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Linwei Xin joined the School of Operations Research and Information Engineering (ORIE) at Cornell University as an Associate Professor in July 2025. Prior to Cornell, he was an Associate Professor in Operations Management at the University of Chicago Booth School of Business. His research specializes in inventory supply chain management, designing cutting-edge models and algorithms that enable organizations to effectively balance supply and demand in contexts of uncertainty. Xin’s research, recognized in the prestigious INFORMS paper competition, focuses on stochastic inventory theory and has received several awards including the George E. Nicholson Student Paper Competition and the Applied Probability Society Publication Award. His recent interests delve into the role of AI in supply chains influenced by labor shortages, reshoring trends, and global supply chain disruptions. He employs tools such as neural networks, VC theory, applied probability, online optimization/learning, and random graph theory to address challenges posed by AI-driven automation. Xin has targeted issues in inventory management, robotics automation in modern warehousing, dual-sourcing, real-time order fulfillment, omnichannel strategies, and transportation network design. His research on implementing multi-agent deep reinforcement learning techniques in Alibaba’s inventory replenishment system has achieved a 65% algorithm adoption rate in Tmall Mart, and he was a finalist for the INFORMS 2022 Daniel H. Wagner Prize. Additionally, his work on dispatching algorithms for robots in JD.com’s intelligent warehouses has been recognized as a finalist for the INFORMS 2021 Franz Edelman Award, with estimated annual savings in hundreds of millions of dollars.
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