I strive to develop exposome data integration and machine learning algorithms to better discover actionable patterns from big health data. My research considers the totality of the biological, lifestyle, and environmental factors that impacts population health and provides personalized solutions that allow individuals and neighborhoods to improve their health and wellness. Specifically, I am interested in the following topics:
- Precision Health
- Machine Learning
- Integration of Multi-Type, Multi-Scale Health Data
- Environmental, Cardiovascular, and Perinatal Epidemiology
- Health Disparities
Ongoing Research Projects
- Hypertensive Disorders of Pregnancy and Early Risk of Maternal CVD: Influence of the External Exposome. NIH/NHLBI. PI.
- The External Exposome and COVID-19 Severity. NIH/NIEHS. Contact PI.
- The External Exposome and COVID-19 Severity among Individuals with Alzheimer's Disease and Related Dementias. NIH/NIA and NIEHS. Contact PI.
- Assessing the Feasibility of a Universal Prenatal Screening Tool to Identify Women at Risk of Pregnancy-Associated Death in Florida. NIH/NCATS. MPI.
- Artificial Intelligence-aided Personalization on Dual Antiplatelet Therapy for Patients Underwent Coronary Stent Implantation Using Large-scale Electronic Health Records. American Heart Association. Co-I.
: Our lab would like to thank generous support from the NIH, American Heart Association, and Florida Department of Health.