Nguyen, N. C., Vila-Pérez, J., & Peraire, J. (2023). An adaptive viscosity regularization approach for the numerical solution of conservation laws: Application to finite element methods. Journal of Computational Physics, 112507.

Nguyen, N. C., & Rohskopf, A. (2023). Proper orthogonal descriptors for efficient and accurate interatomic potentials. Journal of Computational Physics, 480, 112030.

Nguyen, N. C. (2023). Fast proper orthogonal descriptors for many-body interatomic potentials. Physical Review B, 107(14), 144103.

Rohskopf, A., Goff, J., Sema, D., Gordiz, K., Nguyen, N. C., Henry, A., Thompson, A. P., & Wood, M. A. (2023). Exploring model complexity in machine learned potentials for simulated properties. Journal of Materials Research.

Vila-Pérez, J., Van Heyningen, R. L., Nguyen, N.-C., & Peraire, J. (2022). Exasim: Generating discontinuous Galerkin codes for numerical solutions of partial differential equations on graphics processors. SoftwareX, 20, 101212.

Nicolas G. Hadjiconstantinou and Mathew M. Swisher, “On the equivalence of nonequilibrium and equilibrium measurements of slip in molecular dynamics simulations,” Physical Review Fluids, 7, 114203, 2022

Nandy, A., Duan, C., Taylor, M.G., Liu, F., Steeves, A.H., & Kulik, H.J. (2021). Computational Discovery of Transition-metal Complexes: From High-throughput Screening to Machine Learning. Chemical Reviews, 121, 9927–10000.

William Moses, Valentin Churavy. “Instead of Rewriting Foreign Code for Machine Learning, Automatically Synthesize Fast Gradients.” In Advances in Neural Information Processing Systems 33 (NeurIPS 2020).