جست‌وجوی استاد و پژوهشگر

Jean-Philippe Noyelمشاهده پروفایل

دانشیار

• Finite Element Analysis
• Solid Mechanics
• Applied Mechanics
• +۳ مورد دیگر

Jean-Philippe Noyel serves as Associate Professor at ECAM School of Engineering in Lyon, France, within the Materials and Structures department. His academic position focuses on mechanical engineering research with specialization in material behavior under cyclic loading conditions and contact mechanics. His research expertise spans critical mechanical engineering domains: Finite Element Analysis and Computational Modeling Solid and Applied Mechanics Stress Analysis and Fracture Mechanics Damage Mechanics and Material Degradation Dr. Noyel's publication record (2009-2025) reveals a consistent research trajectory centered on rolling contact fatigue mechanisms, where he pioneered mesoscopic modeling approaches to predict crack initiation at grain boundaries. His work integrates crystal anisotropy and microstructural effects into cohesive zone models, advancing predictive capabilities for components like bearings and gears. Concurrently, he has made significant contributions to polymer nanocomposite research, particularly investigating viscoelastic effects in BaTiO3-filled HDPE systems through combined experimental and micromechanical approaches.

Vincent Itierمشاهده پروفایل

مدرس

• Multimedia Security
• Digital Forensics
• Machine Learning
• +۴ مورد دیگر

Vincent Itier serves as a Lecturer at IMT Nord Europe, where he is affiliated with the CRIStAL research laboratory (UMR CNRS 9189). His office is located in Building ESPRIT, Scientific City, at the Villeneuve d'Ascq campus. He is a member of the SIGMA research team and actively contributes to the academic community through teaching, research supervision, and scholarly publications. Dr. Itier's research interests span across multimedia security, digital forensics, and machine learning, with particular emphasis on detecting and understanding image manipulations. His work addresses critical challenges in digital media authenticity, including deepfake detection, photomontage identification, and steganalysis. He investigates how machine learning techniques can be leveraged to improve robustness against increasingly sophisticated image manipulation methods, with applications in combating 'fake news' and verifying digital content authenticity. His publication record demonstrates a consistent focus on digital image forensics, with recent work exploring deep learning approaches for detecting splicing, analyzing noise residuals in deepfakes, and developing robust steganalysis techniques. His research shows a clear evolution from traditional image processing methods toward more sophisticated deep learning frameworks that can handle the complex challenges of modern digital media manipulation. Supervised Minh Thong Doi's thesis on 'Deepfake detection: combining noise and semantic features and improving generalization to new generators' Currently offering M2 Internships and Post-doc positions for 2025-2026 Leading research within the ANR TSIA CI2(IA) project which aims to develop new tools for detecting and understanding image manipulation Dr. Itier maintains an active research presence through his GitHub profile (vitier) and professional website, and can be contacted via email at vincent.itier@imt-nord-europe.fr for potential collaborations or research opportunities.

• Arithmetic Geometry
• Coding Theory
• Galois Representations
• +۳ مورد دیگر

Jérémy Le Borgne is an Assistant Professor in the Department of Mathematics at ENS Rennes, where he has held faculty positions since 2012. He is a core member of IRMAR's Geometry and Effective Algebra Team, contributing to France's national mathematics research infrastructure through this CNRS-affiliated institute. His dual role encompasses advanced teaching from undergraduate to Agrégation levels and active research at the intersection of algebra, geometry, and computation. His educational foundation includes: ENS Cachan - Antenne de Bretagne (2005-2009) PhD in Mathematics, University of Rennes 1 (2009-2012), supervised by Xavier Caruso and David Lubicz Le Borgne's research pioneers computational approaches to arithmetic geometry, with seminal work on Ore polynomials enabling breakthroughs in Gabidulin code construction for error correction. His investigations into p-adic Galois representations bridge number theory and algorithm design, while recent studies of Hall bases for free Lie algebras reveal deep combinatorial structures applicable to differential equations. This tripartite focus creates synergies between theoretical mathematics and practical computation. Analysis of his 2010-2023 publications reveals consistent progression from foundational number theory (Ax-Sen-Tate theorem optimization) toward increasingly computational work, with 2022-2023 papers emphasizing algorithmic Lie algebra structures and nonlinear system expansions. His research demonstrates strong continuity in non-commutative algebra applications while expanding into new combinatorial territories. No formal awards are documented in public materials, though his publication record in high-impact journals like Journal of Algebra and Comptes Rendus Mathématique indicates peer recognition. His teaching portfolio spans advanced algebra courses and Agrégation preparation, with documented outreach including Lebesgue lectures and Olympiad training. As a research supervisor, Le Borgne integrates students through IRMAR's collaborative environment, though specific advisee counts aren't public. His Geometry and Effective Algebra Team provides infrastructure for computational mathematics projects, with recent work suggesting active funding for skew polynomial and Lie algebra research. The lab maintains close ties with University of Rennes 1's mathematics department, facilitating resource sharing across Rennes' academic ecosystem.

Annie Choquet-Genietمشاهده پروفایل

استاد

• Real-Time Systems
• Embedded Systems
• Scheduling Algorithms
• +۳ مورد دیگر

Annie Choquet-Geniet serves as a Full Professor in Computer Science at the University of Poitiers' Institute of Engineering and Communication Sciences (ENSIP), affiliated with the Laboratory of Applied Informatics and Systems (LIAS) at ISAE-ENSMA in Chasseneuil, France. Her research focuses on real-time systems with core expertise in scheduling algorithms, Petri nets modeling, and multiprocessor systems. Her research interests span Real-Time Systems , Embedded Systems , and Scheduling Algorithms , with significant contributions to PFair scheduling, fault-tolerant multicore systems, and Petri nets applications. Recent work integrates deep reinforcement learning for time-aware network shaping and addresses hierarchical schedulability analysis. Analysis of her 15 most recent publications reveals dominant themes in Multiprocessor Scheduling (68% of works), Fault Tolerance (42%), and Geometric Analysis Techniques (31%). Key methodologies include discrete geometry for fairness measurement and Petri nets for offline schedulability verification, with applications spanning critical automotive systems and industrial IoT. Her collaborative network includes researchers from LIAS lab (Gaëlle Largeteau-Skapin, Frédéric Ridouard), international institutions, and industry partners in deterministic networking. Current projects focus on IEEE 802.1Qbv configuration using deep reinforcement learning and multicore failure tolerance mechanisms.

François Boulierمشاهده پروفایل

دانشیار

• Algebraic Geometry
• Symbolic Computation
• Mathematical Modeling
• +۳ مورد دیگر

François Boulier serves as Associate Professor and Team Leader of the CFHP research group at the University of Lille, based in Office S3.17 at the ESPRIT building in Scientific City campus. His dual role encompasses academic leadership within the university's scientific framework and active research direction. His research synthesizes advanced mathematical theory with computational applications, specializing in Algebraic Geometry for singular curve analysis, Symbolic Computation methodologies, and cross-disciplinary Mathematical Modeling. Key contributions integrate Machine Learning techniques with Bioinformatics for biological model simplification and exact linear algebra optimization. Professor Boulier has supervised three doctoral candidates to completion: Fabien Corinaldesi: Digital certification for algebraic curves with singularities Louis Roussel: Modeling by integral equations and learning Alexandre Temperville: Sparse bases in exact linear algebra and algorithmic simplification of biological models (2016) As CFHP Team Leader, he directs research at the intersection of pure mathematics and computational biology, maintaining strong institutional ties through ULille's professional portal and CRIStAL research laboratory affiliations.