Zhang Shixuan

Zhang Shixuan is an Assistant Professor in the Department of Industrial & Systems Engineering at Texas A&M University. His research focuses on mathematical optimization theory and its applications to data science, operations research, and systems engineering.

• Education: Ph.D. in Operations Research from Georgia Institute of Technology
• Postdoctoral: Institute for Computational and Experimental Research in Mathematics (ICERM), Brown University

His primary research areas include:

• Polynomial Optimization
• Integer Optimization
• Stochastic Optimization
• Robust Optimization

His recent publications explore advances in distributionally robust optimization, security-constrained power flow algorithms, and theoretical aspects of multistage stochastic programming. Key trends in his work emphasize computational efficiency, algorithm design for nonconvex problems, and applications to energy systems and convex geometry.

Doctoral Advisees: Jiamin Chen and Qi Xiao.