Lijing is a third-year Ph.D. student in Geological Sciences. Her interests include Bayesian inversion, geometric and topological data analysis, geostatistics and deep learning (focusing on computer vision). Her research goal is to develop statistical methods to quantify uncertainty and make decisions in energy resources and environments. She is currently working on 3D subsurface structural modeling given geophysical data for groundwater and oil/gas reservoirs.

Honors & Awards

  • Harriet Benson Fellowship Award, Stanford University (06/2020)
  • Second Prize and Best use of Planet Data, Stanford Big Earth Data Hackathon (04/2018)

Professional Affiliations and Activities

  • Co-President, Association of Chinese Students and Scholars at Stanford (2019 - 2020)
  • Student Organizing committee, Women in Data Science @ Stanford Earth (2019 - 2019)

Education & Certifications

  • B.S., Peking University, Applied Mathematics (2017)
  • B.S., Peking University, Space Physics (2017)

Stanford Advisors

Work Experience

  • Data Science Intern, Total (6/15/2020 - 9/11/2020)

    AI & Geosciences Program, collaborating with Google Cloud Advanced Solutions Lab


    Sunnyvale, CA

  • Guest PhD Student, HydroGeophysics Group, Department of Geoscience, Aarhus University (6/12/2019 - 7/17/2019)



  • Teaching Assistant: GS 240 Data Science for Geoscience, Stanford University (1/1/2019 - 3/29/2019)



All Publications

  • Semantic Segmentation of Crop Type in Africa: A Novel Dataset and Analysis of Deep Learning Methods CVPR 2019 Rustowicz, R. M., Cheong, R., Wang, L., Ermon, S., Burke, M., Lobell, D. B. 2019