Ph.D. Student Spotlight

Yizhe Huang

Yizhe Huang is a Ph.D. candidate in the Department of Information, Risk and Operations Management at the McCombs School of Business. He is advised by professor Rui Gao. His research addresses challenges in decision-making problems from two complementary perspectives. First, he studies reliable and scalable dynamic decision-making by developing robust formulations that provide performance guarantees even when data exhibit noise, model bias, or distributional shifts, while reducing the over-conservativeness of the solution as a necessary price to robustness. Second, he explores how deep learning can advance algorithmic tools for solving large-scale problems in operations research. Together, these two threads form a unified research agenda for designing principled, generalizable, and scalable methods for dynamic decision-making under uncertainty.