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Hierarchical Computations on Manycore Architectures
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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.