Haoxiang Yang

Haoxiang Yang is an assistant professor at the School of Data Science, the Chinese University of Hong Kong, Shenzhen. He graduated with a PhD degree from the Department of Industrial Engineering and Management Sciences at Northwestern University.  

Haoxiang's research focuses on the theory of optimization under uncertainty, specifically in stochastic programming and robust optimization, integer programming and nonlinear programming, with its applications in energy systems, supply chain and logistics, disaster relief and sports analytics.

News

• June 2026: PhD student Zhuo Zhang will give a talk at SIAM-OP26, titled "Globally Converging Algorithm for Multistage Stochastic Mixed-Integer Programs Via Enhanced Lagrangian Cuts."

• June 2026: I will give a talk at SIAM-OP26, titled "Optimizing Staged-Alert Thresholds for Pandemic Control under Decision-Dependent Uncertainty."

• May 2026: I gave a talk at JOPT-2026, titled "Stochastic Mixed-Integer Programming Approach to Integrated Protection and Restoration Planning for Interdependent Infrastructure Networks."

• April 2025: Our manuscript "Globally Converging Algorithm for Multistage Stochastic Mixed-Integer Programs via Enhanced Lagrangian Cuts" was released on Optimization-Online.

• June 2021: I joined the School of Data Science at the Chinese University of Hong Kong, Shenzhen as an Assistant Professor.