Professor Shi’s research is focused on the design of efficient algorithms with analyzed performance for fundamental multi-stage stochastic optimization models, arising in the context of inventory and supply chain management, revenue management, as well as health-care management. These fundamental multi-stage stochastic models are typically hard to solve to optimality, both theoretically and in practice. He constructs efficient heuristics that provide provably near-optimal policies for these hard models. In doing so he develops novel techniques that are applicable in a broad class of models. He won the first prize of the 2009 George Nicholson Student Paper Competition.