Computational modeling of vascular systems

My research focuses on computational modeling of blood flow in patient-specific vascular systems, particularly coronary arteries. As a member of the Randles Lab at Duke University, I work on developing high-fidelity simulations that capture how physiological variations—such as changes in heart rate and vessel geometry affect key hemodynamic quantities including pressure, velocity, and wall shear stress.

Using computational fluid dynamics and emerging data-driven approaches, I study how these flow characteristics influence cardiovascular disease progression and treatment outcomes. A central goal of this work is to develop scalable computational frameworks that enable the construction of cardiovascular digital twins—patient-specific models that can support improved understanding of vascular disease and eventually inform personalized clinical decision-making.