Pengyi Shi
Health Professions · Purdue University West Lafayette
Publications
63
Citations
923
Est. group size
~1
Recurring co-author estimate
Active years
17
Publishing since 2010
Pengyi Shi's research focuses on improving how hospitals and other public-service systems (such as criminal justice and community corrections) manage capacity, scheduling, and patient/case flow using mathematical modeling, queueing theory, and machine learning. Much of the work combines operations research methods (like optimization and reinforcement learning) with predictive modeling to support decisions such as patient admission, hospital bed allocation, and case routing. The research often bridges healthcare operations with data-driven decision-making tools that could apply to other service systems facing similar capacity or fairness challenges.
Publication output rose steadily from 2017 to a peak in 2021, then settled into a slower but steady pace of about 3-5 papers per year through 2026.
Generated by claude-sonnet-5 from public bibliographic data · Jul 20, 2026
- Enhancing Predictive Model Learning via Domain-Knowledge Augmented Latent Feature Mining
Proceedings of the AAAI Conference on Artificial Intelligence · 2026
- Capacity Management in Networks: A Structural Estimation Approach for Hospital Inpatient Wards
Manufacturing & Service Operations Management · 2026
- Inpatient Overflow Management with Proximal Policy Optimization
Manufacturing & Service Operations Management · 2026
- Admission Decisions under Imperfect Classification: An Application in Criminal Justice
SSRN Electronic Journal · 2025
- Development and internal validation of a prediction model for the malnutrition in lung cancer patients based on modified patient-generated subjective global assessment
Clinical Nutrition ESPEN · 2025
- Data-Pooling Reinforcement Learning for Preventative Healthcare Intervention
Management Science · 2025
- Towards an understanding of community-engaged efforts in addressing the youth substance use in the Democratic Republic of the Congo
BMC Public Health · 2025
- Cumulative Difference Learning VAE for Time-Series with Temporally Correlated Inflow-Outflow
Proceedings of the AAAI Conference on Artificial Intelligence · 2024
- Combining Machine Learning and Queueing Theory for Data-Driven Incarceration-Diversion Program Management
Proceedings of the AAAI Conference on Artificial Intelligence · 2024
- Latent Feature Mining for Predictive Model Enhancement with Large Language Models
arXiv (Cornell University) · 2024
- Interpretable machine learning models for hospital readmission prediction: a two-step extracted regression tree approach
BMC Medical Informatics and Decision Making · 2023
- Optimal Routing Under Demand Surges: The Value of Future Arrival Rates
Operations Research · 2023
- Refined mean‐field approximation for discrete‐time queueing networks with blocking
Naval Research Logistics (NRL) · 2023
- Stopping the Revolving Door: MDP-Based Decision Support for Community Corrections Placement
SSRN Electronic Journal · 2023
- A Constrained Bandit Approach for Online Dispatching
ACM SIGMETRICS Performance Evaluation Review · 2022
- arXiv (Cornell University)×10
- SSRN Electronic Journal×10
- Manufacturing & Service Operations Management×4
- Proceedings of the AAAI Conference on Artificial Intelligence×4
- Operations Research×3
- Zekun Liu
Health Professions · Indiana University
- Jonathan E. Helm
Health Professions · Indiana University
- Jiaqi Suo
Health Professions · Purdue University West Lafayette
- Mohammad Zhalechian
Health Professions · Indiana University
- Nan Kong
Health Professions · Purdue University West Lafayette
This profile was generated automatically from public scholarly data (OpenAlex). Group size and activity levels are estimates derived from co-authorship patterns.
Last updated Jul 20, 2026.
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