3 papers
cs.CE2026
From Centerlines to Hemodynamics: Anisotropic RBF Decoders for Coronary Arteries
Reza Akbarian Bafghi, Sukirt Thakur, Maziar Raissi
Accurate and rapid estimation of hemodynamic metrics, such as pressure and wall shear stress (WSS), is important for assessing the severity of Coronary Artery Disease (CAD). Existi…
cs.LG2026
PUNCH: Physics-informed Uncertainty-aware Network for Coronary Hemodynamics
Sukirt Thakur, Marcus Roper, Yang Zhou +8
More than 10 million coronary angiograms are performed globally each year, providing a gold standard for detecting obstructive coronary artery disease. Yet, no obstructive lesions…
physics.flu-dyn2025
ELPINN: Eulerian Lagrangian Physics-Informed Neural Network
Sukirt Thakur, Maziar Raissi
Physics-Informed Neural Networks (PINNs) have gained widespread popularity for solving inverse and forward problems across a range of scientific and engineering domains. However, m…