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General Information
Full Name | Justin Dong |
Education
- 2023 (expected)
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
- 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.
- 2015
Visiting Research Scholar
University of Stuttgart, Germany
- Implemented a discontinuous Galerkin finite element method for two-phase flow in heterogeneous media with discontinuous capillary pressures.
- Advisor - Rainier Helmig.
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)