Apoya a Reza Shahin

Reza Shahin, Ph.D. in Computer Science with a focus on Operations Research, specializes in developing and implementing advanced optimization models, including Mixed-Integer Linear Programming (MILP) and machine learning techniques, for complex industrial and supply chain systems. His expertise includes applying machine learning methods, such as reinforcement learning and data-driven decision-making, to enhance operations in logistics, scheduling, and intelligent manufacturing.

He has collaborated on high-impact projects, notably optimizing inventory management during the COVID-19 pandemic (a case study of Quebec province), and has extensive experience in leveraging computational tools like CPLEX, Python, and machine learning libraries such as TensorFlow and scikit-learn. Backed by numerous publications in international journals and conferences, he has a solid research portfolio in areas like digital manufacturing, healthcare analytics, and supply chain resilience.

With a proven track record in teaching and mentoring, he has served as a lecturer for operations research, operations management, and production planning courses. He combines technical expertise with creativity, adaptability, and problem-solving skills, making him an effective collaborator in diverse and interdisciplinary settings.