Huiwen Xu
Emory University
Huiwen Xu
Huiwen Xu, PhD, is an Associate Professor in the Nell Hodgson Woodruff School of Nursing at Emory University. Dr. Xu’s research examines the staffing, quality, disparity, and policy in nursing homes using large administrative data and various survey data. He is also interested in applying machine learning to aging research and has built various supervised and unsupervised machine learning models. Dr. Xu currently leads a 4-year R01 grant from the National Institute on Aging (R01 AG081282, 2023-2027). He participated in multiple NIH-funded projects in cancer survivorship previously (R01, U01, UG1, R21, etc.). Dr. Xu was selected into several prestigious aging-related training programs including the RL5 Pepper Scholar from UTMB Pepper OAIC Center, the NIA RCCN Scholars Program in Multidisciplinary Research, the NIA AWARD Network Dementia Workforce Summer Institute, and the R25 Research Methods in Supportive Oncology from Harvard Medical School.
Dr. Xu has published 60+ peer-reviewed articles in leading medical and policy journals including The Lancet, JAMA Internal Medicine, JAMA Oncology, JAMA Network Open, Journal of Clinical Oncology, JAGS, JAMDA, Health Affairs, Health Services Research, and Medical Care; he coauthored two book chapters and 90+ scientific abstracts. His work has been cited 2,400+ times, with an H-index of 24.
Dr. Xu holds national leadership positions at the AcademyHealth, NIA AWARD Network for Dementia Workforce Research, and Cancer and Aging Research Group (CARG). He serves as a scientific reviewer for the National Institutes of Health, AWARD Network, and CARG, as well as 25+ scientific journals. He has mentored 20+ statisticians, fellows, junior faculty, and students (undergraduate, master, medical, and doctoral). Dr. Xu received several national and international awards.
Before coming to Emory, Dr. Xu held faculty positions at the University of Rochester Medical Center and University of Texas Medical Branch. He earned his PhD in Health Services Research and Policy with Data Science training from the University of Rochester.
FURTHER INFORMATION
| Countries | United States; |
|---|---|
| Topics | Access to care; Artificial Intelligence; Care economy; Care in rural and other non-urban settings; Care inequalities; Climate Change and LTC; COVID-19 and other infectious diseases and LTC; Economics of LTC; LTC Policy; LTC systems in LMIC countries; LTC Workforce; Quality regulation and accreditation for LTC services; |
| Methods | Causal inference in Long-Term Care; Comparative policy analysis; Longitudinal data analysis; Mixed methods; Observational studies; Panel data analysis; Policy analysis; Quantitative data analysis; Quasi-experimental methods; Surveys; Trials and other evaluations; |
| Role | Research; |
| Interest Groups | Economics of Long-Term Care; Long-Term Care Policy; |
| Website | https://aginglab.us |
| ORC.ID | 0000-0002-4033-0659 |
| GOOGLE SCHOLAR | https://scholar.google.com/citations?user=nv3DHRUAAAAJ&hl=en |
| X (Twitter) | https://x.com/Dr_HuiwenXu |
| https://www.linkedin.com/in/huiwenxu/ | |
| Research interests | Staffing, quality, disparity, and policy in nursing homes using large administrative data and various survey data. |