Healthcare AI & Analytics
Developing AI-enabled models that translate healthcare data into actionable policy and care insights.
Academic Research Lab
PATH Lab
Policy Analytics & Transformative Healthcare
AI, Optimization & Policy for Smart Healthcare
Mission
PATH Lab develops data-driven analytical, simulation, and optimization methods to support healthcare policy design and health system decision-making.
Our research integrates artificial intelligence, operations research, and healthcare data analytics to study the allocation, delivery, and accessibility of healthcare resources and services. We translate methodological advances and empirical evidence into practical decision-support tools that aim to strengthen preventive care, improve access to healthcare, enhance population health outcomes, and increase the resilience of healthcare systems.
Vision
We envision healthcare systems that anticipate emerging needs, adapt to changing conditions, and use data and evidence to guide policy and operational decisions.
Through these capabilities, healthcare systems can improve equity in access and delivery, strengthen population health, and achieve more sustainable outcomes across diverse communities.
Research Areas
Preventive Healthcare
Designing evidence-based strategies that improve screening, prevention, access, and population health.
Resilient Healthcare Systems
Strengthening preparedness, adaptability, and policy response under uncertainty and system disruption.
Healthcare Operations & Capacity Management
Optimizing patient flow, staffing, and service capacity across complex and dynamic care settings.
Human-Centered Healthcare Systems
Integrating clinical, behavioral, and community perspectives into practical healthcare system design.
Team
Core Members
Sarah Yini Gao
Director, PATH Lab
Healthcare operations, optimization, and preventive healthcare policy.
Daniel Zhichao Zheng
Lead Researcher, PATH Lab
Healthcare analytics, AI, and operational decision-making.
Collaborators
Prof. Chung Piaw Teo
National University of Singapore
Dr. Xiaoquan Gao
Singapore Management University
Dr. Sean Lam
SingHealth Duke-NUS Academic Medical Centre
Dr. Krishnamoorthy Rajeeva Lochanamoorthy
National University of Singapore
Dr. Hanzhang Qin
National University of Singapore
Dr. Zhaowei She
Singapore Management University
Dr. Leon Xu
Singapore Management University
RFs & Students
Zhuolin Wang
Research Fellow, PATH Lab
Healthcare operations, optimization under uncertainty, and AI.
RFs & Students
Research Fellows & Trainees
Developing the next generation of healthcare AI and policy researchers.
Collaborating Institutions
PATH Lab works with academic, healthcare, and research partners to translate policy analytics into practical healthcare impact.
Join Us
We are looking for motivated researchers and students who are excited about using data, AI, analytics, optimization, and policy design to improve healthcare systems.
Research Fellow
Healthcare Analytics & Research
Research Assistant
Healthcare Modelling & Research
Research Assistant
AI & Data Development
Selected Publications
Publications grouped by our research areas. Select a topic to expand the list.
Extubation decisions with predictive information for mechanically ventilated patients in ICU.
Management Science, 71(7), 6069–6091.
Optimizing Initial Screening for Colorectal Cancer Detection with Adherence Behavior.
Management Science
Pierskalla Best Paper Award Finalist (2025)
POMS HK Best Student Paper Competition – 1st Place (2022)
Working papers
On the Adherence of Colorectal Cancer Screening Policies – A Survey Study in Singapore.
Working paper
Does information type matter in promoting cancer screening? Evidence from a randomized controlled trial.
Working paper
On the Test Accuracy and Effective Control of the COVID-19 Pandemic: A Case Study in Singapore.
INFORMS Journal on Applied Analytics, 52(6), 524–538.
Working papers
Optimal Scheduling and Policy Design of Two-Dose Vaccination Rollout.
Working paper
Inventory-Responsive Donor Management Policy: A Tandem Queueing Network Model.
Manufacturing & Service Operations Management
A queueing model for customer rescheduling and no-shows in service systems.
Operations Research Letters, 49(6), 821–828.
Effects of rescheduling on patient no-show behavior in outpatient clinics.
Manufacturing & Service Operations Management, 21(4), 780–797.
Scheduling arrivals to a stochastic service delivery system using copositive cones.
Operations Research.
Working papers
Rethinking Appointment Scheduling: Addressing Counselor Burnout and Improving Patient Outcomes.
Working paper