Lijing is a third-year Ph.D. student in Geological Sciences. Her interests include Bayesian inference, geometric and topological data analysis, geostatistics and deep multi-task learning. Her research goal is to develop statistical methods to quantify uncertainty and make decisions in energy resources and environments. She is currently working on groundwater and targeted nitrate management, crop type mapping and landslides hazards.

Honors & Awards

  • Second Prize and Best use of Planet Data, Stanford Big Earth Data Hackathon (04/2018)

Professional Affiliations and Activities

  • 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

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