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About

Yeming Gong is a prominent operations research scholar whose work centers on automated warehouse systems, robotic logistics, and smart fulfillment technologies. His research has fundamentally advanced the understanding of Robotic Mobile Fulfillment Systems (RMFS), the technology pioneered by companies like Amazon Robotics, where autonomous robots transport movable shelves to human order pickers. Through rigorous queueing network models and optimization frameworks, Gong has tackled critical operational challenges including workstation assignment rules, battery charging and swapping strategies, and customer priority classifications — contributions that have collectively garnered over 550 citations. Among his most influential works, his 2017 trilogy on RMFS design established foundational performance benchmarks and practical operating policies that researchers and practitioners continue to reference widely. His later investigations expanded into emerging technologies such as robotic sorting systems and rack-climbing autonomous robots, reflecting his ability to anticipate and shape the next frontier of warehouse automation. His 2023 study on battery management in self-climbing robotic warehouses demonstrates his continued engagement with real-world sustainability and operational efficiency challenges. For students and researchers in supply chain management, industrial engineering, or logistics automation, Gong's body of work offers both rigorous analytical tools and actionable insights into the rapidly evolving landscape of intelligent fulfillment systems.