Affiliation: Department of Applied Computing, Michigan Technological University

Emran Hossen, PhD, is a postdoctoral scholar in the Department of Applied Computing at Michigan Technological University, where he develops patient-specific coronary digital twins for the noninvasive assessment of fractional flow reserve (FFR). His work integrates image-based computational fluid dynamics with physics-informed and operator-learning neural networks (PINNs/PINOs), validated against invasive FFR measurements in patient-specific CTA and ICA geometries. He earned his PhD in mathematics from the University of Texas at Arlington in 2025, with a background in numerical methods and partial differential equations that underpins his computational modeling. His research interests span cardiovascular image analysis, hemodynamic simulation, scientific machine learning, and the translation of reproducible computational pipelines toward clinical decision support.