Hokwon Cho

Hokwon Cho is an Associate Professor in the Department of Mathematical Sciences at the University of Nevada, Las Vegas (UNLV). His expertise includes Statistical Decision Theory, Sequential Analysis, Ranking and Selection Methods, Linear Models, and Sampling Methods with a focus on Statistical Computing. His research emphasizes methodologies for multinomial models, clinical trials, radial basis functions, and numerical approximations.

Cho's work centers on developing statistical methodologies for decision-making under uncertainty, particularly in sequential sampling frameworks. His recent articles address confidence interval estimation for risk ratios, multinomial cell counts, and binomial proportions, reflecting his deep engagement with sequential analysis and statistical inference. His contributions also extend to numerical methods for solving partial differential equations using Trefftz methods and addressing computational challenges in statistical modeling.

No scientific awards are explicitly mentioned in the provided text. His advising and grant activities are not detailed here, though his research interests suggest involvement in methodological advancements. Cho's research integrates theoretical statistics with computational techniques, bridging applied and computational mathematics.