Linwei Xin

Linwei Xin joined the School of Operations Research and Information Engineering (ORIE) at Cornell as an Associate Professor in July 2025. Prior to Cornell, he was an Associate Professor of Operations Management at the University of Chicago Booth School of Business. He specializes in inventory and supply chain management, where he designs cutting-edge models and algorithms that enable organizations to effectively balance supply and demand in various contexts with uncertainty.

Xin’s research using asymptotic analysis to study stochastic inventory theory is renowned and has been recognized with several prestigious INFORMS paper competition awards, including First Place in the George E. Nicholson Student Paper Competition in 2015 and the Applied Probability Society Best Publication Award in 2019. Xin’s recent interest focuses on AI for supply chains, driven by labor shortages, reshoring trends, global supply chain disruptions, and e-commerce growth. He leverages various tools such as neural networks, VC theory, applied probability, online optimization/learning, and random graph theory to address emerging challenges arising from AI-driven automation. His work targets problems in inventory management, robotics and automation in modern warehousing, dual-sourcing, real-time order fulfillment, omnichannel, and transportation network design. His research on implementing state-of-the-art multi-agent deep reinforcement learning techniques in Alibaba’s inventory replenishment system was selected as a finalist for the INFORMS 2022 Daniel H. Wagner Prize, with over 65% algorithm-adoption rate within Alibaba’s own supermarket brand Tmall Mart. His research on designing dispatching algorithms for robots in JD.com’s intelligent warehouses was recognized as a finalist for the INFORMS 2021 Franz Edelman Award, with estimated annual savings in the hundreds of millions of dollars.

Xin currently serves as an associate editor for Operations Research, Management Science, Manufacturing & Service Operations Management, and Naval Research Logistics.