournier is a University Professor at the University of Picardy Jules Verne (UPJV), France, affiliated with the ALCO research unit (UR 4290) focusing on Algorithmic and Complexity. His office is located in room 401 with contact phone 5913. He maintains an active research profile with continuous publications from 1992 through 2024, primarily in distributed computing and theoretical computer science. Professor Cournier's research centers on fault-tolerant distributed algorithms, specializing in self-stabilizing systems for networked environments. His core contributions span leader election protocols, synchronous unison mechanisms, and message forwarding algorithms in directed and undirected topologies. He pioneered work in snap-stabilization and polynomial-time convergence guarantees, with recent focus on directed network challenges. Earlier career phases included modular graph decomposition algorithms (1990s), while 2018-2019 saw exploration of autoencoder neural networks for anomaly detection in connected buildings. Analysis of his 15 most recent publications reveals strong continuity in distributed algorithms research (12/15 papers), with 2023-2024 works exclusively addressing self-stabilization in directed networks using innovative metaphors like Roman infrastructure. The 2018-2019 neural network studies represent a brief interdisciplinary expansion before returning to core theoretical work. His publications consistently appear in premier venues including PODC, ICDCN, and Theoretical Computer Science, often collaborating with Altisen, Defalque, and Devismes. He operates within the ALCO research unit (UR 4290) at UPJV, which serves as the institutional home for his algorithmic complexity research. This unit facilitates collaboration across the French distributed computing community, evidenced by regular AlgoTel conference participation. While specific lab structures aren't documented, his publication patterns indicate sustained theoretical work with periodic applied explorations in cybersecurity contexts.

Fabrice Boissierمشاهده پروفایل

دانشیار

• Formal Concept Analysis
• Topic Modeling
• Text Processing
• +۷ مورد دیگر

Fabrice Boissier is an Associate Professor at EPITA, specializing in digital methods for humanities and social sciences. He earned his PhD and MSc from Université Paris 1 Panthéon-Sorbonne, focusing on knowledge extraction and reuse in knowledge-intensive processes, enterprise modeling for decentralized organizations, and applications of formal concept analysis, natural language processing, and data visualization. Current Research: Formal Concept Analysis, Topic Modeling, Text Processing, Data Visualization, Knowledge Extraction, and Knowledge-Intensive Processes. Collaborations: Working with Nida Meddouri in the Security and Systems team and Marie Puren in the DMHSS (MNSHS) team. Teaching: Courses in algorithmics, computer architecture, programming languages, and operating systems at EPITA's Bachelor CyberSécurité program. Supervision: Mentoring research and industry interns from EPITA, Université de Sousse, and Université Paris 1 Panthéon-Sorbonne.

Vincent BARRAمشاهده پروفایل

استاد

• Data Analysis
• Image Processing
• Video Processing
• +۶ مورد دیگر

Vincent BARRA is a full professor in Computer Science at the LIMOS lab of Clermont-Auvergne University and CNRS. He serves as Vice dean of Clermont-Auvergne-INP (education and training), Assistant director of LIMOS, and Artificial Intelligence Special Advisor for Clermont-Auvergne University. He is also a member of the scientific board and Executive committee of MIAI Cluster. His academic work is primarily conducted through ISIMA, the engineering school in computer science of Clermont-Auvergne INP. Professor BARRA's research focuses on data analysis from both methodological and applicative perspectives. His work spans image and video processing, mesh processing, computational geometry, and machine/deep learning techniques. His interdisciplinary research connects computer science with applications in medical imaging, geothermal systems, polymer dynamics, mental health diagnostics, semiconductor manufacturing, and environmental monitoring. His publications demonstrate consistent innovation in developing algorithms for segmentation, feature extraction, and pattern recognition across diverse domains. The analysis of his recent publications reveals strong trends toward deep learning applications in specialized domains. His work shows increasing focus on medical applications (depression diagnosis, preterm birth prediction), geoscience (geothermal systems analysis), and industrial applications (semiconductor metrology, structural health monitoring). A consistent theme across his research is the development of robust, domain-specific deep learning architectures that address unique challenges in data analysis across different scientific fields. Professor BARRA maintains active collaborations across multiple institutions and disciplines, as evidenced by his extensive co-authorship network. His work bridges theoretical computer science with practical applications in diverse fields, demonstrating a commitment to solving real-world problems through innovative computational approaches. He leads research within the LIMOS laboratory, which focuses on computer science, modeling, and systems optimization.

• Data Mining
• Knowledge Graphs
• Pattern Analysis
• +۷ مورد دیگر

Dr. Arnaud Soulet is a researcher at the University of Tours , affiliated with the Polytechnic School of the University of Tours and the Department of Computer Science . He works at the intersection of the LIFAT Laboratory (UR 6300) and contributes to the fields of pattern mining and knowledge graph analysis. Research Focus: Data Mining, Knowledge Graphs, Sequential Pattern Mining, Distributed Databases, Cultural Heritage Informatics Publication Trends His recent publications emphasize knowledge graph analysis (e.g., Rankingdom architecture, structural modeling) and pattern mining (reservoir sampling, frequency constraints, sequential patterns). Applications span employee attrition analysis , cultural heritage data , and data stream processing .

Murielle GEORGES-LEROYمشاهده پروفایل

پژوهشگر

• Archaeology
• Antiquity
• Lidar Analysis
• +۳ مورد دیگر

Murielle GEORGES-LEROY is an Associate Researcher at the French Ministry of Culture’s SOPAST delegation, focusing on heritage inspection, research, and innovation. Her work bridges archaeology and environmental science, specializing in forest archaeology and the application of LiDAR technology. She holds roles as a General Curator of Heritage and Inspector of Heritage, contributing to the preservation and analysis of cultural sites. Her research emphasizes the Gallo-Roman rural world, particularly ancient land parcelling and settlement dynamics, often in collaboration with institutions like INRAE. Current projects include studying settlements on the Haye plateau in Meurthe-et-Moselle. She also manages archaeological data and archives, addressing challenges in scientific documentation and heritage management. GEORGES-LEROY’s publications span LiDAR applications, transborder archaeology, and historical land use. She has authored/co-authored over 50 works since 1990, including books like Le passé sous les arbres (2023). Her work highlights interdisciplinary approaches, integrating remote sensing, GIS, and environmental archaeology to explore human-environment interactions. Key contributions include advancing LiDAR’s role in uncovering fossilized agricultural structures under forests and advocating for innovative methods in cultural heritage preservation. She participates in international initiatives and policy discussions on archaeological data management and cross-border collaboration. GEORGES-LEROY’s expertise spans archaeological fieldwork, data analysis, and policy, with a focus on Lorraine’s historical landscapes and their modern ecological implications.

• Biomedical Signal Processing
• Decision-Making Methodologies
• Frailty Prevention in Elderly
• +۳ مورد دیگر

Aly CHKEIR is an Associate Professor at the University of Technology of Troyes (UTT), holding the 'SilverTech' chair focused on technologies for healthy aging and elderly autonomy support. He earned his PhD in biomedical sciences from the University of Technology of Compiègne (UTC) in 2011, specializing in uterine electrical activity modeling. His research emphasizes biomedical signal processing, decision-making methodologies, and applications in frailty prevention among the elderly. Education: PhD in Biomedical Sciences, UTC, France (2011). Research interests include signal segmentation/classification, biomedical engineering, and solutions for aging populations. Notable projects include the SilverTech chair's holistic approach to aging technologies and the PiCADo initiative for in-home medical monitoring systems. Recent work focuses on AI-driven diagnostics (e.g., MRI segmentation, cough analysis), radar-based mobility assessment, and voice recognition for health monitoring. His contributions span sensor fusion, gait analysis, and non-invasive health tracking tools. His lab collaborations include Doppler radar systems for gait speed measurement, thermal imaging for health indicators, and AI-enhanced geriatric assessment tools. Projects like ARPEGE and PiCADo highlight his commitment to deploying innovative healthcare solutions for aging populations.

• Machine Learning
• Computer Vision
• Image Analysis
• +۳ مورد دیگر

Prof. Jean-Yves RAMEL is a faculty member at Savoie Mont Blanc University's Department of Computer Science (LISTIC laboratory). Previously, he served as a Professor at Polytech’Tours (2007–2023) and held roles at INSA Lyon (1997–2002). His research focuses on machine learning on graphs, medical and document image analysis, and interactive learning systems. He has published extensively in journals like Pattern Recognition and Medical Image Analysis . His work spans medical imaging segmentation, graph-based algorithms, and historical document processing. Notably, he contributed to projects like BVH (Bibliothèques Virtuelles Humanistes) and developed methods for graph edit distance and dynamic classification. He maintains active collaborations in digital humanities and has supervised numerous projects in computer science education. Education: PhD in Computer Science (1996), INSA Lyon: 'Interpretation automatique de documents graphiques' Maitre de conférences positions at INSA Lyon (1997–2002) and Polytech’Tours (2002–2023) Research Interests: Machine Learning on Graphs: Graph neural networks, graph embedding, and graph matching algorithms. Image Analysis: Medical imaging segmentation, historical document processing, and 3D texture analysis. Interactive Learning Systems: Dynamic classification, anytime algorithms, and one-class classifiers. Publications: Over 140 publications, focusing on graph-based methods, medical imaging, and document analysis. Recent work includes advancements in CNN/GNN pipelines for brain imaging and grammar-reinforcement learning for graphs (2025). Grants & Projects: Led the LIFAT lab (2018–2021) and contributed to the BVH digital humanities program. Active in collaborative projects involving medical imaging segmentation and historical document digitization. Labs/Teams: LISTIC laboratory (Savoie Mont Blanc University) and prior roles in LIFAT (Tours) and INSA Lyon's Interaction Collaborative lab.

Thomas Conradمشاهده پروفایل

مدرس

• French Novel (19th-20th century)
• Poetics of Literature
• Literary Theory
• +۳ مورد دیگر

Thomas Conrad is a Lecturer in the Department of Literatures and Language at the École Normale Supérieure (ENS) in Paris, where he has been teaching since 2015. He is affiliated with several research entities including La République des savoirs: Lettres, Sciences, Philosophie and the Centre de Recherches sur les Relations entre Littérature, Philosophie et Morale. As a former student of the ENS himself, Conrad brings deep institutional knowledge to his academic work. Conrad holds an agrégé in modern literature and a doctorate in French literature. His scholarly focus centers on the poetics of novel cycles (sequels, series, trilogies), with particular emphasis on 19th and 20th century French literature from Balzac and Dumas to contemporary authors. His research spans theoretical frameworks including narrative structure, literary sociology, and the representation of time and space in fiction. Analysis of Conrad's extensive publication record reveals a consistent scholarly trajectory focused on Balzac studies, with significant contributions to understanding novel cycles, narrative structure, and 19th century French literary production. His work demonstrates expertise in both theoretical literary analysis and close reading of canonical texts, with particular attention to how narrative form reflects social and historical contexts. Conrad's scholarship shows remarkable continuity in exploring how literary cycles function as complex narrative systems that reflect broader cultural patterns. While specific scientific awards are not documented in the available information, Conrad's substantial publication record in prestigious journals and with respected academic presses demonstrates significant scholarly recognition. His work appears regularly in specialized Balzac and 19th century literature journals, as well as in broader literary theory publications. Though specific details about student supervision are not provided in the available documentation, Conrad's position as a lecturer at ENS suggests involvement in graduate education and potentially doctoral supervision. His extensive research output and specialized knowledge in 19th century French literature would position him as a valuable mentor for students working in this field. Conrad is actively involved with several research collectives, most notably La République des savoirs: Lettres, Sciences, Philosophie, which serves as an intellectual hub for interdisciplinary work connecting literature, philosophy, and moral studies. His participation in this collective and the Centre de Recherches sur les Relations entre Littérature, Philosophie et Morale suggests engagement with broader theoretical questions that extend beyond strictly literary analysis.

Anne-Lise Jouenمشاهده پروفایل

دانشیار

• Neuroscience
• Language
• Speech
• +۵ مورد دیگر

Anne-Lise Jouen is an Associate Professor at the Faculty of Sports Sciences, University of Burgundy, where she is affiliated with the INSERM U1093 Laboratory. She has held prestigious research positions at institutions including the University of Geneva, University of Tokyo, and Sorbonne University. Her academic credentials include: PhD in Neuroscience (2013) from Stem cell and Brain Research Institute, Claude Bernard University – Lyon I Master 2 in Engineering of Cognition, Creation and Learning (2009) from Grenoble INP Master 2 in Neuropsychology (2009) from Université Pierre Mendès France Master 1 in Cognitive Sciences (2008) from Université Lumière Lyon II Licence in Psychology and Cognitive Sciences (2007) from Université Lumière Lyon II DIU in Gerontechnology (2010) from Joseph Fourier University and others Dr. Jouen's research focuses on the intersection of neuroscience, language processing, and technology. She investigates how the brain processes language and spatial information through embodied cognition frameworks, employing neuroimaging techniques like fMRI, EEG, and fNIRS. Her recent work explores human-robot interaction for language learning and autism intervention, demonstrating through EEG monitoring that social robots increase functional connectivity in children's brains during language acquisition. Her publication record shows consistent research impact across multiple domains including semantic processing, speech production, and autism interventions. Notable projects include the GOLIAH platform for home-based autism intervention and research on telepresence robotics' impact on spatial cognition. Her scientific recognition includes the JSPS fellowship award for her post-doctoral research at the University of Tokyo. Dr. Jouen's current research trajectory includes: 2022-2023: Post-doctorate studying telepresence robotics and virtual reality effects on spatial representations at CAPS Laboratory 2017-2020: Speech production research using EEG (SNF Sinergia Project MoSpeeDi) at University of Geneva 2015-2017: Language learning via human-robot interactions at University of Tokyo 2013-2015: Autism social skills evaluation via ICT at Sorbonne University

Filippo Gattiمشاهده پروفایل

پژوهشگر

• High-fidelity physics-based earthquake simulation
• Artificial Intelligence applied to seismology
• Dynamic Soil-Structure Interaction coupling
• +۳ مورد دیگر

Filippo Gatti is a researcher at the Paris-Saclay Mechanics Laboratory, specializing in high-fidelity physics-based earthquake simulations, AI applications in seismology, and soil-structure interaction dynamics. His work integrates advanced numerical methods with high-performance computing to model seismic wave propagation across heterogeneous geologies. Current research focuses on hybrid digital twins, neural operators, and physics-guided machine learning Active in 3D regional-scale simulations with spectral/finite element methods Collaborates on seismic safety analyses for critical infrastructure like nuclear power plants Recent publications highlight innovations in earthquake ground motion modeling, mesh generation techniques, and AI-enhanced physics simulations using technologies like GANs and diffusion models. His work demonstrates strong interdisciplinary connections between computational mechanics, geophysics, and artificial intelligence, particularly in developing predictive models for seismic risk assessment.