جست‌وجوی استاد و پژوهشگر

Adrien Busnot Laurentمشاهده پروفایل

پژوهشگر

• Numerical integration of stochastic differential equations
• Geometric numerical integration
• Algebraic and geometric structures in numerical analysis
• +۴ مورد دیگر

Adrien Busnot Laurent is a permanent researcher (Chargé de recherche) at INRIA Rennes in the MINGuS (Multi-scale numerical geometric schemes) team. He previously held a postdoctoral position at the University of Bergen working on the CODYSMA project (Computational Dynamics and Stochastics on Manifolds) with Hans Z. Munthe-Kaas, and completed his Ph.D. in Mathematics at the University of Geneva under Gilles Vilmart's supervision. His research focuses on numerical methods for stochastic differential equations, with particular emphasis on geometric numerical integration, algebraic structures in numerical analysis, and numerical integrators on manifolds. He has made significant contributions to the theory of exotic aromatic B-series, which provide a framework for analyzing high-order integrators for ergodic stochastic differential equations. Adrien's publication record shows consistent high-impact contributions in top journals including Foundations of Computational Mathematics, SIAM Journal on Scientific Computing, and Forum of Mathematics, Sigma. His work bridges theoretical mathematics with practical numerical algorithms, with applications in molecular dynamics and statistical physics. He has been recognized with the SWICCOMAS prize 2022 and the Henri Fehr prize for his Ph.D. thesis. As PI of the ANR JCJC project MaStoC, he leads research on manifolds and stochastic computations, with plans to open postdoc positions from September 2026. Adrien is actively involved in the academic community, co-organizing conferences including GeoStoch 2026 and CANUM 2026, and organizing a research seminar in applied mathematics at ENS Rennes. He also participates in outreach activities and supports diversity in mathematics.

• Control Theory
• Quantum Systems
• Partial Differential Equations
• +۴ مورد دیگر

Thomas Chambrion is a Professor of Applied Mathematics at the University of Burgundy, affiliated with the engineering school ESIREM and the Institute of Mathematics of Burgundy (IMB). He leads the Statistics, Probability, Optimization and Control (SPOC) research team at IMB, focusing on theoretical and applied aspects of control systems. His research encompasses: Quantum control : Infinite-dimensional bilinear systems, Schrödinger/Gross-Pitaevskii equations, molecular rotation Optimization : Real-time constraints, switching systems, signal denoising algorithms Cross-disciplinary applications : Fluid dynamics (swimmer locomotion), MRI pulse design, industrial process modeling Recent publications (2020-2024) show a strong emphasis on controllability analysis for quantum systems and development of efficient algorithms for signal processing. His work frequently employs geometric methods, perturbation theory, and statistical modeling. No grants or awards are detailed in the available information. His laboratory, SPOC, operates within the Institute of Mathematics of Burgundy, collaborating extensively with researchers in quantum physics and engineering.

Sébastien Thomasseyمشاهده پروفایل

دانشیار

• Supply Chain Management
• Production Optimization
• Sales Forecasting
• +۴ مورد دیگر

Sébastien Thomassey is an Associate Professor at the National School of Arts and Textile Industries (ENSAIT), specializing in AI-driven solutions for textile engineering. His research focuses on optimizing fashion supply chains through machine learning applications in production management, sales forecasting, and sustainable manufacturing. He leads the Research Human Centered Design Group and coordinates multiple EU-funded projects including H2020's FBD-BModels and Erasmus+'s Digital Fashion initiative. His core research integrates: Supply chain optimization using AI forecasting models Textile manufacturing process automation Sustainable production lifecycle management Human-machine interaction in industrial settings Recent publications demonstrate strong emphasis on AI applications in textile anomaly detection (2024), digital twin technology (2023), and reinforcement learning for process optimization (2021). Awards include: Top 25 Most Cited Article in International Journal of Information Management (2021) He coordinates €5M+ in collaborative grants including: Fashion Trends 4.0 (Région Hauts-de-France) SMDTex Erasmus Mundus doctorate program H2020 FBD-BModels textile supply chain project Leads the Human Centered Design Group developing sensor-based textile tracking systems and industrial AI solutions.

Loïc Adamمشاهده پروفایل

دانشیار

• Incremental Preference Elicitation
• Multicriteria Decision Making
• Decision Theory under Risk and Uncertainty
• +۸ مورد دیگر

Loïc Adam serves as an Associate Professor in Data Engineering at ISAE-ENSMA since 2024, concurrently holding a lecturer position in Digital Information. Previously, he was an ATER at Université de Technologie de Compiègne (2023-2024) where he taught operational research and data analysis courses. He completed his PhD in Computer Science at UTC in 2023 and currently serves on ENSMA's improvement council and scientific expertise commission (2025-2027). His research spans decision theory under risk and uncertainty, with core expertise in incremental preference elicitation, multicriteria decision-making, and uncertainty modeling through possibility theory and belief functions. He actively investigates information fusion, machine learning applications, and game-theoretic approaches to preference learning, focusing on resolving inconsistent preferences and developing robust decision support frameworks under severe uncertainty. Adam's publication record (2020-2024) reveals consistent contributions at the intersection of artificial intelligence and decision science, particularly in preference modeling and uncertainty quantification. His work demonstrates methodological innovation in applying possibility theory to inconsistency resolution and developing imprecise probabilistic models for label ranking, with publications spanning top venues in AI, fuzzy systems, and decision theory. Scientific Awards: No major awards or fellowships were documented in the source material. He currently supervises M2 intern Aicha AIT HAMMOUCH on auto-detection of erroneous models through personalized data elicitation in uncertain environments. As a member of LIAS Laboratory's Data Engineering team, he collaborates across ENSIP (University of Poitiers) and ISAE-ENSMA sites, contributing to interdisciplinary projects that bridge theoretical decision science with real-world engineering applications in control systems and real-time data processing.

• Data Analytics
• Business Analytics
• Operations Research
• +۳ مورد دیگر

Dr Arshad Raza Syed serves as a Lecturer in Data Analytics & Business Analytics within the Department of Global Business and Enterprise at Ulster University Business School, based at the Derry~Londonderry campus. His academic role focuses on delivering high-quality education in data-driven business decision making and analytical methodologies. Educational Background: PhD: Systemic Problems related to Multiple Stakeholders in Information Technology adoption and use in Organizations: A Systems Thinking Perspective, Edith Cowan University (2012) Master: Visualization with Spline using a Genetic Algorithm, King Fahd University of Petroleum and Minerals (2001) Bachelor: A Computer based Simulation of a Diesel Engine Combustion Process, NED University of Engineering and Technology, Karachi (1997) Dr Syed's research expertise encompasses Data Analytics , Business Analytics , Operations Research , Stochastic Processes , Software Engineering , and Complex Systems . His work addresses inherent complexities in organizational IT adoption and develops innovative approaches for managing stochastic failures in multistage processes. Recent publications (2024-2025) reveal a clear trajectory in algorithmic development for discrete approximation of continuous distributions and reliability engineering under uncertainty, highlighting his dual focus on theoretical rigor and practical business applications. No scientific awards or major grants are documented in the available profile information. There is no mention of specific laboratories or research teams led by Dr Syed in the provided materials.