The fluid mechanics of blood are central to the development, progression, diagnosis, and treatment of cardiovascular diseases. Our laboratory advances this field by integrating artificial intelligence (AI) with novel image‑based computational and experimental models for cardiovascular fluid mechanics, including applications in the cerebrovascular system. Our workflow begins with AI‑enhanced medical image processing - such as flow segmentation, anatomical reconstruction, and feature extraction - and extends to data‑driven, physics‑informed flow models and advanced fluid–structure interaction simulations. Our experimental platforms include physiological flow loops, particle image velocimetry, and magnetic resonance imaging, all increasingly augmented by AI‑based analytics.
Current research projects include:
- Characterizing blood flow environments in fetal circulation, congenital heart diseases, and valvular disorders using hybrid physics-AI models.
- Optimizing medical device design - including stents, artificial valves, blood pumps, and ventricular assist devices - through simulation‑ and AI‑guided design pipelines.
- Supporting and improving surgical procedures and interventions for pediatric and adult patients via personalized, AI‑accelerated computational planning with “virtual surgery” platforms.
An essential mission of our lab is translating these computer‑aided, AI‑enabled personalized therapies into clinical practice. We collaborate with clinicians across the United States and worldwide to refine surgical and interventional strategies for real-world patients.
In the classroom, I enjoy teaching the fundamentals of biofluids and biosolids, as well as AI‑driven algorithms for biological and clinical data, connecting these concepts to practical, real-world challenges. I am particularly enthusiastic about mentoring students on capstone projects that address pressing problems from hospitals and the medical device industry.
