Summary
Haoxiang Yang is an assistant professor at CUHK-Shenzhen with nine years of experience translating advanced optimization theory into practical solutions for energy systems, security, and supply chains. He earned a PhD in Industrial Engineering from Northwestern and has a track record at national labs and research centers—developing algorithms for nonconvex recourse, robust ACOPF models, and multistage stochastic programs implemented in Julia/JuMP. Comfortable across multiple programming languages and modeling tools, he pairs rigorous convergence proofs with production-ready code to tackle large-scale, uncertain decision problems. His work at Los Alamos, PNNL and RAND shows a rare blend of theoretical depth and applied impact, such as improving airport delay models and grid optimization benchmarks. An aspiring educator, he brings analytical precision to identify root causes and devise scientific, deployable solutions while mentoring the next generation of optimization researchers.
9 years of coding experience
7 years of employment as a software developer
Bachelor's Degree, Industrial Engineering, 3.97/4.00, Bachelor's Degree, Industrial Engineering, 3.97/4.00 at Georgia Institute of Technology
Doctor of Philosophy (Ph.D.), Industrial Engineering, 3.88/4.00, Doctor of Philosophy (Ph.D.), Industrial Engineering, 3.88/4.00 at Northwestern University
English, Chinese, German