Minseok Choi

About me

• 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)

Research Interests

Scientific machine learning, AI for science, Uncertainty quantification (for machine learning), Scientific computing

Publications

• 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 (with H. Kwon, E.Kim, S. Cho, D. Kwon, and H. Choe), in preparation

• Stabilize physics-informed neural networks for stiff differential equations: Re-Spacing layer (with E. Kim, S. Cho, H. Kwon, and K. Yeo), under review

• Learning Random Dynamical System from Noisy Observations (with K. Yeo and H. Shin), under revision

• 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