| Publication | Year of publication | Type of publication |
|---|---|---|
| MORADKHANI, N., F. BENABEN, B. MONTREUIL, M. LAURAS, T. CERABONA, C. L. DUFF, L. FAUGERE, J. JEANY, "A force-inspired paradigm for performance-based decision support—Physics of Decision application in nonlinear dynamical systems", Journal of Industrial Information Integration, 2024, vol. 41, pp. 100656 | 2024 | Journal article |
| MORADKHANI, N., F. BENABEN, B. MONTREUIL, M. LAURAS, J. JEANY, L. FAUGERE, "Multi-criteria performance analysis based on Physics of Decision — Application to COVID-19 and future pandemics", IEEE Transactions on Services Computing, 2023, vol. 16, no. 3, pp. 1987-1998 | 2023 | Journal article |
| BENABEN, F., L. FAUGERE, B. MONTREUIL, M. LAURAS, N. MORADKHANI, T. CERABONA, J. GOU, W. MU, "Instability is the norm! A physics-based theory to navigate among risks and opportunities", Enterprise Information Systems, 2022, vol. 16, no. 6 | 2022 | Journal article |
Nafe Moradkhani is an Assistant Professor in AI and Data Science at KEDGE Business School, based at the Bordeaux campus within the Operations Management and Information Systems department. His research focuses on data-driven optimization, machine learning, and supply chain analytics, with a strong emphasis on urban logistics and operational resilience. Nafe holds a Ph.D. in Computer Science and Industrial Engineering, awarded jointly by IMT Mines Albi and the Georgia Institute of Technology. His doctoral work introduced innovative decision support systems for managing complex socio-technical systems, drawing on physical principles and advanced modeling techniques. He has a particular interest in improving supply chain efficiency and sustainability through AI-driven solutions. At KEDGE, Nafe is part of the Center of Excellence in Supply Chain Innovation and Transportation (CESIT), where he contributes to cutting-edge research and collaborative projects with industry partners. His role includes teaching undergraduate, graduate, and post-graduate courses, publishing in leading academic journals, and working on international research initiatives. With a blend of academic rigor and real-world application, Nafe aims to advance knowledge in AI and supply chain management, addressing both economic and societal challenges through innovative research and teaching.