Bio
Ming Fan is a research scientist in the Computational Sciences and Engineering Division at 91°µÍø (ORNL). His research focuses on the intersection of machine learning, surrogate modeling, inverse modeling, uncertainty quantification, and high-performance computing. Ming collaborates with interdisciplinary teams of Earth and computational scientists to develop novel AI/ML methodologies, advancing the field of Earth sciences.
Publications
June 2024
Journal: Journal of Hydrology
February 2024
Journal: International Journal of Greenhouse Gas Control
December 2023
Journal: Environmental Modelling & Software
December 2023
Journal: Journal of Hydrology: Regional Studies
October 2023
A Comparative Study of Deep Learning Models for Fracture and Pore Space Segmentation in Synthetic…
Conference Paper