I previously was a graduate student researcher within the Computational Science Laboritory at Virginia Tech, focusing on machine learning applications within numeriacal analysis and uncertainty quanitfication.

Publications & Presentations

Adjoint-Matching Neural Network Surrogates for Fast 4D-Var Data Assimilation
A. Chennault, A. Popov, A. Subrahmanya, R. Cooper, A. Karpatne, A. Sandu
Virginia Tech 2021

Investigation of Nonlinear Model Order Reduction of the Quasigeostrophic Equations through a Physics-Informed Convolutional Autoencoder
R. Cooper, A. Popov, A. Sandu
Virginia Tech 2021

Augmented Neural Network Surrogate Models for Polynomial Chaos Expansions and Reduced Order Modeling
R. Cooper
Virginia Tech (Thesis) 2021

Machine Learning applications in Uncertainty Quanitification
R. Cooper, A. Moosavi, A. Sandu, V. Rao
SIAM CSE Conference (Minisymposia talk) 2019
Media: [Presentation]

Projects

ML Autotuning of CFD Simulation
R. Cooper, A. Sandu, D. Tafti, P. Windes
2017-2019