معرفی
Shervin Zakeri is a Research Fellow at the Research Institute for Statistics and Information Science, University of Geneva. His research focuses on multi-criteria decision-making (MCDM), integrating machine learning and artificial intelligence into decision support systems, particularly in transportation and supply chain contexts. He holds a Ph.D. from the University of Geneva.
Key research areas include developing novel MCDM methodologies, such as the RWCVP and ARWEN methods, and applying these to real-world problems like autonomous vehicle integration and supplier selection. His work bridges theoretical advancements with practical applications in urban logistics, grey systems theory, and optimization algorithms.
Publications highlight contributions to decision modeling in transportation (e.g., Geneva’s public transport systems) and material selection problems. Collaborations involve interdisciplinary teams addressing challenges in sustainable supply chains and urban planning.
No scientific awards are listed, but his active research portfolio demonstrates significant contributions to operations research and decision analysis.
