Sufficient Dimension Reduction

  • Extended sufficient dimension reduction methods to multivariate, survival, and non-elliptical settings.

    • Reference

    • Minjee Kim, Minjeong Kim and Jae Keun Yoo. (2026). Non-elliptical Dimension Reduction in Survival Regression. Stat.
    • Minjee Kim & Jae Keun Yoo. (2025). Covariance Projective Resampling Informative Predictor Subspace for Multivariate Regression. Journal of the Korean Statistical Society.
    • Minjee Kim & Jae Keun Yoo. (2024). Applications of response dimension reduction in large p-small n problems. Communications for Statistical Applications and Methods.


    Functional Data Analysis

  • Developed model-based nonlinear sufficient dimension reduction methods for functional data.

    • Reference

    • Minjee Kim, Yujin Park, Kyongwon Kim and Jae Keun Yoo. (2025). Nonlinear Functional Sufficient Dimension Reduction via Principal Fitted Components. Statistics and Computing.


    Applied Collaboration

  • Developed a dynamic mortality prediction model for prostate cancer patients in Sunnybrook Health Sciences Centre.

    • Reference

    • Eunseon Seong, Minjee Kim, Dareen Eom, Gyeonghwa Heo, Urban Emmenegger, Saleh Tabatabaei, Tayler Declan Ross and Michael Hardisty. Dynamic Mortality Prediction for Prostate Cancer based on Irregularly Sampled Multimodal EHR and Musculoskeletal Image-based Biomarkers. PAKDD 2026.