
Griffith Boyce
استاد · Computational mathematics
University of North Carolina at Chapel Hillمعرفی
Griffith Boyce is a Professor of Mathematics and Biomedical Engineering at the University of North Carolina at Chapel Hill (UNC), with an adjunct appointment in Applied Physical Sciences. He serves as Associate Chair for Research in the Department of Mathematics and leads the Cardiovascular Modeling and Simulation Laboratory. His affiliations include the Carolina Center for Interdisciplinary Applied Mathematics, Computational Medicine Program, and McAllister Heart Institute at UNC School of Medicine.
Dr. Griffith earned his BA and BS in Mathematics from Rice University (2000), followed by a PhD in Mathematics from New York University (2005). He completed postdoctoral training at NYU (2005-2008) before joining NYU as faculty (2008-2014), then UNC in 2014.
His research focuses on developing computational tools to predict cardiovascular physiology and pathology through fluid-structure interaction (FSI) modeling. Key applications include cardiac hemodynamics, bioprosthetic heart valves, ventricular assist devices, and thrombosis in atrial fibrillation. His group advances the immersed boundary (IB) method and maintains the IBAMR software infrastructure for adaptive mesh refinement in FSI problems.
Recent publications highlight innovations in divergence-free numerical methods, viscoelastic flow modeling, and patient-specific cardiovascular simulations. His team's work spans from fundamental FSI algorithms to clinical translation in medical device design.
Dr. Griffith collaborates with clinicians, engineers, and computational scientists across academia, industry, and regulatory agencies. His lab includes PhD alumni like Marshall Davey, Charles Puelz, Aaron Barrett, and Cole Gruninger, alongside current researchers.
The Cardiovascular Modeling and Simulation Laboratory develops open-source software and interdisciplinary frameworks for predictive biomedical simulations. Their research integrates mathematical modeling, high-performance computing, and experimental validation to address cardiovascular disease mechanisms and therapy optimization.
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