Pohang University of Science and Technology (POSTECH)
Email: mchoi at postech.ac.kr
Assistant professor in Mathematics, POSTECH
Postdoc, Princeton Univeristy (mentor: Yannis Kevrekidis)
Ph.D. in Applied Mathematics, Brown University (advisor: George Karniadakis)
M.S. in Mechanical Engineering, Seoul National University (advisor: Frank Chongwoo Park)
B.A. in Mechanical Engineering and Mathematics, Seoul National University (dual major)
Scientific machine learning, AI for science, Uncertainty quantification (for machine learning), Scientific computing
I am looking for motivated students and postdocs who are interested in scientific machine learning, uncertainty quantification, and scientific computing. Please send me an email if you are interested.
2025-2026: Vice President, East Asia Society for Industrial and Applied Mathematics (EASIAM)
2025-: Associate Editor, East Asian Journal on Applied Mathematics
2025.08: Co-organized AI-CFD International Mini Symposium (Scientific Machine Learning and AI for CFD)
2025.08: Program Committee in Forum Math for Industry
2025.06: Executive Committee in EASIAM Annual Meeting
2025.02: Co-organized Scientific Machine Learning Workshop
2025.01: Co-organized International Conference on Navier-Stokes Equations and Numerical Analysis
2023.08: Local Committee in ICOSAHOM 2023
2023.08: Co-organized Physics-Informed Machine Learning Workshop
2022.08: Co-organized International Conference on Machine Learning and PDEs: Theory, Algorithms, and Its Applications
2021-2022: Managing Editor, Journal of the Korean Society for Industrial and Applied Mathematics
ThermalNet: Fast and Accurate Thermal Solver based on Operator Learning, in preparation
Physics-Informed Laplace Neural Operator, in preparation
Gaussian processes for nonlinear differential equations, in preparation
Operator learning methods for forward and inverse problem of fluid flow, in preparation
Plasma-simulation physics informed neural networks (PS-PINNs) for fluid simulation of DC discharge, in preparation
Neural Augmented Lagrangian Methods for Approximating Viscosity Solution of Eikonal Equation, under review
Prior-Date Fitted Scientific Foundation Model for In-context Learning without Equations, under review
Real-Time Physics-informed Reconstruction of Transient Fields Using Sensor Guidance and Higher-order Time Differentiation (with H. Noh, J. Park, and J.H. Lim), under review
Model-free Learning of Random Dynamical System from Noisy Observations (with K. Yeo, H. Shin, and H. Kim), Journal of Computational Physics, , 545, 114474, 2026
Stabilize physics-informed neural networks for stiff differential equations: Re-Spacing layer (with E. Kim, S. Cho, H. Kwon, and K. Yeo), Computers and Mathematics with Applications, 200, 167-179, 2025
Real-time full-field estimation of transient responses in time-dependent partial differential equations using causal physics-informed neural networks with sparse measurements (with H. Noh and J.H. Lim), Engineering Analysis with Boundary Elements, 179, 106363, 2025
Re-initialization Strategy for Physics-informed Neural Networks for Fluid Flow Analysis with Repetitive Parameter Initialization (with J. Lee, S. Shin, T. Kim, B. Park, H. Choi, A. Lee and S. Lee), Scientific Reports, 15(1), 1-16, 2025
Plasma-simulation physics informed neural networks (PS-PINNs) for global discharge models (with H. Kwon, E.Kim, S. Cho, D. Kwon, and H. Choe), East Asian Journal on Applied Mathematics, 14(3), 636-656, 2024
CEENs: Causality-enfored evolutional networks for solving time-dependent partial differential equation problems (with J.Jung, H. Kim, and H. Shin), Computer Methods in Applied Mechanics and Engineering, 427, 117036, 2024
Bayesian deep learning framework for uncertainty quantification in stochastic partial differential equations (with J. Jung and H. Shin), SIAM Journal on Scientific Computing, 46(1), C57-C76, 2024
Data-driven methods to quantify high-dimensional correlated uncertainties (with J. Jung), IEEE Access, 11, 50605-50618, 2023
Physics-informed variational inference for uncertainty quantification of stochastic differential equations (with H. Shin), J. Comp. Phys., 487, 112183, 2023
MGDGAN: Multiple Generator and Discriminator Generative Adversarial Networks for Solving Stochastic Partial Differential Equations (with S. Cho), IEEE Access, 10, 130908-130920, 2022
A robust bi-orthogonal/dynamically-orthogonal method using the covariance pseudo-inverse for the stochastic Navier-Stokes equations (with H. Babaee, T. Sapsis, and G.E. Karniadakis), J. Comp. Phys., 344, 303-319, 2017
Revisiting diffusion: self-similar solutions and the $t^{-1/2}$ decay in initial and initial-boundary value problems (with P.G. Kevrekidis, M.O. Williams, D. Mantzavinos, E.G. Charalampidis, and I.G. Kevrekidis), Quart. Appl. Math., 75, 581-598, 2017
Dimension reduction in heterogeneous neural networks: generalized Polynomial Chaos (gPC) and Analysis-Of-Variance (ANOVA) (with T. Bertalan, C.R. Laing, and I.G. Kevrekidis), Eur. Phys. J. Special Topics, 225(6), 1165-1180, 2016
On the equivalence of dynamically orthogonal and bi-orthogonal methods: theory and numerical simulations (with T. Sapsis, and G.E. Karniadakis), J. Comp. Phys., 270, 1-20, 2014
A convergence study for SPDEs using combined polynomial chaos and dynamically-orthogonal schemes (with T. Sapsis, and G.E. Karniadakis), J. Comp. Phys., 245, 281-301, 2013
Supercritical quasi-conduction states in stochastic Rayleigh Benard convection (with D. Venturi, and G.E. Karniadakis), Int. J. of Heat & Mass Transfer, 55(13-14), 3732-3743, 2012
Adaptive ANOVA decomposition of stochastic incompressible and compressible flows (with X. Yang, G. Lin, and G.E. Karniadakis), J. Comp. Phys., 231, 1587-1614, 2012
Error estimates for the ANOVA method with polynomial chaos interpolation: tensor product functions (with Z. Zhang, and G.E. Karniadakis), SIAM J. Sci. Comp., 34(2), A1165-A1186, 2012
Anchor points matter in ANOVA decomposition (with Z. Zhang, and G.E. Karniadakis), Spectral and High Order Methods for Partial Differential Equations, Lecture Notes in Computational Science and Engineering, 76, 347-355, 2011
Geometric direct search algorithms for image registration (with S. Lee, H. Kim, and F.C. Park), IEEE Transactions on image processing, 16, 2215-2224, 2007
Particle filtering on the Euclidean group: framework and applications (with J. Kwon, C. Chun, and F.C. Park), Robotica, 25, 725-737, 2007
National Research Foundation of Korea, Korea Institutue of Fusion Energy, Hyundai Mobis, POSCO Holdings, SK hynix.