Publications

(2026). Asymptotic Theory for IV-Based Reinforcement Learning with Potential Endogeneity. Journal of Econometrics, Minor Revision.

Preprint Reinforcement Learning & Sequential Decision-Making

(2026). Predicting Effects, Missing Distributions: Evaluating LLMs as Human Behavior Simulators in Operations Management. INFORMS Journal on Data Science, forthcoming.

Preprint Agentic & Generative AIService Operations & Digital Platforms

(2026). SPARKLE: A Nonparametric Approach for Online Decision-Making with High-Dimensional Covariates. Operations Research, Major Revision.

Preprint Reinforcement Learning & Sequential Decision-MakingService Operations & Digital Platforms

(2026). Dynamic Cloud Service-Capacity Deployment with Costly Response Readiness.

Preprint Service Operations & Digital PlatformsReinforcement Learning & Sequential Decision-Making

(2026). Attribution and Persuasion: The Paradox of Interpretable AI. Management Science, forthcoming.

Preprint Agentic & Generative AI

(2026). Learning to Simulate: Generative Metamodeling via Quantile Regression. INFORMS Journal on Computing, forthcoming.

Preprint Data-Driven Simulation & Stochastic OptimizationAgentic & Generative AI

(2026). On the Suboptimality of GP-UCB under Polynomial Effective Optimism.

Preprint Reinforcement Learning & Sequential Decision-MakingData-Driven Simulation & Stochastic Optimization

(2026). Staffing under Taylor's Law: A Unifying Framework for Bridging Square-Root and Linear Safety Rules. Management Science, Minor Revision.

Preprint Service Operations & Digital PlatformsData-Driven Simulation & Stochastic Optimization

(2026). Cold-Start Forecasting of New Product Life-Cycles via Conditional Diffusion Models.

Preprint Agentic & Generative AIService Operations & Digital Platforms

(2026). Optimizing Service Operations via LLM-Powered Multi-Agent Simulation.

Preprint Agentic & Generative AIService Operations & Digital Platforms

(2026). ''Over-Optimizing'' for Normality: Budget-Constrained Uncertainty Quantification for Contextual Decision-Making. Manufacturing and Service Operations Management, Major Revision.

Preprint Data-Driven Simulation & Stochastic Optimization

(2026). Can AI Master Econometrics? Evidence from Econometrics AI Agent on Expert-Level Tasks.

Preprint Agentic & Generative AI

(2026). Uncertainty-Adjusted Sorting for Asset Pricing with Machine Learning.

Preprint FinTech & Quantitative Risk

(2025). AgentGit: A Version Control Framework for Reliable and Scalable LLM-Powered Multi-Agent Systems. WMAC 2026.

Preprint Agentic & Generative AI

(2025). Hierarchical AI Multi-Agent Fundamental Investing: Evidence from China’s A‑Share Market.

Preprint FinTech & Quantitative RiskAgentic & Generative AI

(2025). Seesaw Experimentation: A/B Tests with Spillovers.

Preprint Reinforcement Learning & Sequential Decision-MakingService Operations & Digital Platforms

(2024). Smooth Nested Simulation: Bridging Cubic and Square Root Convergence Rates in High Dimensions. Management Science 70(12):9031-9057.

DOI Preprint Data-Driven Simulation & Stochastic OptimizationFinTech & Quantitative Risk

(2024). How Does Risk Hedging Impact Operations? Insights from a Price-Setting Newsvendor Model. Management Science 70(7):4167-4952.

DOI Preprint Service Operations & Digital PlatformsFinTech & Quantitative Risk

(2024). Sample and Computationally Efficient Stochastic Kriging in High Dimensions. Operations Research 72(2):660–683.

DOI Preprint Data-Driven Simulation & Stochastic Optimization

(2023). Dynamic Selection in Algorithmic Decision-making.

Preprint Reinforcement Learning & Sequential Decision-Making

(2022). Knowledge Gradient for Selection with Covariates: Consistency and Computation. Naval Research Logistics 69(3):496–507.

DOI Preprint Data-Driven Simulation & Stochastic OptimizationReinforcement Learning & Sequential Decision-Making

(2021). Surrogate-Based Simulation Optimization. Emerging Optimization Methods and Modeling Techniques with Applications, 287–311, INFORMS TutORials in Operations Research.

DOI Preprint Data-Driven Simulation & Stochastic Optimization

(2021). High-Dimensional Simulation Optimization via Brownian Fields and Sparse Grids.

Preprint Reinforcement Learning & Sequential Decision-MakingData-Driven Simulation & Stochastic Optimization

(2021). Ranking and Selection with Covariates for Personalized Decision Making. INFORMS Journal on Computing 33(4):1500–1519.

DOI Preprint Data-Driven Simulation & Stochastic Optimization

(2020). Distributionally Robust Selection of the Best. Management Science 66(1):190–208.

DOI Preprint Data-Driven Simulation & Stochastic OptimizationReinforcement Learning & Sequential Decision-Making

(2018). A Scalable Approach to Enhancing Stochastic Kriging with Gradients. Proceedings of the 2018 Winter Simulation Conference, 2213–2224.

DOI Data-Driven Simulation & Stochastic Optimization

(2018). Data-Driven Ranking and Selection: High-dimensional Covariates and General Dependence. Proceedings of the 2018 Winter Simulation Conference, 1933–1944.

DOI Data-Driven Simulation & Stochastic Optimization

(2018). Affine Jump-Diffusions: Stochastic Stability and Limit Theorems.

Preprint FinTech & Quantitative Risk

(2018). Enhancing Stochastic Kriging for Queueing Simulation with Stylized Models. IISE Transactions 50(11):943–958.

DOI Data-Driven Simulation & Stochastic OptimizationService Operations & Digital Platforms

(2018). Scalable Stochastic Kriging with Markovian Covariances.

Preprint Data-Driven Simulation & Stochastic Optimization

(2018). Stochastic Kriging for Inadequate Simulation Models.

Preprint Data-Driven Simulation & Stochastic Optimization

(2017). Ranking and Selection with Covariates. Proceedings of the 2017 Winter Simulation Conference, 2137–2148.

DOI Data-Driven Simulation & Stochastic Optimization

(2016). Sequential Sampling for Bayesian Robust Ranking and Selection. Proceedings of the 2016 Winter Simulation Conference, 758–769.

DOI Data-Driven Simulation & Stochastic OptimizationReinforcement Learning & Sequential Decision-Making

(2016). Simulation Metamodeling in the Presence of Model Inadequacy. Proceedings of the 2016 Winter Simulation Conference, 566–577.

DOI Data-Driven Simulation & Stochastic Optimization

(2015). Affine Point Processes: Approximation and Efficient Simulation. Mathematics of Operations Research 40(4):797–819.

DOI FinTech & Quantitative RiskData-Driven Simulation & Stochastic Optimization

(2014). Scaling and Modeling of Call Center Arrivals. Proceedings of the 2014 Winter Simulation Conference, 476–485.

DOI Service Operations & Digital PlatformsData-Driven Simulation & Stochastic Optimization

(2013). A Bayesian Approach for Modeling and Analysis of Call Center Arrivals. Proceedings of the 2013 Winter Simulation Conference, 713–723.

DOI Service Operations & Digital PlatformsData-Driven Simulation & Stochastic Optimization

(2013). Robust Selection of the Best. Proceedings of the 2013 Winter Simulation Conference, 713–723.

DOI Data-Driven Simulation & Stochastic Optimization

(2010). A Regenerative Bootstrap Approach to Estimating the Initial Transient. Proceedings of the 2010 Winter Simulation Conference, 965–970.

DOI Data-Driven Simulation & Stochastic Optimization

(2010). On the Dynamics of a Finite Buffer Queue Conditioned on the Amount of Loss. Queueing Systems 67(2):91–110.

DOI Data-Driven Simulation & Stochastic OptimizationService Operations & Digital Platforms

(2009). Rare Event Simulation for a Generalized Hawkes Process. Proceedings of the 2009 Winter Simulation Conference, 1291–1298.

DOI FinTech & Quantitative RiskData-Driven Simulation & Stochastic Optimization

(2007). Efficient Suboptimal Rare-event Simulation. Proceedings of the 2007 Winter Simulation Conference, 389–397.

DOI FinTech & Quantitative RiskData-Driven Simulation & Stochastic Optimization