Biography

Dr. Amin Kaboli is a lecturer at Swiss Federal Institute of Technology in Lausanne (EPFL), specializing in Supply Chain and AI. He coaches and advises tech founders, business executives, and numerous AI startups across industries. His expertise in AI, supply chain, and operational excellence has benefited companies such as Philip Morris International, Nespresso, Rolex, Patek Philippe,  Haleon, Sika, and the Sauber Motorsport - Alfa Romeo F1 Team. Amin holds advanced leadership diplomas from IMD Business School and a Ph.D. in Manufacturing Systems & Robotics from EPFL. You may watch his TEDx talk on “Leading Change Consciously” here. 

Selected Publications

· Bibri, E. S., Krogstie, J., Kaboli, A., & Alahi, A. (2023). Smarter eco-cities and their leading-edge artificial intelligence of things solutions for environmental sustainability: A comprehensive systematic review. Environmental Science and Ecotechnology, 100330.
· Bouquet, P., Jackson, I., Nick, M., & Kaboli, A. (2023). AI-based forecasting for optimised solar energy management and smart grid efficiency. International Journal of Production Research, 1-22.
· Fatemi, M. S., Ghodratnama, A., Tavakkoli-Moghaddam, R., & Kaboli, A. (2022). A multi-functional tri-objective mathematical model for the pharmaceutical supply chain considering congestion of drugs in factories. Research in Transportation Economics, 92, 101094.
· Jalayer, M., Kaboli, A., Orsenigo, C., & Vercellis, C. (2022). Fault detection and diagnosis with imbalanced and noisy data: A hybrid framework for rotating machinery. Machines, 10(4), 237.
· Eghbali-Zarch, M., Tavakkoli-Moghaddam, R., Dehghan-Sanej, K., & Kaboli, A. (2022). Prioritizing the effective strategies for construction and demolition waste management using fuzzy IDOCRIW and WASPAS methods. Engineering, Construction and Architectural Management, 29(3), 1109-1138.
· Jalayer, M., Jalayer, R., Kaboli, A., Orsenigo, C., & Vercellis, C. (2021, July). Automatic visual inspection of rare defects: A framework based on gp-wgan and enhanced faster R-CNN. In 2021 IEEE International Conference on Industry 4.0, Artificial Intelligence, and Communications Technology (IAICT) (pp. 221-227). IEEE.
· Kaboli, A., Glardon, R., Zufferey, N., & Cheikhrouhou, N. (2019). Replenishment behaviour in sequential supply chains. International Journal of Logistics Systems and Management, 32(3-4), 322-345.
· Kaboli, A. (2013). Trust and inventory replenishment decision under continuous review system (No. THESIS). EPFL.
· Tabari, M., Kaboli, A., Aryanezhad, M. B., Shahanaghi, K., & Siadat, A. (2008). A new method for location selection: a hybrid analysis. Applied Mathematics and Computation, 206(2), 598-606.
· Tavakkoli-Mogahddam, R., Ghezavati, V. R., Kaboli, A., & Rabbani, M. (2008). An efficient hybrid method for an expected maximal covering location problem. New Challenges in Applied Intelligence Technologies, 289-298.
· Kaboli, A., Aryanezhad, M. B., Shahanaghi, K., & Niroomand, I. (2007, October). A new method for plant location selection problem: a fuzzy-AHP approach. In 2007 IEEE International Conference on Systems, Man and Cybernetics (pp. 582-586). IEEE.