Yueyang Liu Assistant Professor of Operations Management Jones Graduate School of Business Rice University Email: yueyl at rice dot edu Office: McNair 132C

Bio

I am currently an assistant professor in operations management at Rice University, Jones Graduate School of Business.

I grew up in Beijing, China. I studied mathematics at MIT as an undergraduate, then worked as a software engineer at Oracle before completing my PhD at Stanford MS&E with Benjamin Van Roy and Kuang Xu.

Research Overview

I study learning — how AI agents learn over time, and how humans make decisions with AI.

Continual Learning Agents — designing and analyzing agents that acquire knowledge over an extended lifetime. My work draws on probability theory, stochastic modeling, and information theory to build agents that are theoretically grounded and practically scalable, with applications in recommendation systems and operations.

Human-AI Decision Making — I study how humans learn and make decisions in complex, uncertain environments. Using tools from game theory and behavioral economics, I develop models and interventions that improve decision-making and inform the design of human-centered AI systems.

Papers

• Yueyang Liu and Wichinpong Park Sinchaisri.
  Strategic advice in the age of personal AI.
  Preprint, 2026.
  [arXiv]
• Saurabh Kumar, Henrik Marklund, Ashish Rao, Yifan Zhu, Hong Jun Jeon, Yueyang Liu, and Benjamin Van Roy.
  Continual learning as computationally constrained reinforcement learning.
  Foundations and Trends in Machine Learning 18 (5), 913-1053, 2025.
  [arXiv] [paper]
• Yueyang Liu, Xu Kuang, and Benjamin Van Roy.
  A definition of non-stationary bandits.
  Preprint, 2023.
  [arXiv]
• Zheqing Zhu, Yueyang Liu, Xu Kuang, and Benjamin Van Roy.
  Non-stationary contextual bandit learning via neural predictive ensemble sampling.
  Preprint, 2023.
  [arXiv]
• Yueyang Liu, Xu Kuang, and Benjamin Van Roy.
  Non-stationary bandit learning via predictive sampling.
  In International Conference on Artificial Intelligence and Statistics (AISTATS), 2023. Major revision at Management Science.
  [arXiv] [paper]
• Yueyang Liu, Adithya M. Devraj, Benjamin Van Roy, and Kuang Xu.
  Gaussian imagination in bandit learning.
  Preprint, 2022.
  [arXiv]

Teaching

BUSI 395 Data Analytics | Fall 2024, Fall 2025

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