Yuan-Heng Wang is a postdoctoral research fellow in the Climate and Ecosystem Sciences Division at Lawrence Berkeley National Laboratory. His research aims to advance the frontiers of hydrology and environmental science through cutting-edge machine learning and physics-informed modeling. He received his B.S. and M.S. in Civil Engineering from National Taiwan University and a Ph.D. in Hydrology and Atmospheric Sciences from the University of Arizona. His doctoral work explored/integrated both process-based land surface modeling and pure data-driven deep learning to simulate snowpack accumulation and melt, as well as physics-informed machine learning models to capture catchment-scale precipitation–runoff dynamics. At Berkeley Lab, he focuses on analyzing stream intermittency using Earth observation remote sensing imagery, physics-based model outputs, and field measurements. He is also developing the next generation of physically interpretable, machine learning–based hydrologic models at the catchment scale by leveraging off-the-shelf ML technologies.
