Yuanjun Li is a Ph.D. Candidate from Energy Resources Engineering. She is currently working on time-series missing data imputation and well historical data analysis with deep learning approaches. In addition, she has broad interests in thermal energy resources including geothermal energy and solar thermal energy.

Honors & Awards

  • LASPE Scholarship - Graduate Student Awards of Excellence, SPE-Los Angeles (2018)
  • University Scholarship - Excellent Student Awards, CUPB (2015)
  • National Scholarship, China Scholarship Council (2014)
  • Enterprise Scholarship - Excellent Student Awards, SINOPEC (2013)

Professional Affiliations and Activities

  • Teaching Assistant, ENERGY 175: Well Test Analysis (2020 - 2020)
  • Research Assistant, Smart Fields Consortium (2018 - Present)
  • Research Assistant, SUPRI-D (2018 - Present)

Education & Certifications

  • PhD, Stanford University, Energy Resources Engineering (2022)
  • MS, University of Southern California, Petroleum Engineering (2018)
  • BS, China University of Petroleum, Beijing, Storage &Transportation Engineering (2016)
  • Exchange Scholar, University of Tulsa, Petroleum Engineering (2014)

Current Research and Scholarly Interests

- Application of deep learning approaches for pressure history regeneration.
- Smart oilfield technologies and oilfield optimization
- Time series production data analysis with deep learning