Prof. Linwei Xin
Booth School of Business, University of Chicago
Linwei Xin is an associate professor of Operations Management at Booth School of Business, University of Chicago. His primary research is on inventory and supply chain management: designing models and algorithms for organizations to effectively "match supply to demand" in various contexts with uncertainty. His research using asymptotic analysis to study stochastic inventory theory has been recognized with several INFORMS paper competition awards, including the Applied Probability Society Best Publication Award (2019), First Place in the George E. Nicholson Student Paper Competition (2015), Second Place in the JFIG Paper Competition (2015), and a finalist in the MSOM Student Paper Competition (2014). His work 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 more than 65% algorithm-adoption rate within Alibaba’s own supermarket brand Tmall Mart. His research with JD.com on dispatching algorithms for robots in intelligent warehouses was recognized as a finalist for the INFORMS 2021 Franz Edelman Award, with an estimate of billions of dollars in savings. His research has been published in journals such as Operations Research, Management Science, Mathematics of Operations Research, and INFORMS Journal on Applied Analytics.