جستجوی استاد راهنمای دانشگاهی

• Fouling and Cleaning in Food Processing
• Dairy Protein Engineering
• Food-Surface Interfaces
• +۵ مورد دیگر

Guillaume DELAPLACE serves as an INRAE Research Director and Laboratory Director of CERTIA at the Materials and Transformations Unit (UMET, CNRS UMR 8207), a joint research entity with the University of Lille. Based at the INRAE PIHM Building (RB2) and UMET's Scientific City (Building C6) in Villeneuve d'Ascq, France, he leads critical work in dairy processing hygiene and fouling mitigation. His position as a senior researcher in France's national agricultural research institute places him at the forefront of food engineering innovation. Research Interests focus on food-surface interfaces in agro-industries , particularly dairy thermal equipment. He investigates protein denaturation kinetics, mineral fraction impacts on fouling, and dimensional analysis of transfer phenomena. His team pioneers biomimetic anti-fouling coatings and ultrasound sensors for real-time clean-in-place monitoring , bridging molecular-scale protein behavior with industrial-scale process optimization. Publication Trends (2020-2024) reveal concentrated efforts in dairy fouling mechanisms, with increasing emphasis on enzymatic cross-linking of casein/whey proteins and calcium-mineral interactions. His work spans predictive modeling, sensor development, and anti-fouling surface engineering, consistently targeting industrial applications in UHT plants and ready-to-drink beverage systems. Over 80% of recent output addresses protein aggregation and deposit management through experimental-numerical approaches. Scientific Awards : No awards, fellowships, or medals were documented in the provided text. Advising and Grants : DELAPLACE has supervised 13 PhD completions and currently mentors 5 doctoral candidates. His projects include PROTEINOLAB (LabCom joint innovation partnership) and participation in ANR/ERC/Interreg initiatives. Collaborations span France (Ingredia Dairy Experts), Brazil (Paulo Peres de Sa Peixoto Jr.), and international networks like LIA, with students transitioning to R&D roles in industry. Labs and Teams : He anchors the Process Interfaces and Materials Hygiene Research team at UMET, specializing in food-surface interactions, transfer phenomena, and mixing dynamics. The group develops fouling prediction tools and anti-adhesion surfaces using plasma deposition and ultrasound, directly addressing dairy industry challenges in heat exchangers and cleaning systems.

Élie Awwadمشاهده پروفایل

دانشیار

• Telecommunication Systems
• Optical Fiber Sensors
• Digital Signal Processing
• +۳ مورد دیگر

Élie Awwad is an Associate Professor (Maître de Conférences) in Optical Communications at Télécom Paris, part of Institut Polytechnique de Paris. He leads research in the Optical Telecommunications (GTO) group within the Information Processing and Communication Laboratory (LTCI) under the Department of Communications and Electronics (Comelec). He joined Télécom Paris in 2019 after working as a Research Scientist at Nokia Bell Labs. He holds M.Eng. degrees in Electrical Engineering from Lebanese University and Telecom Engineering from Télécom Paris (2011), and a PhD in Communications and Electronics from Télécom Paris (2015). His research focuses on optical fiber communications and sensing systems, specializing in: Telecommunication Systems Optical Fiber Sensors Digital Signal Processing Distributed Acoustic Sensing (DAS) Nonlinear interference mitigation Novel optical sensing interrogators His publications demonstrate strong emphasis on distributed fiber sensing techniques (especially phase-sensitive OTDR), coherent MIMO processing, machine learning for optical networks, and free-space optical communications. Recent work integrates quantum cascade laser technology and chaotic encryption methods with optical transmission systems. He currently supervises multiple PhD students and has secured research funding through national CIFRE agreements, ANR SAFER project, CIEDS FIBROUS project, and Celtic-Next AI-NET initiative. His lab focuses on developing advanced monitoring solutions for optical networks and improving distributed sensing capabilities over telecom infrastructure.

Thomas Bonaldمشاهده پروفایل

استاد

• Graph Analysis
• Machine Learning
• Natural Language Processing
• +۳ مورد دیگر

Thomas Bonald is a Professor at Télécom Paris, Institut Polytechnique de Paris, where he heads the Data, Intelligence and Graphs (DIG) team at the Information Processing and Communication Laboratory (LTCI). His academic career spans several decades with significant contributions to the fields of graph analysis, machine learning, and network systems. Professor Bonald's research interests focus on data analysis and machine learning, particularly for large graphs, text data, and time series. He has made substantial contributions to knowledge base construction, with involvement in the YAGO project, and has developed the scikit-network Python library for graph analysis. His work bridges theoretical foundations with practical applications across various domains including natural language processing, network analysis, and knowledge representation. His recent publication trends reveal a strong emphasis on graph-based machine learning techniques, knowledge graph refinement, and hierarchical classification systems. Bonald's research shows increasing integration of large language models with structured knowledge bases, as evidenced by his work on Wikidata taxonomy refinement and YAGO development. His publications span top-tier venues in machine learning, information retrieval, and network systems. Professor Bonald has mentored numerous PhD students throughout his career, including both current students (Roman Plaud, Yiwen Peng, Rajaa El Hamdani) and former students who have gone on to receive notable awards such as the Telecom Paris thesis award (Céline Comte) and the Gilles Kahn award (Mathieu Feuillet). He has been instrumental in developing educational resources in probability, statistics, graph learning, and reinforcement learning. He leads the DIG research team at LTCI, which focuses on developing advanced methods for analyzing complex graph structures and creating practical tools like scikit-network. His work demonstrates a consistent trajectory from theoretical network analysis to practical implementations in knowledge representation and machine learning systems.

Ada Diaconescuمشاهده پروفایل

دانشیار

• Autonomic Computing
• Complex Systems
• Software Engineering
• +۱۲ مورد دیگر

Ada Diaconescu is a Tenured Associate Professor at Télécom Paris (Institut Polytechnique de Paris) since October 2009. She is a member of the Autonomous Critical Embedded Systems (ACES) team within the Information Processing and Communication Laboratory (LTCI) , affiliated with the Computer Science and Networks (Infres) department. Research Focus: Autonomic Computing, Organic Computing, Complex Adaptive Systems, Self-Organising Systems, Smart Grids/Cities/Homes, Nature-Inspired Computing, Socio-Technical Systems Key Methodologies: Decentralised Control, Multi-Agent Systems, Component/Service-Oriented Architectures, Multi-Scale Feedback Loops Her recent publications (2021-2023) explore topics like holonic architectures for self-integration, multi-scale feedback systems in smart environments, and decentralised explanatory frameworks for AI transparency. She co-authored the textbook "Autonomic Computing: Principles, Design and Implementation" (Springer, 2013) and contributed chapters to books on Organic Computing (Springer, 2018) and Self-Aware Systems (Springer, 2017). Scientific Leadership: General Chair of IEEE SASO 2017 Steering Committee Co-Chair of IEEE ACSOS (2019-2021) Co-Organizer of Dagstuhl Seminars (2015, 2018) Doctoral Symposium Co-Chair at FAS* 2019 Teaching: Delivered courses on software engineering, autonomic systems, and complex system modeling at Télécom Paris and other institutions. Collaborations: Active in interdisciplinary research with institutions including Leibniz University, ETH Zurich, Arizona State University, and Lancaster University.

Jean-Claude Moissinacمشاهده پروفایل

مدرس

• Semantic Web Technologies
• Knowledge Graphs
• Machine Learning
• +۳ مورد دیگر

Jean-Claude Moissinac is a Lecturer at Télécom Paris, part of the Institut Mines-Télécom, affiliated with the Image, Data, Signal department and Multimedia research group. He serves as the educational manager for the CPD master's degree program (Digital Project Designer). His research focuses on semantic technologies applied to multimedia systems and knowledge representation. His primary research areas include: Semantic representations of knowledge and knowledge graphs Machine learning techniques for graph-based data analysis Advanced multimedia document processing (production, transport, representation) Semantic web technologies across diverse application contexts His publications demonstrate consistent focus on semantic technologies, knowledge graphs, and multimedia systems, with recent work emphasizing cultural heritage applications and graph-based machine learning techniques. Earlier publications focused on multimedia systems optimization and SVG standards development. He has led multiple research projects including: ILOT Project : Intelligent Learning Object for Teaching SOA2M : Multimodal interface research Data&Musée : Semantic applications for cultural heritage data SemBib : Semantic representation of bibliographic data GeoRacing : Interactive mobile TV services for sporting events He contributes to standardization efforts as co-author of the SVG web standard and participates in academic committees including SVG Open, IEEE International Symposium on Multimedia, and project evaluations for the French National Research Agency.

Thomas Robertمشاهده پروفایل

دانشیار

• Real-Time Systems
• Distributed Computing
• Fault Tolerance
• +۳ مورد دیگر

Thomas Robert is an Associate Professor at Télécom Paris, actively contributing to the AUTONOMOUS CRITICAL EMBEDDED SYSTEMS (ACES) research team under the INFORMATION PROCESSING AND COMMUNICATION LABORATORY (LTCI) . His research spans real-time systems, distributed computing, fault tolerance, and security policy modeling. Research Trends: Recent publications focus on software supply chain security (2025), intrusion detection mechanisms (2024), and mixed-criticality scheduling frameworks like RUN (2015). Earlier works include AADL-based fault tolerance (2010) and real-time error detection (2008). Teaching: Offers courses in programming, operating systems, fault tolerance, and embedded systems at Télécom ParisTech (engineering cycle) and Master 2 programs (SAR, SETI, COMASIC). Collaborations: Works with Laurent Pautet, Jean Leneutre, and colleagues on real-time scheduling and security projects. Tools: Develops PRISM models for system reliability analysis and contributes to fault tolerance practical works.

Aslan Tchamkertenمشاهده پروفایل

استاد

• Information Theory
• Machine Learning
• Communications and Signal Processing

Aslan Tchamkerten is a Professor at Télécom Paris (Institut Polytechnique de Paris), where he leads the Mathematics of Information and Communications (MIC) group within the Communications and Electronics (Comelec) department. His research bridges information theory and machine learning, focusing on theoretical and applied aspects of communication systems and data processing. Education: Physics Engineering Degree (2000) and PhD in Information Theory (2005) from EPFL, postdoctoral research at MIT (2005–2008). His research interests include information theory, machine learning, and their intersections with communication technologies. He co-organized the 2016 thematic program 'Nexus of Information and Computation Theories' at the Institut Henri Poincaré and served as Associate Editor for IEEE Transactions on Information Theory (2016–2019, 2021–2024). He was awarded a Junior Excellence Chair by the French National Research Agency (ANR) in 2009.

• Speech Processing
• Human-Machine Interaction
• Speech Analysis
• +۳ مورد دیگر

Meysam Shamsi serves as an Associate Professor in the Computer Science Department at Le Mans University, where he is a core member of the Language and Speech Technology (LST) research team. He joined Le Mans University in 2020 after completing his doctoral research at the University of Rennes 1's IRISA laboratory. His academic journey includes: Bachelor's degree in Electronic Engineering with specialization in Signal Processing Master's degree in Artificial Intelligence Ph.D. in Computer Science (2020, University of Rennes 1) Dr. Shamsi's research focuses on advanced speech processing systems with emphasis on speaker diarization , emotion recognition , and synthetic speech evaluation . His work integrates lifelong learning and human-in-the-loop methodologies to develop adaptive systems that improve through continuous interaction. Key projects include ESPERANTO and contributions to the LIUM Human Active Correction Platform. Recent publications (2021-2025) demonstrate evolving expertise in cross-lingual adaptation for speech quality assessment and multidimensional emotion modeling. His work shows increasing integration of human feedback mechanisms with deep learning architectures , particularly in speaker diarization and synthetic speech evaluation domains. He actively collaborates within the LST team at Le Mans University's LIUM laboratory, focusing on practical implementations of speech technology systems for real-world applications. Current research directions emphasize scalable solutions for multilingual environments and improved human-AI collaboration frameworks in speech processing.

• Embedded Systems
• Electronic Architecture Design
• Hardware-Software Co-design
• +۵ مورد دیگر

Arnaud Dion is an Associate Professor at ISAE-SUPAERO (Institut Supérieur de l'Aéronautique et de l'Espace), the French Aerospace Engineering Institute, since 2022. Previously, he worked as a research engineer at ISAE from 2004 to 2022. He obtained his PhD from ISAE in 2014. His academic work is centered in the Engineering for Critical Systems (DISC) department, specifically within the Critical Systems Analysis and Design (CASC) research team. Dr. Dion's research interests span multiple domains in aerospace engineering and computing systems: Embedded Systems design and implementation Electronic architecture design for aerospace applications Hardware-software co-design methodologies Satellite navigation algorithms and systems Real-time operational systems Quantum computing applications in engineering His recent work shows a significant expansion into quantum computing, where he has gained hands-on experience with the Q# programming language to explore quantum algorithms and their potential applications. This represents a strategic extension of his established aerospace engineering expertise toward cutting-edge computational approaches that could transform aerospace system design. Dr. Dion has secured research funding from prestigious organizations including the European Space Agency (ESA), French Space Agency (CNES), French Armament Agency (DGA), and regional bodies like Occitanie. His projects address critical challenges in aerospace systems, navigation technologies, and secure communications. As an educator, he heads the Advanced Master on Embedded Systems program and teaches across multiple degree programs, covering topics from fundamental digital design to emerging quantum computing applications. His teaching spans both theoretical concepts and practical implementation in aerospace contexts.

• Reinforcement Learning
• Sequential Decision Problems
• Machine Learning
• +۱ مورد دیگر

Emmanuel Rachelson is a Professor of Machine Learning and Optimization at ISAE-SUPAERO. He is affiliated with the Department of Complex Systems Engineering (DISC) and focuses on Reinforcement Learning and Sequential Decision Problems. His work also spans broader interests in Machine Learning and Operations Research. Founder and co-head of the Supaero Reinforcement Learning Initiative (SuReLI) Contributor to the Data & Decision Sciences Master's curriculum His research integrates decision sciences and optimization within complex systems engineering frameworks. For detailed publications, visit his Google Scholar page .

• Visual Perception
• Image Synthesis
• Computer Graphics
• +۳ مورد دیگر

Samuel DELEPOULLE is an Associate Professor (Maître de Conférences) at the University of the Littoral Opal Coast, France, holding an HDR (Habilitation à Diriger des Recherches) qualification for PhD supervision. His research centers on visual perception and image synthesis within computer graphics and interdisciplinary applications. His core research domains include: Visual Perception mechanisms in human-computer interaction Image Synthesis techniques for realistic rendering Computer Graphics algorithms for Monte Carlo rendering Machine Learning applications in noise reduction Neuroscience collaborations on action representation Computer Vision for biological imaging analysis Recent publications reveal dominant trends in deep learning architectures for rendering optimization, interdisciplinary neuroscience collaborations, and software development for video-microscopy. His work bridges technical computer graphics with cognitive science and biological applications, particularly through the IC research team. Scientific recognition: No specific awards documented in source materials As an HDR-qualified researcher, Delepoulle supervises doctoral candidates though no student names are publicly listed. His grant activity appears concentrated in computer graphics research with biological and neurological applications, evidenced by cross-disciplinary publications. He maintains active affiliation with the IC research team at University of the Littoral Opal Coast, focusing on image processing and computational perception systems.

• Signal Processing
• Remote Sensing
• Environmental Science
• +۳ مورد دیگر

Gilles Delmaire is an Associate Professor specializing in signal processing, hyperspectral imaging, and environmental science. His research spans topics like super-resolution hyperspectral multisensor fusion , tensor decomposition , and butterfly species classification using advanced computational methods. Key research areas: Signal Processing, Remote Sensing, Environmental Science, and Machine Learning. Recent work focuses on hyperspectral data restoration , insect tracking algorithms , and air quality analysis in Mediterranean regions. Collaborations include institutions in France, Greece, Portugal, and Cyprus, with publications in IEEE, Pattern Analysis and Applications, and Science of the Total Environment.

• Dielectric Spectroscopy
• Recycling of Electronic Waste
• Liquid Crystal Characterization
• +۵ مورد دیگر

Pierre-Alexandre Hébert is an Associate Professor at the University of the Littoral Opal Coast. His research spans interdisciplinary domains including dielectric material analysis , electronic waste recycling , and machine learning applications for environmental monitoring. Key research focus: Liquid Crystal recycling from E-waste using dielectric spectroscopy Contributions to phytoplankton detection via automated systems and clustering algorithms Collaborations across France, Turkey, Italy, and Ireland His recent publications (2021-2023) emphasize sustainable materials processing, particularly dielectric characterization of recycled liquid crystals for circular economy applications. Earlier work (2008-2018) showcases expertise in image processing , phytoplankton classification , and data clustering techniques. Collaborative projects include: JERICO NEXT (2018), ISyDMA'6 (2021), and SFGP (2022) conferences. Current affiliations involve laboratories at Université du Littoral Côte d’Opale (ULCO) and Université d’Artois (UA).

• Complex systems
• Combinatorial optimization
• Evolutionary computation
• +۵ مورد دیگر

Sebastien Verel is a Researcher at the Laboratoire d'Informatique de l'Université du Littoral Côte d'Opale (LISIC) . His work focuses on complex systems, combinatorial optimization, evolutionary computation, and fitness landscape analysis. Research Interests: Multiobjective optimization, metaheuristics, adaptive algorithms, and simulation-based modeling Collaborations: Active in international conferences (GECCO, EvoCOP, PPSN) with teams from UK, Italy, Australia, and Morocco Key Publications (2023-2025) address topics like: Pareto local optimal networks for multiobjective landscapes Surrogate-assisted optimization using Walsh decomposition Fitness landscape analysis across ML models and protein engineering Urban mobility benchmarks (bus spacing in Calais)

• Color Image Representation
• Color Space Selection
• Color Texture Feature Selection
• +۳ مورد دیگر

Nicolas Vandenbroucke is a researcher affiliated with the Université du Littoral Côte d'Opale. His work focuses on color and hyperspectral imaging, texture classification, and biomedical applications. Research Interests Color image representation and segmentation Hyperspectral texture descriptors for pattern recognition Dimensionality reduction via feature selection Biomedical imaging for multiple sclerosis diagnosis Machine vision applications in environmental monitoring Selected Publications Recent work on lightweight CNN models for marine plastic debris classification (2025) Hyperspectral imaging systems for aquatic drone-based waste detection (2024) Advancements in Local Binary Pattern algorithms for texture analysis (2023) Comparative studies of color vs. hyperspectral imaging (2022) Clustering-based feature selection for high-dimensional data (2021) Technical Contributions Development of remote hyperspectral imaging systems Design of compact descriptors for color texture classification Optimized hierarchical warping for medical diagnostics LBP histogram selection scores for supervised learning