معرفی
Jinha Lee, PhD, serves as an Assistant Professor in the Department of Biomedical Education and Data Science at the Lewis Katz School of Medicine, Temple University. His research applies operations research and data science methodologies to optimize healthcare delivery systems and policy implementation.
Education:
- PhD in Industrial and Systems Engineering, Georgia Institute of Technology, 2016
- Post-Doctoral Fellowship, Rollins School of Public Health, Emory University, 2017-2018
Dr. Lee's research integrates health informatics, healthcare operations, and economic decision analysis to address critical challenges in healthcare systems. His work leverages large-scale clinical datasets and field observations to develop evidence-based solutions for practice variance reduction, resource allocation optimization, and quality improvement in medical services. Current projects focus on system modeling for healthcare policy analysis and establishing data-driven clinical guidelines through operational research frameworks.
Publication trends reveal consistent focus on applying geospatial analytics to public health crises (particularly drug overdose incidents) and optimizing anesthesia procedures in obstetric care. His recent work demonstrates strong interdisciplinary connections between data science, clinical practice, and healthcare management, emphasizing patient-centered outcomes and operational efficiency across diverse healthcare settings.
Scientific Awards:
- Health Transformation Research and Practice Excellence (NSF I/UCR CHOT Meeting, 2015)
- Outstanding Early Career Award Nomination (Bowling Green State University, 2021)
Professional Activities:
- Active collaboration with hospitals and healthcare delivery organizations across the U.S. and internationally
- Membership in INFORMS (Institute for Operations Research and the Management Sciences) including Health Applications Society, Analytics Society, and Decision Analysis Society
Dr. Lee maintains extensive field-based research partnerships with healthcare institutions to implement data-driven solutions for real-world operational challenges in clinical environments.
