Received the Accenture IOE Scholarship at UMich.
Industrial Engineering · Machine Learning · Optimization
Zijian Huang
Hi! I am a first-year Ph.D. student in Industrial and Operations Engineering at the University of Michigan, advised by Prof. Raed Al Kontar.
Prior to that, I received my undergraduate education in Industrial and Operations Engineering at the University of Michigan and Electrical and Computer Engineering at Shanghai Jiao Tong University.
I am broadly interested in the intersection of machine learning, statistics, and optimization. My current interests are Bayesian optimization and diffusion models.
Updated in 5/2026
News
Awarded National Scholarship at SJTU.
Selected Publications
Understanding Generalization in Diffusion Models via Probability Flow Distance
We propose Probability Flow Distance (PFD), a theoretically grounded and computationally efficient metric to quantify distributional generalization in diffusion models. Using a teacher-student evaluation protocol, we empirically uncover several novel generalization behaviors.