Skip to main content
(Archived Site)
Energy Conversion Devices and Materials Laboratory
Energy Conversion Devices and Materials Laboratory
Main navigation
Home
Contacts
Publications
Research
Teaching
Subsurface Flow
Zhao Beichen
Visiting Student,
Applied Mathematics and Computational Science
Physics-informed Neural Networks
Scientific Machine Learning
Subsurface Flow
Beichen Zhao is a Ph.D. candidate at China University of Petroleum–Beijing and a visiting student in the Applied Mathematics and Computational Science program at KAUST. His research focuses on physics-informed neural networks and surrogate modeling for subsurface flow, with applications in CO₂ enhanced oil recovery, geological carbon storage, and geothermal reservoir simulation.