Simulation Optimization, Sequential Learning
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: Improving the Health Innovation Pipeline
Zaile Li, Stephen E. Chick, and Shane G. Henderson (2026). Response Adaptivity Across Clinical Trials In Portfolios of Biomedical Innovations. To Be Submitted
Zaile Li, Stephen E. Chick, and Shane G. Henderson (2026). Optimizing Portfolios of Multiple Treatments for One Indication. Work in Progress
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
TOPIC 2: Selection Among Many 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 Optimization Under Input Uncertainty
Zaile Li, Yuchen Wan, and L. Jeff Hong (2026). Additive Distributionally Robust Ranking and Selection. To Be Submitted
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
TOPIC 4: Diverse Selection Objectives
Yuchen Wan, Zaile Li, and L. Jeff Hong (2026). Seeking the Best Extreme. Working Paper
TOPIC 5: Simulation Optimization & Ranking and Selection
Stephen E. Chick, Zaile Li, and L. Jeff Hong (2026). Economics of Selection Procedures are Neither Fixed Precision nor Fixed Budget. Working Paper