About me

I am a fifth-year Ph.D. student in the Department of Statistics & Data Science at Carnegie Mellon University, Pittsburgh, PA. Current research interests largely lie in the robust statistical inference including how to better accommodate the model misspecification. I am very fortunate to be advised by Sivaraman Balakrishnan and Larry Wasserman. I have also been collaborating with oceanographers and Mikael Kuusela on developing statistical framework for large-scale oceanographic data. I am a member of the Statistical Machine Learning Reading group and the Statistical Methods for the Physical Sciences group.

Prior to joining the Carnegie Mellon University, I have worked on wide-ranging applications and extensions in the Bayesian semiparametric regression and Variational inference while pursuing an M.Sc. in Statistics at Korea University advised by Taeryon Choi. Hierarchical modeling and fast Variational Bayes approximation to the flexible Bayesian regression framework were the central themes. I earned B.Sc. in Industrial engineering and Statistics at Korea University.


  • Robust statistical inference
  • Model misspecification
  • Statistical learning theory
  • Nonparametrics