Gege Wen

Gege Wen is Ph.D. candidate at the Energy Resources Engineering Department in the School of Earth, Energy and Environmental Sciences at Stanford University. She received her Master's degree in Fluid Mechanics and Hydrology from Civil and Environmental Engineering at Stanford University and has been working with Professor Sally Benson since 2016 on numerical simulation for carbon capture and storage. During her Ph.D., she focuses on machine learning approaches for carbon storage problems and published journal articles on this topic. She is currently an ExxonMobil Emerging Energy Fellow. She served as reviewer for academic journals and ICML, NeurIPS, and ICLR conference workshops. Prior to attending Stanford, she received her Bachelor's degree with honors from Lassonde Mineral Engineering at University of Toronto.

Gege Wen developed CCSNet.ai a deep learning modeling suite for CO2 storage (https://ccsnet.ai).