Hyung Park

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).