Sharareh Taghipour
Sharareh Taghipour is Canada Research Chair in Physical Asset Management at Toronto Metropolitan University. She is recognized for her ground-breaking work on novel models for real-time and distributed learning and decision optimization for physical asset management, as well as methods for optimal design and operation of systems. She develops models for real-time and distributed prognostic and health management, prescriptive maintenance, and production scheduling, and advances methodologies for optimal design of systems and supply chain networks with the consideration of reliability, resilience, safety, and sustainability.
She has received multiple awards, including the PEMAC-Maintenance Management Leadership Award, several best paper awards at international competitions, and Ontario’s Early Career Researcher Award. She has an excellent track record of research collaboration with both academia and industry. She has published over 80 journal articles, and is serving as the Associate Editor of several high impact journals including IEEE Transactions on Reliability, Journal of Intelligent Manufacturing, Computers & Industrial Engineering, and Operational Research Society.
Recent Publications
Taghipour S., Namoura H., Ghaleb M., & Sharifi M. (2024). Real-Time Production Scheduling Using a Deep Reinforcement Learning-Based Multi-Agent Approach (external link) . INFOR: Information Systems and Operational Research, 62(2), 186-210.
Asadayoobi N., Taghipour S., & Jaber M.Y. (2023). Optimising stochastic task allocation and scheduling plans for mission workers subject to learning-forgetting, fatigue-recovery, and stress-recovery effects (external link) . Expert Systems with Applications, 229, 120524.
Ghaleb M. and Taghipour S. (2023). Dynamic shop-floor scheduling using real-time information: a case study from the thermoplastic industry (external link) . Computers & Operations Research, 152, 106134.
