| Models and insights for hospital inpatient operations: Time-dependent ED boarding time P Shi, MC Chou, JG Dai, D Ding, J Sim Management Science 62 (1), 1-28, 2016 | 249* | 2016 |
| Inpatient overflow: An approximate dynamic programming approach JG Dai, P Shi Manufacturing & Service Operations Management 21 (4), 894-911, 2019 | 120 | 2019 |
| The impact of mass gatherings and holiday traveling on the course of an influenza pandemic: a computational model P Shi, P Keskinocak, JL Swann, BY Lee BMC public health 10, 1-12, 2010 | 95 | 2010 |
| A two-time-scale approach to time-varying queues in hospital inpatient flow management JG Dai, P Shi Operations Research 65 (2), 514-536, 2017 | 82 | 2017 |
| Descriptive study of case scheduling and cancellations within 1 week of the day of surgery F Dexter, P Shi, RH Epstein Anesthesia & Analgesia 115 (5), 1188-1195, 2012 | 76 | 2012 |
| Timing it right: Balancing inpatient congestion vs. readmission risk at discharge P Shi, JE Helm, J Deglise-Hawkinson, J Pan Operations Research 69 (6), 1842-1865, 2021 | 63 | 2021 |
| An efficient pessimistic-optimistic algorithm for stochastic linear bandits with general constraints X Liu, B Li, P Shi, L Ying Advances in Neural Information Processing Systems 34, 24075-24086, 2021 | 52 | 2021 |
| Modelling seasonality and viral mutation to predict the course of an influenza pandemic P Shi, P Keskinocak, JL Swann, BY Lee Epidemiology & Infection 138 (10), 1472-1481, 2010 | 45 | 2010 |
| Comparing policies for case scheduling within 1 day of surgery by Markov chain models P Shi, F Dexter, RH Epstein Anesthesia & Analgesia 122 (2), 526-538, 2016 | 44 | 2016 |
| Group-aware threshold adaptation for fair classification T Jang, P Shi, X Wang Proceedings of the AAAI Conference on Artificial Intelligence 36 (6), 6988-6995, 2022 | 42 | 2022 |
| A survey on skill-based routing with applications to service operations management J Chen, J Dong, P Shi Queueing Systems 96, 53-82, 2020 | 37 | 2020 |
| Off-service placement in inpatient ward network: Resource pooling versus service slowdown J Dong, P Shi, F Zheng, X Jin Columbia Business School Research Paper Forthcoming, 2019 | 31* | 2019 |
| Patient flow from emergency department to inpatient wards: Empirical observations from a Singaporean hospital P Shi, J Dai, D Ding, SK Ang, M Chou, X Jin, J Sim Available at SSRN 2517050, 2014 | 31 | 2014 |
| Recent modeling and analytical advances in hospital inpatient flow management JG Dai, P Shi Production and Operations Management 30 (6), 1838-1862, 2021 | 25 | 2021 |
| Operations (management) warp speed: Rapid deployment of hospital‐focused predictive/prescriptive analytics for the COVID‐19 pandemic P Shi, JE Helm, C Chen, J Lim, RP Parker, T Tinsley, J Cecil Production and Operations Management 32 (5), 1433-1452, 2023 | 21 | 2023 |
| Optimal routing under demand surges: The value of future arrival rates J Chen, J Dong, P Shi Operations Research 73 (1), 510-542, 2025 | 15 | 2025 |
| Steady‐state diffusion approximations for discrete‐time queue in hospital inpatient flow management J Feng, P Shi Naval Research Logistics (NRL) 65 (1), 26-65, 2018 | 13 | 2018 |
| POND: Pessimistic-optimistic online dispatch X Liu, B Li, P Shi, L Ying arXiv preprint arXiv:2010.09995, 2020 | 12 | 2020 |
| Structural estimation of load balancing behavior in inpatient ward network J Dong, P Shi, F Zheng, X Jin Working Paper. 2020: 1–36, 2020 | 11 | 2020 |
| Pond: Pessimistic-optimistic online dispatching X Liu, B Li, P Shi, L Ying arXiv preprint arXiv:2010.09995, 2020 | 10 | 2020 |