My research spans singular perturbation theory, boundary and interior layer analysis, and structure-preserving numerical and learning-based methods for stiff partial differential equations. Recent work and selected earlier publications are listed below. A complete list of publications is available in my curriculum vitae.
Recent Work (2024–present)
Accepted
Singular layer neural network methods for singularly perturbed problems with C.-Y. Jung and J. Kim, book chapter in Multiscale Problems and Singular Perturbations: Recent Advancements in Numerical Analysis and Scientific Machine Learning, accepted.
Singular layer PINN methods for steep reaction-diffusion equations in convex polygonal domains with Y. Hong and C.-Y. Jung, AMS proceedings volume (ed. K. Yamazaki), accepted; to appear in 2027.
Finite volume neural networks for viscous Burgers equations in a rectangular domain with C.-Y. Jung and J. Kim, submitted.
Finite volume neural networks for singular perturbation problems in a rectangular domain with C.-Y. Jung and J. Kim, submitted.
Finite volume neural networks for singularly perturbed boundary value problems with J. Kim, submitted; revised version under review at the International Journal of Numerical Analysis and Modeling.
Physics-informed neural network approach for singular layers in periodic parallel pipe flows with M. Moon, Y. Hong, and C.-Y. Jung, submitted to the Journal of Computational and Applied Mathematics.