Lijing is a Ph.D. candidate in the Department of Geological Sciences at Stanford University. Her research focuses on using data-driven methods for efficient and sustainable groundwater exploration and exploitation. She is currently working on 1) geomodelling with electromagnetic images using computer vision methods and 2) Bayesian uncertainty quantification method for reservoir predictions and further decision making. She is passionate about teaching data science methods to geoscience audiences and the broader scientific community.
Previously, she did a Research Data Scientist internship in Total E&P, collaborating with Google Cloud. This work focuses on AI solutions to optimize geophysical data interpretation. Prior to Stanford, Lijing received her Bachelor of Science degree in Space Physics and Applied Mathematics from Peking University.