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Our lab's mission is advancing treatment of patients with cardiovascular disease through computational modeling.


Our lab develops tools for simulating the cardiovascular system, with a particular focus on blood flow in the vasculature and the heart. We build patient specific models from medical image data to create a customized model for each individual patient, which represents their unique vascular anatomy. We then use that model to run simulations of blood flow, which allows us to do virtual surgery, virtual treatment planning, and risk assessment. 

Much of our focus is developing numerical tools and computational algorithms to ensure we can capture things like cardiovascular physiology, moving heart and vessel walls or valve leaflets in a realistic way. We also develop advanced algorithms for optimization of surgeries and medical devices and uncertainty quantification.  Ultimately, we aim to bring the same kind of predictive simulations that we’ve come to routinely expect in for example, the aerospace industry to medicine. Our goal is to make better predictions about patients' individual outcomes following surgery or other interventions, and ultimately improve their overall outcomes and quality of life. 

Our research interests include: 

  • cardiovascular disease and bio fluid mechanics
  • shape optimization for complex flows
  • pediatric cardiology and congenital heart disease
  • coronary artery disease 
  • uncertainty quantification
  • multiscale modeling
  • vascular design principles
  • vascular growth and remodeling
  • cardiovascular devices
  • ventricular flow simulation
  • fluid structure interaction
  • machine learning for automatic segmentation 
  • machine learning for reduced order modeling

Specific diseases we are currently studying include: 

  • Coronary Artery Disease
  • Single Ventricle Physiology
  • Pulmonary Hypertension
  • Kawasaki Disease
  • Tetralogy of Fallot