Currently I am a post doctoral researcher at the Center for Mathematics and Artificial Intelligence (CMAI)
and the Center for Computational Fluid Dynamics (CFD)
in the research group of Prof Harbir Antil and Prof Rainald Löhner.
George Mason University
4400 University Drive
Exploratory Hall, room 4104
Fairfax, Virginia 22030
E-mail : rprice25 [at] gmu.edu
My research interests are primarily in partial differential equations, data assimilation, fluid dynamics, uncertainty quantification, numerical analysis, and deep learning.
CV(Last updated 10/2022)
Research Statement(Last updated 10/2022)
Google Scholar1. Data Assimilation for Neural Network Surrogate PDE Models
2. Learning One Time Step of a Chemically Reacting Flow
3. Comparison of Ensemble Kalman filter and Nudging Algorithm for the Navier-Stokes Equations
1. H. Antil, R. Löhner, R. Price. NINNs: Nudging induced neural networks. (submitted to SIAM journal on Scientific Computing).
2. H. Antil, R. Löhner, R. Price. Data assimilation with deep neural nets informed by nudging. (in review for Computer Methods in Applied Mechanics and Engineering).
3. B. Sousedik, H. Elman, K. Lee, R. Price. On surrogate learning for linear stability assessment of Navier--Stokes equations with stochastic viscosity. Applications of Mathematics (2022): 1-23.
4. B. Sousedik, R. Price. A stochastic Galerkin method with adaptive time-stepping for the Navier--Stokes equations. Journal of Computational Physics 468 (2022): 111456.
5. A. Biswas, R. Price. Continuous data assimilation for the three-dimensional Navier--Stokes equations. SIAM Journal on Mathematical Analysis 53.6 (2021): 6697-6723.