Research

• Sequential Learning, Simulation Optimization

  • Ranking and Selection (R&S), also known as Pure Exploration and Best Arm Identification

  • Bayesian Learning

  • Generative AI, Large Language Models

  • Applications to Healthcare Management

• Healthcare Management

  • Improving the Health Innovation Pipeline

  • Adaptive Clinical Trial Design

  • Value-based Clinical Trials

  • Precision Medicine

• Target: the best, a good one, the optimal subset, a good set, ranking, etc.

• Evaluator: large language models, stochastic simulation, input uncertainty in simulation, etc.

• Learning Algorithm: greedy, UCB, expected value of information, etc. 

• Formulation: fixed-budget, multi-phase, portfolio, etc.

• Economics: value-based clinical trials

• Auxiliary Information: Bayesian priors

TOPIC 1: Sequential Learning for Improving the Health Innovation Pipeline

• Zaile Li, Stephen E. Chick, Sam Daems, and Shane G. Henderson (2025). Explore Then Confirm: Investment Portfolios for New Drug Therapies. 2025 Winter Simulation Conference (WSC) 3214-3225 (link)

• Zaile Li, Stephen E. Chick, and Shane G. Henderson (2026). Response Adaptivity Across Clinical Trials In Portfolios of Biomedical Innovations. Submitted (link)

• Zaile Li, Stephen E. Chick, and Shane G. Henderson (2026). Optimizing Portfolios of Multiple Treatments for One Indication. Submitted to 2026 Winter Simulation Conference (WSC)

• Stephen E. Chick, Zaile Li, David Roberson, Sofía Villar (2026). A Cost-Calibrated Approach to Selecting Bayesian Designs with Frequentist Guarantees. In Progress

• Zaile Li, Stephen E. Chick, and L. Jeff Hong (2026). Seeking the Best Treatment: Portfolios of Multi-phase Exploratory Trials. In Progress

TOPIC 2: Selection Among Many Choices (Alternatives)

• Zaile Li, Weiwei Fan, and L. Jeff Hong (2025). The (Surprising) Sample Optimality of Greedy Procedures for Large-Scale Ranking and Selection. Management Science 71(2):1238-1259

🏆 Finalist, 2024 George Nicholson Student Paper Competition, INFORMS

🏆 First Prize, Best Student Paper Competition, the 14th POMS-HK International Conference

• Zaile Li, Weiwei Fan, and L. Jeff Hong (2025). UCB for Large-Scale Pure Exploration: Beyond Sub-Gaussianity. Reject & Resubmit at Operations Research

• Zaile Li, Weiwei Fan, and L. Jeff Hong (2026). Virtual Screening at Scale: Efficient Budget Allocation with (Almost) Free Ranking. To Be Submitted

🏆 Finalist, Next-Gen Scholar's Symposium 2025, NUS

TOPIC 3: Simulation Selection Under Input Uncertainty

• Yuchen Wan, Zaile Li*, and L. Jeff Hong (2025). New Additive OCBA Procedures for Robust Ranking and Selection. Asia-Pacific Journal of Operational Research 42(06):2540003

• Zaile Li, Yuchen Wan, and L. Jeff Hong (2026). Additive Distributionally Robust Ranking and Selection. To Be Submitted

TOPIC 4: Diverse Learning Objectives

• Yuchen Wan, Zaile Li, and L. Jeff Hong (2026). Seeking the Best Extreme. In Progress

TOPIC 5: Meta Thoughts About Simulation Optimization & Ranking and Selection

• Stephen E. Chick, Zaile Li, and L. Jeff Hong (2026). Beyond Fixed-Precision and Fixed-Budget Ranking and Selection: Economics of Selection Procedures, New and Old. Submitted to 2026 Winter Simulation Conference (WSC)

  • Journal version In Progress

• Zaile Li, and L. Jeff Hong (2026). Achieving Asymptotically Optimal Budget Allocation for Ranking and Selection Optimally. In Progress