2 citations · 2 across the 1 of their papers we have counts for
3 papers
Uncovering near-wall blood flow from sparse data with physics-informed neural networks
Amirhossein Arzani, Jian-Xun Wang, Roshan M. D'Souza
Near-wall blood flow and wall shear stress (WSS) regulate major forms of cardiovascular disease, yet they are challenging to quantify with high fidelity. Patient-specific computati…
Integrating multi-fidelity blood flow data with reduced-order data assimilation
Milad Habibi, Roshan M. D'Souza, Scott T. M. Dawson +1
High-fidelity patient-specific modeling of cardiovascular flows and hemodynamics is challenging. Direct blood flow measurement inside the body with in-vivo measurement modalities s…
An Application of Manifold Learning in Global Shape Descriptors
Fereshteh S. Bashiri, Reihaneh Rostami, Peggy Peissig +2
With the rapid expansion of applied 3D computational vision, shape descriptors have become increasingly important for a wide variety of applications and objects from molecules to p…