جستجوی استاد راهنمای دانشگاهی

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.

Patrick Girardمشاهده پروفایل

استاد

• Human-Computer Interaction
• Task Modeling
• Interactive Systems Design
• +۳ مورد دیگر

Patrick Girard is a Full Professor in Data Engineering at ISAE-ENSMA (Institut Supérieur de l'Aéronautique et de l'Espace - École Nationale Supérieure de Mécanique et d'Aérotechnique) in France. He is a member of the Data Engineering Team within the LIAS (Laboratoire d'Ingénierie des Applications de la Sensorique) laboratory, with dual affiliations at ISAE-ENSMA in Chasseneuil and ENSIP in Poitiers. Professor Girard's research focuses on Human-Computer Interaction , with particular expertise in task modeling , interactive systems design , and programming by demonstration techniques. His work spans theoretical foundations to practical applications in model-based development, user interface design methodologies, and educational technology for programming. He has made significant contributions to task model validation, simulation techniques, and the application of these principles in complex systems engineering, particularly in aerospace contexts. His publication history demonstrates a consistent evolution from foundational work on programming by demonstration and task-oriented architectures in the 1990s to more recent applications in complex systems engineering and avionics. A distinctive trend in his work is the integration of formal methods with practical HCI approaches, creating robust frameworks for developing user-centered interactive systems with safety-critical applications. Professor Girard has mentored numerous researchers throughout his career, with frequent collaborations showing sustained relationships with scholars like Loé Sanou, Nicolas Guibert, and Thomas Lachaume. His research has involved multiple interdisciplinary projects, often connecting academic research with industrial applications, particularly in the aerospace sector. Within the LIAS laboratory, Professor Girard works in the Data Engineering Team alongside colleagues in Automatic Control and Real Time research groups. The laboratory maintains strong industry partnerships, especially with aerospace companies, enabling practical implementation of theoretical research in real-world engineering contexts. His work bridges computer science theory with practical engineering applications, particularly in the French aerospace ecosystem.

Guillaume Mercereمشاهده پروفایل

استاد

• System Identification
• Model Learning
• Automatic Control
• +۶ مورد دیگر

Guillaume Mercere is a Full Professor in Automatic Control and Systems at ENSIP (Ecole Nationale Supérieure d'Ingénieurs de Poitiers), University of Poitiers. He maintains dual affiliations with Laboratory LIAS at both ENSIP in Poitiers and ISAE-ENSMA in Chasseneuil, conducting research in system identification and control theory. Professor Mercere teaches automatic control and signal processing at the Master's level, with additional expertise in numerical optimization, machine learning, and time series analysis. His teaching materials are available upon request, reflecting his commitment to educational transparency. Research Focus: Model learning, system identification, estimation theory, state space modeling, gray box modeling, linear parameter varying (LPV) systems, linear fractional representation (LFR), and subspace-based methods Application Areas: Electrical engineering, aeronautics, heat transfer, flexible/cable-driven manipulators, vehicle tire/road interactions, and image processing Analysis of his recent publications reveals a strong emphasis on recursive estimation methods (particularly total least squares), theoretical developments in LPV system representations, predictive control methodologies, and noise covariance estimation for Kalman filtering. His work bridges theoretical advances in identification methodologies with practical applications across multiple engineering domains, demonstrating both depth and breadth in his research program. Professor Mercere leads the Automatic Control Team at Laboratory LIAS, where he collaborates with researchers on theoretical and applied projects. His research group focuses on developing identification methodologies with practical implementation in real-world engineering systems, maintaining an active publication record through 2025 that demonstrates ongoing contributions to the field of system identification and control engineering.

Lili Zhengمشاهده پروفایل

استاد

• Consumer Behavior
• Online Consumer Decision Making
• Emotions and Technology Adoption
• +۷ مورد دیگر

Dr. Lili Zheng is a Professor and Researcher in Marketing at Excelia, La Rochelle, France, specializing in consumer behavior in the digital age, technology adoption, and digital business transformation. Her work bridges academic research and practical applications in digital marketing and e-commerce. Her educational credentials include: Habilitation à diriger des recherches (HDR), Sciences de Gestion, Université Paris Nanterre (2022) PhD in Management Sciences, Marketing, Université de Grenoble (2013) Master of Science in Marketing, Université de Rennes 1 (2010) Professor Zheng's research centers on consumer psychology in digital environments, examining how emotions, cultural factors, and risk perception influence online decision-making, satisfaction, and loyalty. Her methodologies integrate cross-cultural comparative studies with advanced survey techniques, yielding insights applicable to global e-commerce strategies and technology design. Recent work explores AI-driven gamification in cultural institutions and mobile application engagement dynamics. Her publication trajectory (2014-2025) reveals evolving focus from foundational cross-cultural risk perception studies to contemporary investigations of AI in museums and mobile app psychology, consistently emphasizing emotional drivers in digital consumer behavior across diverse contexts including banking, tourism, and recycling. She has received significant recognition including: Eiffel France Excellence Scholarship China Excellence Scholarship Mobility grant from Auvergne-Rhône-Alpes Region Professor Zheng actively supervises doctoral research on blue tourism and mobile payment adoption while coordinating international projects with institutions like UQAM. She serves on scientific committees for conferences including IBIMA and co-organizes the International AI Research Day, demonstrating leadership in knowledge dissemination. Her editorial contributions to journals like Journal of Business Research and conference proceedings further establish her influence in marketing sciences. As a member of AIM, FNEGE, AFM, and AFREN, she actively shapes research discourse through peer review and collaborative initiatives focused on digital transformation in business contexts.

• 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.

Maxime Folschetteمشاهده پروفایل

دانشیار

• Computer Science
• Formal Methods
• Bioinformatics
• +۳ مورد دیگر

Maxime Folschette is an Associate Professor at Centrale Lille Institut, affiliated with the CRIStAL research laboratory (UMR 9189) and the BioComputing research group. His position combines teaching responsibilities at Centrale Lille and its internal school IG2I with active research in computational biology and formal methods. His primary research focuses on the analysis and learning of dynamical biological models, with particular emphasis on formal methods applied to biological regulatory networks. His work spans multiple domains including Parameters Inference, Static Analysis, Polyadic μ-calculus, and Hoare Logic, all applied to biological systems modeling. Folschette's publications demonstrate a strong trend toward developing computational frameworks that bridge theoretical computer science with practical biological applications. His recent work shows increasing focus on hybrid modeling approaches that combine discrete and continuous dynamics, logical learning techniques for network inference, and applications in medical domains such as diabetes modeling and cancer research. ILP best paper award during IJCLR'2021 Best Paper Award for BIOINFORMATICS'2024 As an advisor, Folschette currently mentors two PhD students (Madeleine Eyraud and Karim Raqbi) and has successfully guided two PhD students to defense (Honglu Sun in 2023 and Danilo Dursoniah in 2024). His research is supported through multiple collaborations across France and Japan, particularly with the BioComputing team at CRIStAL. His laboratory work focuses on developing computational tools like Pint, Hybrid Hoare Logic tool, key-pipline, INEX-MED, and pyBRAvo for biological network analysis.

• Human-Computer Interaction
• Task Modeling
• User Interface Design
• +۳ مورد دیگر

Sybille Caffiau serves as a Lecturer in Data Engineering at ISAE-ENSMA's School of Engineering, affiliated with the LIAS laboratory across both ENSIP (Poitiers) and ISAE-ENSMA (Chasseneuil) campuses. Her research focuses on Human-Computer Interaction with specialization in task modeling and user interface validation. Her research interests span Human-Computer Interaction , Task Modeling , and User-Centered Design . She develops and evaluates tools like K-MADe for modeling user activities, with emphasis on empirical validation of task modeling approaches. Her work bridges cognitive science principles with practical software engineering applications, particularly in educational technology and interactive system design. Analysis of her publication trends reveals consistent contributions to HCI conferences and journals since 2006, with increasing focus on tool development (notably K-MADe) and empirical validation methodologies. Her recent work demonstrates strong interdisciplinary connections between cognitive modeling, software engineering, and educational technology. No scientific awards or fellowships are documented in the available materials. While her collaborative network includes prominent researchers like Laurent Guittet and Patrick Girard, specific details about student advising or research grants are not provided in the source materials. Her thesis work (2009) established foundations for model-driven interactive application design. She operates within the LIAS laboratory's Data Engineering team, contributing to research on interactive systems and task modeling frameworks. The KMADe environment represents her primary software contribution for activity description and task modeling.

Yassine Ouhammouمشاهده پروفایل

دانشیار

• Real-Time Systems
• Embedded Systems
• Model-Based Design
• +۶ مورد دیگر

Yassine Ouhammou is an Associate Professor in computer science at École Nationale Supérieure de Mécanique et d'Aérotechnique (ENSMA), where he is a member of the "Real-Time and Embedded Systems" research team at LIAS laboratory. His work focuses on critical real-time embedded systems with applications in avionics, drones, and control command systems. His research interests include: Software architectures for critical real-time embedded systems Design and analysis of critical real-time systems regarding their temporal performances Model-based design using domain specific languages (MoSaRT, AADL, Capella, Time4Sys) Real-time scheduling and dimensioning Knowledge repositories for expertise capitalization, reuse and reproducibility Collaborative engineering for complex systems design Model-driven engineering and formal methods Dr. Ouhammou's publication record shows consistent contributions to real-time systems, embedded architectures, and model-based approaches. His recent work demonstrates increasing emphasis on drone technology and avionic applications, with numerous collaborations on autopilot design, scheduling optimization, and verification methodologies. His research bridges theoretical computer science with practical aerospace engineering challenges, addressing safety-critical aspects of embedded systems. Professional service includes: PC Member of MEDES 2020, INISTA 2020, WIMS, SADASC 2020 PC Chair of DETECT 2019 General Co-Chair of RTNS 2018 PC Member of multiple international conferences since 2017 Dr. Ouhammou collaborates extensively with researchers in the field of real-time systems, particularly with Emmanuel Grolleau and other members of the LIAS laboratory. His work often involves interdisciplinary teams addressing complex challenges in aerospace and embedded systems engineering, with practical applications in drone technology and avionic systems.