I’m a statistician and work as an Assistant Professor at the division of biostatistics at the New York University School of Medicine. I received my Ph.D. in biostatistics from Columbia University in 2018, advised by Dr. Todd Ogden. I also earned a MS in biostatistics at Harvard and a MS in applied & computational math at Johns Hopkins University. My research focus is on developing analytical tools for studying effects of interactions between a variable (e.g., “treatment” variable) and a set of variables on their effects on an outcome, using semiparametric regression methods. This is mainly motivated by an ultimate goal of making patient-specific (“personalizing”) treatment decisions based on individual patients’ pretreatment characteristics.
My particular interest here is in some specific types of high-dimensional patient characteristics that are observed in the form of curves or images; for instance, measurements from electroencephalogram (EEG) or magnetic-resonance-imaging (MRI). Such data can be viewed as functional, and such data are becoming increasingly prevalent in a modern randomized clinical trial setting as patient-specific information. I also work on Bayesian methods for matrix-valued regression.
I like reading (particularly science or history books) and hiking, and try to walk at least 2 hours a day (NYC is a great place to walk).
(Selected) Publications/Preprints
Ju, X., Park, H., and Tarpey, T., “Projection-pursuit Bayesian regression for symmetric matrix predictors” arXiv (preprint) [pdf]
Ju, X., Park, H., and Tarpey, T., “Bayesian scalar-on-network regression with applications to brain functional connectivity” arXiv (preprint) [pdf]
Park, H., “Bayesian estimation of covariate-assisted principal regression for brain functional connectivity” Biostatistics (2024) [pdf][Supp.]
Park, H., Tarpey, T., Petkova, E., and Ogden, R.T., “A high-dimensional single-index regression
for interactions between treatment and covariates” Statistical Papers (2024) [pdf][Supp.]
Park, H., Wu, D., Petkova, E., Tarpey, T. and Ogden, R.T., “Bayesian index models for heterogeneous treatment effects on a binary outcome” Statistics in Bioscience (2023) [pdf]
Park, H., Yu, C., Pirofski, L. …, “Association between COVID-19 convalescent plasma antibody levels and outcomes stratified by clinical status at presentation” BMC Infectious Diseases (2024) [pdf][Supp.]
Park H., Tarpey T., Liu M., Goldfeld K., …, Troxel, A., Antman, E., Petkova E., “Development and validation of a treatment benefit index to identify who may benefit from convalescent plasma among patients hospitalized with COVID-19” JAMA Network Open (2022) [pdf][Supp.]
Park, H., Petkova, E., Tarpey, T., and Ogden, R.T., “Functional additive models for optimizing individualized treatment rules” Biometrics (2022) [pdf][Supp.]
Park, H., Petkova, E., Tarpey, T., and Ogden, R.T., “A constrained single-index regression for estimating interactions between a treatment and covariates.” Biometrics (2021) [pdf][Supp.]
Park, H., Petkova, E., Tarpey, T., and Ogden, R.T., “A single-index model with a surface-link for optimizing individualized dose rules” Journal of Comput. and Graphical Statistics (2021) [pdf][Supp.]
Park, H., Petkova, E., Tarpey, T., and Ogden, R.T., “A sparse additive model for treatment effect-modifier selection” Biostatistics (2020) [pdf][Supp.]
Park, H., Petkova, E., Tarpey, T., and Ogden, R.T., “A single-index model with multiple-links.” Journal of Statistical Planning and Inference (2020) [pdf]
Park, H. and Lee, S., “Logistic regression error-in-covariate models for longitudinal high-dimensional covariates” Stat. (2019) [pdf][Supp.]
Petkova, E., Park, H., Ciarleglio, A., Tarpey, T., and Ogden, R.T., “Optimizing treatment decision rules through generated effect modifiers: A precision medicine tutorial.” BJPsych Open (2019) [pdf]
Levins, R., Awerbuch, T., and Park, H.,“Managing populations with unimodal dynamics.” Applied Mathematics (2013) [pdf]
