['Published multiple high-impact papers, including:', '"Staffing Under Taylor's Law: A Unifying Framework for Bridging Square-root and Linear Safety Rules"', '"Over-optimizing" for Normality: Budget-constrained Uncertainty Quantification for Contextual Decision-making"', 'Asymptotic Theory for IV-Based Reinforcement Learning with Potential Endogeneity', 'Hierarchical AI Multi-Agent Fundamental Investing: Evidence from China’s A‑Share Market', 'Predicting Effects, Missing Distributions: Evaluating LLMs as Human Behavior Simulators in Operations Management', 'Can AI Master Econometrics? Evidence from Econometrics AI Agent on Expert-Level Tasks', 'Learning to Simulate: Generative Metamodeling via Quantile Regression', 'Sparse Additive Contextual Bandits: A Nonparametric Approach for Online Decision-making with High-dimensional Covariates', 'Seesaw Experimentation: A/B Tests with Spillovers', 'Smooth Nested Simulation: Bridging Cubic and Square Root Convergence Rates in High Dimensions']
Background
Associate Professor of Operations Research, Department of Industrial Engineering and Decision Analytics, The Hong Kong University of Science and Technology (HKUST)
Academic Director of the MSc in FinTech program at HKUST
Research focuses on innovative methodologies for data-driven decision-making, integrating simulation, stochastics, and machine learning
Applications in business operations, finance, and the digital economy, with emphasis on the transformative potential of AI
Serves as Associate Editor for leading journals including Management Science, Operations Research, Naval Research Logistics, and Queueing Systems