Sang Won Yoon

Sang Won Yoon is a Professor at the School of Systems Science and Industrial Engineering, Binghamton University. He holds a PhD from Purdue University, an MS from Korea University, and a BS from Jeonbuk National University. His research focuses on smart manufacturing, decentralized decision modeling, and large-scale data mining optimization. He specializes in applying machine learning and neural networks to improve manufacturing processes, particularly in solder joint prediction, thermal profile optimization, and automation in pharmaceutical distribution.

Research Interests include real-time control systems, quality enhancement in surface mount technology (SMT), and healthcare supply chain automation. His work bridges theoretical models with practical applications, such as optimizing reflow oven profiles and AGV systems.

Recent publications highlight advancements in physics-informed neural networks, explainable AI for defect prediction, and simulation-driven process optimization. He collaborates with the PRISM Center, focusing on global research networks in systems integration. His contributions span smart manufacturing, healthcare automation, and environmental sustainability in energy systems.

Professional Activities include advising on pharmacy robotic systems, discrete event simulation models for healthcare operations, and renewable energy feasibility studies. He actively publishes in top-tier journals and conferences, emphasizing interdisciplinary solutions for industrial challenges.