Former students

• Kyuhwan Kim (김규환), M.S.

  • Thesis: Feature selection and ensemble methods to high dimensional pharmacogenomics data, February 2021.

  • Other publication: Kim K, Kim W*. (2021) Feature selection and prediction modeling of drug responsiveness in Pharmacogenomics, The Korean Journal of Applied Statistics, 34 (2), 153-166. (KCI)

  • After graduation: Ph.D. program in the Department of Statistics at Seoul National University

• Tian Liu (유천천), M.S.

  • Thesis: Hybrid modeling of copulas and linear mixed effects for longitudinal data, February 2020.

  • After graduation: Data mining related position in China

• Junoh Heo (허준오), M.S.

  • Thesis: Modified Bayesian Information Criterion for Longitudinal Data, February 2020.

  • Other publication: Heo J, Lee JY, Kim W*. (2020) Bayesian information criterion accounting for the number of covariance parameters in mixed effects models, Communications for Statistical Applications and Methods. 27 (3), 301-311. (SCOPUS)

  • After graduation: Ph.D. program in the Department of Statistics and Probability at Michigan State University

• Soyeon Jeon (전소연), M.S.

  • Thesis: Deep learning and ensemble methods to predict drug responsiveness in high-dimensional pharmacogenomics data, August 2019.

  • After graduation: Macrogen

• Soyeon Park (박소연), M.S.

  • Thesis: Multifactor Dimensionality Reduction Allowing for Genotyping Error in Next Generation Sequence Experiments, February 2018.

  • Other publication: Park S, Kim W^∗. (2017) Multifactor Dimensionality Reduction Method Based On Area Under Receiver Operating Characteristic Curve. Model Assisted Statistics and Applications; 12 (3): 245– 253. (SCOPUS)

  • After graduation: Ph.D. program in the Department of Biostatistics at SUNY Buffalo