Yujie Tao specializes in optimization and uncertainty quantification in combustion kinetics and is proficient at combustion modeling, Fortran, Linux Shell and Matlab. She also has previous experience in flame synthesis and soot laser diagnostics experiments.

Honors & Awards

  • Distinguished Paper Award, 35th International Symposium on Combustion (2015)
  • Provost's Fellowship, University of Southern California (2011)
  • Distinguished Paper Award, China National Symposium on Combustion (2010)
  • National Scholarship, Ministry of Education of China (2009)

Professional Affiliations and Activities

  • Reviewer, ASME Turbo Exp (2018 - Present)
  • Member, The Combustion Institute (2013 - Present)

Education & Certifications

  • M.S., University of Southern California, Mechanical Engineering (2013)
  • B.S., Tsinghua University, Energy, Power System and Automation (2011)

Stanford Advisors

Current Research and Scholarly Interests

Combustion kinetics, model optimization, uncertainty quantification


  • Foundational Fuel Chemistry Model, Stanford, SRI

    Foundational Fuel Chemistry Model is mainly the result of a long-term, ongoing research collaboration between Hai Wang’s research group at Stanford University and Gregory Smith of the SRI International. Its primary objective is to advance a reaction model for the combustion of small hydrocarbon fuels using up-to-date kinetic knowledge and with well-defined predictive uncertainties. The optimized and uncertainty minimized model for H2, H2-CO, and CH4 combustion, FFCM-1, has been released in 2016 with a comprehensive fundamental combustion database.



  • JP-10 HyChem Model Development, Stanford University, University of Southern California, University of Illinois at Chicago

    A collaborative development of a Hybrid Chemistry combustion model of JP-10 involving parameter optimization with flow reactor and shock tube pyrolysis data.



Lab Affiliations

All Publications