Draft:U Jin Choi

U Jin Choi (최우진) is a Korean mathematician and Professor Emeritus of Mathematical Sciences at KAIST. He is mainly known for his work on numerical analysis, inverse problem, and mathematical finance.

Education and career
Choi studied mathematics at Seoul National University and completed his Ph.D. in 1987 at Carnegie Mellon University. His dissertation, Fractional Volterra Equations in Hilbert Spaces, was supervised by Richard C. MacCamy. In 1987, he became a faculty member of Department of Mathematical Sciences at KAIST.

In 2011, Choi received the Korean Mathematical Society Education Award for his contribution to education and talent development in the mathematics field. He is a founding member of the Korean Society for Industrial and Applied Mathematics (KSIAM).

Selected publications

 * Choi, U Jin; MacCamy, R. C (1989-05-01). "Fractional order Volterra equations with applications to elasticity". Journal of Mathematical Analysis and Applications. 139 (2): 448–464. doi:10.1016/0022-247X(89)90120-0.
 * Choi, U Jin; Kwak, Do Y. (1989-01-01). "Almost sure convergence of galerkin approximations for a heat equation with a random initial condition". Computers & Mathematics with Applications. 18 (12): 1057–1063. doi:10.1016/0898-1221(89)90032-1
 * Kim, Philsu; Choi, U. Jin (2000-12-30). "A quadrature rule of interpolatory type for Cauchy integrals". Journal of Computational and Applied Mathematics. 126 (1): 207–220. doi:10.1016/S0377-0427(99)00354-4
 * Shin, Yong Hyun; Lim, Byung Hwa; Choi, U Jin (2007-05-15). "Optimal consumption and portfolio selection problem with downside consumption constraints". Applied Mathematics and Computation. 188 (2): 1801–1811. doi:10.1016/j.amc.2006.11.053
 * Kwak, Minsuk; Shin, Yong Hyun; Choi, U Jin (2009-07-15). "Optimal portfolio, consumption and retirement decision under a preference change". Journal of Mathematical Analysis and Applications. 355 (2): 527–540. doi:10.1016/j.jmaa.2009.02.004
 * Choi, Yun Young; Park, Sun Woo; Woo, Youngho; Choi, U. Jin (2022-09-29). "Cycle to Clique (Cy2C) Graph Neural Network: A Sight to See beyond Neighborhood Aggregation". International Conference on Learning Representations 2023.