Posts by Collection


A variational Bayes approach to a semiparametric regression using Gaussian process priors

Victor M. H. Ong, David K. Mensah, David J. Nott, Seongil Jo, Beomjo Park, Taeryon Choi.
Electric Journal of Statistics. 11(2) pp. 4258-4296, 2017

bsamGP: An R Package for Bayesian Spectral Analysis Models Using Gaussian Process Priors

Seongil Jo, Taeryon Choi, Beomjo Park, Peter Lenk.    Journal of Statistical Software. 90(10), pp. 1-41, 2019

Sparse signal shrinkage and outlier detection in high-dimensional quantile regression with variational Bayes

Daeyoung Lim, Beomjo Park, David Nott, Xueou Wang, Taeryon Choi.
Statistics and Its Interface. 13(2), pp. 237 – 249, 2020

Bayesian semiparametric mixed effects models for meta‐analysis of the literature data : An application to cadmium toxicity studies

Seongil Jo, Beomjo Park, Yeonseung Chung, Jeongseon Kim, Eunji Lee, Jangwon Lee, Taeryon Choi.
Statistics in Medicine., 2021

Spatio-temporal Local Interpolation of Global Ocean Heat Transport using Argo Floats: A Debiased Latent Gaussian Process Approach

Beomjo Park, Mikael Kuusela, Donata Giglio, Alison Gray.    Annals of Applied Statistics., 2023

Robust Universal Inference

Beomjo Park, Sivaraman Balakrishnan, Larry Wasserman.   
⁕ Winner of ASA Statistical Learning and Data Science Student Paper Award


Bayesian Multivariate Hierarchical Semiparametric Mixed Model with Gaussian Process Priors

Bayesian Hierarchical Varying-coefficient Mixed Effect Model


Teaching Assistant

Undergraduate & graduate course, Korea University, 2016–2017

  • Research Methods [Fall 17]
  • Mathematical Statistics [Fall 17]
  • Statistical Computing Methods [Spring 17]
  • Elementary Computing Statistics [Fall 16]

Teaching Assistant

Undergraduate & graduate courses and research workshop, Carnegie Mellon University, 2018–2023