جست‌وجوی استاد و پژوهشگر

• 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.

• Image Processing
• Signal Processing
• Computer Vision
• +۴ مورد دیگر

Marc Donias is an Associate Professor at the University of Bordeaux, affiliated with the IMS (Laboratory of Integration, Material to System) which is part of the College of Engineering. He is a member of the Signal and Image Processing research group and works within the MOTIVE team, focusing on advanced image processing and computer vision applications. His research interests span across multiple domains including image processing, signal processing, computer vision, machine learning, and seismic data analysis. Dr. Donias has made significant contributions in texture analysis, image colorization algorithms, and geological data interpretation. His work often bridges theoretical advances with practical applications in agriculture, materials science, and geophysics. Analysis of his recent publications reveals a strong trend toward deep learning applications in image processing, particularly generative models for image colorization and object detection. His work demonstrates interdisciplinary reach, connecting computer vision with agricultural technology, materials science, and geophysical interpretation. The publications show consistent collaboration with researchers from the IMS laboratory, particularly with Yannick Berthoumieu and other members of the MOTIVE team. Dr. Donias has been actively involved in developing innovative approaches for seismic horizon reconstruction, texture analysis, and agricultural image processing. His work on SPD manifold learning for image colorization represents a sophisticated mathematical approach to a challenging computer vision problem. The practical applications of his research are evident in precision agriculture technologies and geological interpretation tools.

• Machine Learning
• Deep Learning
• Medical Informatics
• +۳ مورد دیگر

Nasmin Jiwani is a Research Scholar with 56 publications, an h-index of 20, and 921 total citations. Her academic work spans interdisciplinary applications of machine learning and deep learning techniques across medical diagnostics, cybersecurity, and IoT systems. Her research focuses on Medical Informatics where she develops AI-driven diagnostic tools for liver disease prediction, diabetic retinopathy classification, and acute lymphoblastic leukemia detection. In Cybersecurity , she pioneers image-based malware classification using deep learning architectures. Her IoT Systems research includes supply chain optimization and smart security applications. Recent work shows increasing emphasis on healthcare technology integration, particularly in cancer diagnostics and autism spectrum disorder analysis. Collaboration patterns indicate strong partnerships with Ketan Gupta (30 co-authored papers), J. Logeshwaran, and Neda Afreen across IEEE conferences and journals. Her publication trajectory demonstrates consistent output with 10+ papers annually since 2022, showing particular strength in translating theoretical machine learning models to practical healthcare and security applications.

Stéphane Safinمشاهده پروفایل

مدرس

• Creative Design
• Human-Machine Interaction
• Cognitive Ergonomics
• +۵ مورد دیگر

Stéphane Safin is a Lecturer and researcher in ergonomics at Télécom Paris, part of the Institut Polytechnique de Paris. He holds a PhD in ergonomic psychology from the University of Liège (2011) and conducted postdoctoral research at the University of Montreal. His academic roles include teaching interaction design, user-centered design methods, and overseeing design projects. He co-leads the Master's in Design program accredited with University of Paris Saclay and ENSCI-Les Ateliers. His research focuses on creative activity in design, particularly in architecture and industrial design, emphasizing cognitive processes and instrumental dimensions of creativity. Key areas include digital sketching, collaborative design, and the role of external representations (drawings, models) in creative processes. Notable projects include the ANR Social Touch Project (2017-2020) exploring tactile interfaces for social communication and the EU-funded DIALLS Project (2018-2021) on cultural literacy through text production. He leads the Interaction, Technology, Activity (Interact) research team within the Interdisciplinary Institute of Innovation (i3) lab. His work spans participatory design, emergency response systems, and co-creation methodologies for urban planning. Recent publications address topics like bicycle modal shift in urban France, haptic interfaces for remote communication, and co-design in geriatric care facilities. He has contributed to over 70 peer-reviewed articles, conference papers, and book chapters, with a focus on design cognition, ergonomics education, and sociotechnical systems. His teaching integrates theoretical and practical design methodologies, emphasizing interdisciplinary collaboration and user-centric approaches.

Caroline Chanelمشاهده پروفایل

استاد

• Autonomous Systems
• Decision-Making Algorithms
• Robotics
• +۳ مورد دیگر

Caroline Chanel is a Professor at ISAE-SUPAERO (DCAS), holding the CASAC Chair since 2022. She has extensive experience in research and teaching, with roles including Associate Professor (2019-2024), Research Engineer (2013-2019), and HDR accreditation (2023). Her research focuses on embedded decision-making for autonomous systems, including proactive architectures, multi-robot cooperation, and human-machine interaction. She leads and participates in high-profile projects like SAMURAI (AID), CHIP-GT (ANR-DFG), and HAICO (CASAC Chair). She has supervised numerous PhD students and post-doctoral researchers, collaborating with institutions like ONERA, INRAe, and international partners. Education: PhD in Control and Embedded Systems (University of Toulouse 2013), Master's in Automatic Systems (Université Paul Sabatier 2008-2009), and Engineer Diploma from PUCRS (2002-2008). Awards include the Amelia Earhart Fellowship (2011) and ISAE-SUPAERO Foundation PhD Fellowship (2013). Research interests span decision-making algorithms, multi-agent systems, and neuroergonomics. Key projects address UAV navigation, blockchain integration for autonomous systems, and physiological computing for human-robot interaction. Teaching responsibilities include modules on autonomous systems, control systems, and neuroergonomics at ISAE-SUPAERO's engineering and master's programs. She co-leads the DECISIO doctoral team (ISAE-ONERA) and is involved in executive roles for conferences like EDSYS'.

Josselin Garnierمشاهده پروفایل

استاد

• Waves in Random Media
• Imaging in Complex Media
• Uncertainty Quantification
• +۶ مورد دیگر

Josselin Garnier is a Professor at Ecole Polytechnique, France, affiliated with the Center for Applied Mathematics. His research focuses on wave propagation in random media, imaging techniques, uncertainty quantification, and inverse problems. He has authored/co-authored multiple influential books including Wave Propagation and Time Reversal in Randomly Layered Media (2007) and Multi-Wave Medical Imaging (2017). His work bridges mathematical theory with applications in optics, seismology, and nuclear engineering. Research interests emphasize stochastic dynamics, nonlinear wave interactions, and Bayesian methods for parameter estimation. He leads a large research group with over 30 PhD students, many working on interdisciplinary projects such as thermalization in optical fibers and seismic fragility analysis. His contributions include developing reduced order modeling approaches for inverse problems and advancing methodologies for uncertainty quantification in nuclear reactor simulations. Key collaborations involve institutions like the French Mathematical Society and the Ciroquo Research & Industry Consortium. His educational contributions include the widely used All-in-one Mathematics textbook series for undergraduate students.

• Ontologies
• Collaborative Systems
• Modal Logic
• +۳ مورد دیگر

Elisabeth Gavignet serves as an Associate Professor in Computer Science at the Institut National Supérieur du Professorat et de l'Éducation (INSPE) within Université Bourgogne. Her academic career spans multiple institutions including Le2i Dijon, IUFM de Bourgogne, and CRIN Nancy, reflecting her deep engagement with both computer science and educational technology domains. Her research centers on ontological frameworks and knowledge representation systems, with significant contributions to collaborative information systems, uncertain data modeling using modal logic, and musicological information management. Current projects include the Cocktail initiative for real-time analysis of food discourse on Twitter and the NEUMA platform for collaborative music score libraries. Her work bridges theoretical computer science with practical applications in archaeology, musicology, and educational technology. Dr. Gavignet's scholarly output demonstrates consistent focus on knowledge engineering applications across diverse domains. Her recent publications emphasize modal logic applications for uncertain data, collaborative digital libraries, and ICT integration in educational settings. This interdisciplinary approach connects computer science fundamentals with domain-specific challenges in cultural heritage and education. Administratively, she has held significant responsibilities including directing CAPET preparation programs, leading the Informatique-Économie et gestion network since 2011, and coordinating distance learning initiatives. Her laboratory affiliations include LIB (since 2018) and Le2i Dijon (2009-2018), where she contributed to multiple ANR-funded research projects.

Didier Lebertمشاهده پروفایل

دانشیار

• Technological Innovation
• Graph Theory Applications
• Patent Data Analysis
• +۷ مورد دیگر

Didier Lebert is an Associate Professor and Deputy Director at the Unit of Applied Economics (UEA) at ENSTA Paris. His research focuses on technological innovation processes at company, industry, and regional levels using graph theory and patent data analysis. He coordinates major research projects including CROTALE on New Space innovation dynamics with CREA and FIREBALL on blockchain applications for armed forces. Lebert's research spans technological innovation, graph theory applications, patent data analysis, defense innovation, and strategic autonomy. His work examines how innovation systems function across different sectors and regions, with particular attention to the defense industry, space sector, and pharmaceutical companies. He applies structural analysis methods to understand technological trajectories, corporate strategies, and regional economic development patterns, often using patent citation networks to map knowledge flows. His recent publications show a clear trend toward defense-related innovation, blockchain technology, and strategic autonomy, reflecting growing national security concerns in technological development. There's also significant focus on analyzing major tech companies like Google and pharmaceutical giants like Sanofi through patent data. His work increasingly integrates AI applications across various sectors while maintaining a strong methodological foundation in graph theory and structural analysis. Award at ENSTA ParisTech's 2016 Technological Innovation Day for CoR&D Lebert leads multiple substantial research grants including CROTALE (with CREA), FIREBALL (AID project), PAESE series (DGA projects), and AUSTIN (DGA project on strategic autonomy). He has coordinated numerous ANR, EU, and defense-related projects since 2009, demonstrating strong grant acquisition capabilities. As co-founder of GraphMyTech, the first spin-off from UEA, he bridges academic research and commercial applications of technological mapping tools. Lebert directs the Unit of Applied Economics (UEA) research laboratory at ENSTA Paris and co-founded GraphMyTech, a technological intelligence solution that evolved from his academic research. His work integrates with the Paris-Saclay innovation ecosystem, where he serves on the management committee of PEPITE PEIPS. He leads research teams focused on applying graph theory to patent data analysis, with applications in defense, space technology, and corporate innovation strategy.

• Linguistics
• Automatic Language Processing
• Statistical Analysis of Textual Data
• +۶ مورد دیگر

Mathieu Valette is a University Professor at the Institut National des Langues et Civilisations Orientales (INALCO) in Paris, France, where he serves as Director of the Texts, Computer Science, Multilingualism department since 2021. He leads the ERTIM research team and coordinates the ANR AID ASTRID GECKO project on cognitive warfare since 2023. Previously, he served as President of section 7 (language sciences) of the CNU from 2014-2019 and Director of ERTIM from 2010-2019. Professor Valette's research focuses on the intersection of linguistics, computational methods, and text analysis. His work spans corpus semantics, statistical analysis of textual data, epistemology of natural language processing, and the characterization of harmful content. He has developed methodologies for subjective data mining and has made significant contributions to textual lexicology and automatic language processing. His research bridges theoretical linguistics with practical applications in multilingual contexts, particularly extending from French linguistics to Chinese language processing. Analysis of Professor Valette's recent publications (2020-2025) reveals a clear evolution in his research interests, with increasing focus on cognitive warfare, language models, and mental health detection through social media analysis. His work demonstrates a consistent integration of statistical text analysis with linguistic theory, particularly in the areas of sentiment analysis, corpus semantics, and the epistemological foundations of NLP. Notably, his research has expanded from theoretical linguistics to address contemporary challenges in AI ethics, cross-cultural language processing, and the societal impacts of language technologies. Throughout his career, Professor Valette has maintained active collaborations with researchers across multiple disciplines, including computer science, public health, political science, and cognitive psychology. His administrative roles in major research projects and department leadership demonstrate his significant contributions to the academic community beyond his direct research output.

• Industrial systems engineering
• Operational research
• Scientific computing
• +۶ مورد دیگر

David Garcia serves as Head of the Research and Innovation Department at CESI South-East region, affiliated with the Digital Innovation Laboratory for Businesses and Learning to Support Territorial Competitiveness (LINEACT). His work focuses on industrial systems engineering, operational research, and numerical simulation with particular expertise in production systems modeling. Dr. Garcia earned his Doctorate from Ecole Supérieure de Chimie, Physique Electronique de Lyon (ESCPE) with his 2002 thesis on polymer injection process optimization (awarded highest honors). He also holds an Advanced Study Diploma in IMAGE from Joseph-Fourier University - Dijon (1998, with honors) specializing in instrumentation and image computing. His research spans production systems engineering, with evolving focus from fundamental polymer injection molding processes to contemporary applications in digital twin technology and Industry 4.0/5.0. Key interests include dynamic scheduling of flexible manufacturing systems, human-system interactions in production environments, and image processing for industrial applications. His work demonstrates a clear trajectory from material science fundamentals to advanced computational approaches for modern manufacturing challenges. Analysis of his publication history reveals consistent contributions to polymer processing optimization that evolved toward digital manufacturing systems. His recent work focuses on digital twin implementation for micro learning factories, affordance characterization in industrial work environments using deep learning, and scheduling frameworks for Industry 5.0 contexts that balance human creativity with machine precision. Dr. Garcia actively supervises research, currently guiding Sarah Ouarab's doctoral work on characterizing affordances in human cyber-physical production systems through multimodal perception of human-system interactions. He serves as Micro Learning Factory (MLF) platform referent and participates in thesis juries for related engineering disciplines. As the regional coordinator for research and innovation activities at CESI South-East, he leads the LINEACT research team focusing on management and decision-making in production systems, human-system interactions, and educational innovation through project-based learning approaches across preparatory and engineering cycles.

OKONGWU Ucheمشاهده پروفایل

استاد

• Supply Chain Management
• Operations Research
• Decision Support Systems
• +۳ مورد دیگر

OKONGWU Uche is a Professor at the Toulouse Business School within the Department of Information, Operations and Decision Sciences . His academic work focuses on the intersection of supply chain management, decision science, and operational optimization, with a particular emphasis on sustainability and responsiveness in complex systems. Supply Chain Management Operations Research Decision Support Systems Humanitarian Logistics Genetic Algorithms Order Fulfillment His research explores advanced methodologies like heuristic-based genetic algorithms for multi-project scheduling, robust humanitarian facility location models, and sustainable supply chain planning frameworks. He has contributed to empirical studies on how supply chain practices impact organizational performance and tactical planning determinants. Recent publications highlight trends in humanitarian logistics , emergency response systems , and supply chain sustainability . His work includes tools for optimizing order fulfillment in stock-out situations and improving the maturity of sustainability disclosures in supply chains. For detailed publications, refer to the articles section. Contact: u.okongwu@tbs-education.fr .

• Computer Vision
• Image Processing
• Autonomous Systems
• +۶ مورد دیگر

Antoine Manzanera is a Professor HDR at ENSTA Paris, affiliated with the Unité d'Informatique et d'Ingénierie des Systèmes (U2IS) and the Systèmes autonomes et Robotique (SAR) department. His research focuses on Computer Vision, Image Processing, and Autonomous Systems, with notable contributions to medical imaging applications and robotics. He holds a Habilitation Degree from Université Pierre et Marie Curie (2012) and has taught at ENSTA, Université Paris Sorbonne, and international institutions. BSc Mathematics, Université Claude Bernard Lyon 1 (1991) MSc Theoretical Computer Science, Université Claude Bernard Lyon 1 (1993) PhD Signal and Image Processing, Télécom ParisTech (2000) Research interests span Computer Vision fundamentals, including Video Analysis, Scene Reconstruction, and Autonomous Visual Learning. His work bridges theory and practice, addressing challenges in medical diagnostics (e.g., colonoscopy analysis, Parkinson's biomarkers) and robotics (e.g., drone navigation, autonomous driving datasets). Recent articles highlight advancements in multimodal data fusion, deep learning optimization, and medical imaging tools. Collaborations include projects on synthetic databases for colon depth estimation and Riemannian geometry for oculomotor analysis. His contributions to open-source frameworks like Video++ and educational initiatives (e.g., DroMOOC on drones) further his impact.

Zachary Tatlockمشاهده پروفایل

دانشیار

• Programming Languages
• Formal Verification
• Compiler Design
• +۴ مورد دیگر

Zachary Tatlock is an Associate Professor at the Paul G. Allen School of Computer Science & Engineering , University of Washington , with a focus on Programming Languages . His research spans formal verification , compiler design , floating-point accuracy , and machine learning frameworks , unified by themes of making tricky code easier to write and ensuring correctness through rigorous proofs and empirical systems. His recent work includes unifying Datalog and equality saturation (PLDI 2023), exploring LLM-driven document markup (Programming with AI 2024), and advancing floating-point error analysis via interactive tools like Odyssey (UIST 2023). He leads the UW PLSE research group and co-organizes events like EGRAPHS and FPTalks . Key collaborations include verifying distributed systems in CakeML (ECOOP 2022) and developing egglog , an e-graph library with relational extensions (PLDI 2023). His teaching includes Solver-Aided Programming (CSE 507) and Grad PL (CSE 505), emphasizing both Greek (formalism) and graphs (empiricism) .

Mohamad Assaadمشاهده پروفایل

استاد

• 5G/6G Systems
• Age of Information
• Resource Optimization
• +۷ مورد دیگر

Mohamad Assaad is a Professor at CentraleSupélec and researcher at L2S (CNRS). He holds the 5G Chair and has authored over 160 publications. His research focuses on 5G/6G systems, Age of Information, resource optimization, and Machine Learning in wireless networks. He has led major projects funded by Qualcomm, Orange, Thales, and Nokia. Assaad is an Editor for IEEE Wireless Communications Letters and has served as TPC co-chair for IEEE conferences. His work spans RIS-aided networks, distributed optimization, and semantic communications. Education: M.Sc. and PhD in Telecommunications from Telecom ParisTech (2002, 2006) Research Interests: 5G/6G systems, Reconfigurable Intelligent Surfaces (RIS), Federated Learning, Massive MIMO, Networked Control Awards: Best paper finalist at IEEE WiOPT 2019, Guest co-editor roles, TPC leadership Grants: €250K/year 5G Chair (2017–2021), Qualcomm €180K (2023–2024), RTE Smart Grids project Labs/Teams: IPHYCOM Team (Intelligent Physical Layers), ILOCOS Team (Optimization & Learning), and collaborations with Orange Labs, Huawei, and Nokia Bell Labs.

Sheng Yangمشاهده پروفایل

استاد

• Information Theory
• Wireless Communications
• MIMO Systems
• +۶ مورد دیگر

Sheng Yang is a full professor at CentraleSupélec, University of Paris-Saclay, and holds an honorary associate professorship at the University of Hong Kong. His research focuses on information theory and its applications to wireless networking, including MIMO systems, non-coherent communication, interference mitigation, and physical layer security. He has authored numerous influential papers and received the 2015 IEEE ComSoc Young Researcher Award. His teaching includes courses on digital communication, information theory, and wireless communications. Educational Background: BE in Electrical Engineering (Jiaotong University, Shanghai, 2001), Engineer Degree and M.Sc. (Telecom ParisTech, 2004), and Ph.D. (Université Pierre et Marie Curie, 2007). Research Interests: Multi-antenna (MIMO) communications, non-coherent systems, hardware impairments, coded caching, federated learning, and the integration of machine learning with communication systems. Notable Contributions: Developed novel rate-splitting strategies for MIMO broadcast channels, analyzed capacity limits of 1-bit quantized MIMO systems, and pioneered CSI compression schemes using context trees. He has supervised over 10 PhD/postdoc students, many now in academia and industry leadership roles. Awards: IEEE ComSoc Young Researcher Award (2015), Associate Editor roles at IEEE Transactions on Information Theory and IEEE Transactions on Wireless Communications. Labs/Teams: Active in the MODESTY, COMEDY, and SYCOMORE research groups at L2S, focusing on system modeling and control. His work intersects energy-efficient communication, distributed computing, and future network architectures.