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General Information

Full Name Justin Dong

Education

  • 2023
    Ph.D. - Applied Mathematics
    Brown University, Providence, Rhode Island
  • 2019
    M.Sc. - Applied Mathematics
    Brown University, Providence, Rhode Island
  • 2014
    B.A. - Computational and Applied Mathematics; B.S. Mechanical Engineering
    Rice University, Houston, Texas

Experience

  • 2023 - present
    Postdoctoral Research Scholar
    Center for Applied Scientific Computing, Lawrence Livermore National Laboratory, Livermore, CA
    • Analyzed time integration methods and physics couplings in Earth system models; high-order finite element methods; physics-informed machine learning for approximating PDEs.
  • 2019 - present
    Graduate Research Assistant
    Division of Applied Mathematics, Brown University, RI
    • Developed and analyzed neural network methods for approximating PDEs.
    • Advisor - Mark Ainsworth.
  • 2022
    Graduate Research Intern
    Pacific Northwest National Laboratory, WA
    • Developed machine learning methods for learning particle stresses in suspension Poiseuille flows.
    • Mentor - Amanda Howard.
  • 2018
    Graduate Research Intern
    Lawrence Livermore National Laboratory, CA
    • Worked on the lab's RAJA (high-performance computing portability abstraction layer) and mint (mesh generation) libraries; produced application examples (discontinuous Galerkin methods for vacuum Maxwell's equations).
    • Mentor - Arturo Vargas.

Honors and Awards

  • 2018-2022
    • National Science Foundation Gradaute Research Fellowship

Academic Interests

  • Numerical Analysis
  • Scientific Computing
  • Scientific Machine Learning

Other Interests

  • Hobbies: photography (see my photos here), hiking, growing houseplants (especially of the tropical variety)