Zean Han

Ph.D. Student at HKUST

Hong Kong University of Science and Technology

Advised by Jiheng Zhang

I work on the intersection of theory and industrial applications of modern AI, trying to bring learning theory to real-world applications.

Portrait of Zean Han

About Me

I am a Ph.D. student in Industrial Engineering and Decision Analytics at the Hong Kong University of Science and Technology, where I am fortunate to be supervised by Prof. Jiheng Zhang, head and full professor of the department. My research develops theory and algorithms for real-world scenarios including LLM inference and offline-to-online learning. I am also interested in applying learning theory to management problems such as inventory management and dynamic pricing. My work often leverages tools from queueing theory, reinforcement learning, and optimization to study how complex service and decision systems behave under uncertainty.

Before coming to HKUST, I received my M.Phil degree in Pure Mathematics from the Chinese University of Hong Kong, where I spent two wonderful years working on geometric representation theory. I used to enjoy considering all kinds of geometric problems and trying to find the underlying algebraic structures. I worked on perverse sheaves and hypertoric varieties there. I am keen in running, watching movies and classical guitar.

Research Interest

Broadly, I try to optimize decision systems under uncertainty using queueing theory, reinforcement learning, and optimization. I am also drawn to AI research which does not involve too much theoretical analysis.

Education

Hong Kong University of Science and Technology

2025 – 2028 (expected)

Ph.D. in Industrial Engineering and Decision Analytics

  • Advisor: Prof. Jiheng Zhang

The Chinese University of Hong Kong

2023 – 2025

M.Phil in Pure Mathematics

  • Research focus: geometric representation theory
  • GPA: 3.81 / 4.0

Papers

Published

VoCAPTER: Voting-based Pose Tracking for Category-level Articulated Object via Inter-frame Priors

Li Zhang*, Zean Han*, Yan Zhong, Qiaojun Yu, Xingyu Wu, Xue Wang, Rujing Wang (*equal contribution)

ACM International Conference on Multimedia (ACM MM), 2024 · Melbourne, Australia

Working papers

Learning to price and stock under contextual and censored demand

Zean Han, Zezhen Ding, and Jiheng Zhang

To appear in IJCAI 2026

Contact

Get in touch

Email: morphismtalking@outlook.com

Hong Kong University of Science and Technology