Papers

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Selected Preprints

• Service-Induced Congestion in Memory-Constrained LLM Serving [SSRN]
  Job Market Paper
  R. Ao, J. Dong, G. Luo, D. Simchi-Levi, under review at Operations Research, available at SSRN, finalist in the 2026 George Nicholson Student Paper Competition, the 2026 INFORMS Service Science Section Best Student Paper Award, and the 2026 DMDA Workshop Best Paper Competition (Theoretical Track)

• Optimizing LLM Inference: Fluid-Guided Online Scheduling with Memory Constraints [SSRN]
  R. Ao, G. Luo, D. Simchi-Levi, X. Wang, major revision at Operations Research, finalist in Applied Probability 2025 Student Paper Award and POMS CSOM 2026 Best Student Paper Competition

• OptiRepair: Closed-Loop Diagnosis and Repair of Supply Chain Optimization Models with LLM Agents [arXiv]
  R. Ao, D. Simchi-Levi, X. Wang, major revision at Manufacturing & Service Operations Management, arXiv preprint arXiv:2602.19439

• Proactive Transfer Admission Control for Emergency Departments [PDF]
  R. Ao, J. Dong, A. Liu, M. Copenhaver, major revision at Manufacturing & Service Operations Management

• Prediction-Guided Active Experiments [SSRN]
  R. Ao, H. Chen, D. Simchi-Levi, minor revision at Management Science, available at SSRN

• Online Resource Allocation with Average Budget Constraints [arXiv]
  R. Ao, H. Chen, D. Simchi-Levi, F.Zhu, major revision at Operations Research, finalist in Revenue Management and Pricing 2024 Jeff McGill Student Paper Award

Conference Proceedings

• Verifier-Native Closed-Loop Repair for Operations Research Agents [OpenReview]
  R. Ao, C. Ma, D. Simchi-Levi, X. Wang, NeurIPS 2026 Workshop on MLxOR, accepted poster

• MARCS: Marginal-Cost Routing and Adaptive Priority Control for LLM Inference [OpenReview]
  Y. Cao, R. Ao, W. Ma, D. Simchi-Levi, NeurIPS 2026 Workshop on MLxOR, accepted poster

• Solver-in-the-Loop: MDP-Based Benchmarks for Self-Correction and Behavioral Rationality in Operations Research [arXiv]
  R. Ao, D. Simchi-Levi, X. Wang, International Conference on Machine Learning (ICML), 2026

• PILOT-Bench: Probabilistic Interaction for LLM Operations in Tool-driven Scenarios
  R. Ao, Z. Min, T. Zhu, X. Wang, W. Yin, International Conference on Learning Representations (ICLR), 2026

• Learning to Price with Resource Constraints: From Full Information to Machine-Learned Prices [arXiv]
  R. Ao, J. Jiang, D. Simchi-Levi, Conference on Neural Information Processing Systems (Neurips), 2025

• Asynchronous Gradient Play in Zero-Sum Multi-agent Games [arXiv]
  R. Ao, S. Cen, and Y. Chi, International Conference on Learning Representations (ICLR), 2023.

Journals

• A Monte Carlo Policy Gradient Method with Local Search for Binary Optimization [arXiv]
  C. Chen, R. Chen, T. Li, R. Ao, Z. Wen, Mathematical Programming, 1-57

• Riemannian natural gradient methods [arXiv]
  J. Hu, R. Ao, AMC. So, M Yang, Z. Wen, SIAM Journal on Scientific Computing 46 (1), A204-A231