Ildoo Kim
Korea University · Mathematics
About the Lab
Professor Ildoo Kim's research lab specializes in mathematical analysis of stochastic and fractional partial differential equations, with a focus on developing rigorous $L_p$- and $L_q(L_p)$-theories for both linear and quasi-linear SPDEs. The lab investigates the existence, uniqueness, and regularity of solutions to equations with Caputo-type time derivatives and random noise, often employing advanced tools from harmonic analysis and stochastic calculus. In parallel, the lab explores innovative deep learning techniques, particularly in test-time augmentation and spatially aware neural network architectures, aiming to improve model robustness and feature representation. The interdisciplinary work bridges theoretical PDEs with practical applications in machine learning and data science.
Research Overview
Research Output Trend
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Selected Papers
15In this article, we present an $L_{p}$-theory ($p\geq 2$) for the semi-linear stochastic partial differential equations (SPDEs) of type \begin{equation*}\partial^{\alpha }_{t}u=L(\omega ,t,x)u+f(u)+\partial^{\beta }_{t}\sum_{k=1}^{\infty }\int^{t}_{0}(\Lambda^{k}(\omega,t,x)u+g^{k}(u))\,dw^{k}_{t},\end{equation*} where $\alpha \in (0,2)$, $\beta <\alpha +\frac{1}{2}$ and $\partial^{\alpha }_{t}$ and $\partial^{\beta }_{t}$ denote the Caputo derivatives of order $\alpha $ and $\beta $, respective
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We introduce an $L_q(L_p)$-theory for the quasi-linear fractional equations of the type $$ \partial^α_t u(t,x)=a^{ij}(t,x)u_{x^i x^j}(t,x)+f(t,x,u), \quad t>0, \,x\in \mathbf{R}^d. $$ Here, $α\in (0,2)$, $p,q>1$, and $\partial^α_t$ is the Caupto fractional derivative of order $α$. Uniqueness, existence, and $L_q(L_p)$-estimates of solutions are obtained. The leading coefficients $a^{ij}(t,x)$ are assumed to be piecewise continuous in $t$ and uniformly continuous in $x$. In particular $a^{i
Research Areas
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