Revealing Fundamental Physics from the Daya Bay Neutrino Experiment Using Deep Neural Networks. - Evan Racah; Seyoon Ko; Peter J. Sadowski; Wahid Bhimji; Craig Tull; Sang-Yun Oh; Pierre Baldi; Prabhat (ICMLA, 2016)

Optimal Minimization of the Sum of Three Convex Functions with a Linear Operator. - Seyoon Ko; Joong-Ho Won (AISTATS, 2019)

DistStat.jl: Towards Unified Programming for High-Performance Statistical Computing Environments in Julia. - Seyoon Ko; Hua Zhou 001; Jin Zhou; Joong-Ho Won (CoRR, 2020)

Splitting with Near-Circulant Linear Systems: Applications to Total Variation CT and PET. - Ernest K. Ryu; Seyoon Ko; Joong-Ho Won (SIAM J. Sci. Comput., 2020)

Computationally scalable regression modeling for ultrahigh-dimensional omics data with ParProx. - Seyoon Ko; Ginny X. Li; Hyungwon Choi; Joong-Ho Won (Briefings Bioinform., 2021)

A fast data-driven method for genotype imputation, phasing and local ancestry inference: MendelImpute.jl. - Benjamin B. Chu; Eric M. Sobel; Rory Wasiolek; Seyoon Ko; Janet S. Sinsheimer; Hua Zhou 001; Kenneth Lange (Bioinform., 2021)

Multivariate genome-wide association analysis by iterative hard thresholding. - Benjamin B. Chu; Seyoon Ko; Jin J. Zhou; Aubrey Jensen; Hua Zhou 001; Janet S. Sinsheimer; Kenneth Lange (Bioinform., 2023)

Sparse vertex discriminant analysis: Variable selection for biomedical classification applications. - Alfonso Landeros; Seyoon Ko; Jack Z. Chang; Tong Tong Wu; Kenneth Lange (Comput. Stat. Data Anal., 2025)