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
Posts by Collection
publications
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 For Misspecified Models
Beomjo Park, Sivaraman Balakrishnan, Larry Wasserman.
Biometrika., 2025
⁕ Winner of ASA Statistical Learning and Data Science Student Paper Award
talks
Bayesian Multivariate Hierarchical Semiparametric Mixed Model with Gaussian Process Priors
Bayesian Hierarchical Varying-coefficient Mixed Effect Model
Spatio-Temporal Local Interpolation for Quantifying Global Ocean Heat Transport from Autonomous Observations Permalink
teaching
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
- 2021-2022 PhD TA of the Year Award
- Summer Undergrad Research Experience (SURE)
- Optum [Summer 23]
- Carnegie Mellon Sports Analytics Camp (CMSAC) [Summer 20, 21]
- Introduction to Statistical Inference [Spring 22]
- Advanced Methods for Data Analysis [Spring 20, 21]
- Probability and Mathematical Statistics [Fall 19, 20, 22; Spring 19]
- Statistical Graphics and Visualization [Summer 19]
- Statistical Computing [Fall 18]