Research

My research interest lies in the areas of personalized medicine, risk prediction, effect heterogeneity, machine learning, transfer learning, and their applications in health sciences. I am dedicated to developing new statistical methodologies and collaborating with other investigators to conduct applied research in biomedical domains. I have developed a penalized regression-based learning procedure to construct optimal personalized dynamic treatment regimes, which can be inferred from accrued patient information and intervention effects. Additionally, I have led several research projects, including risk stratification using tree-based machine learning models and two-stage modeling to address patient heterogeneity.

Regarding collaborative efforts, I have worked with researchers across various fields, including oncology, surgery, immunology, and otolaryngology, and co-authored multiple peer-reviewed publications. This commitment was recognized through my receipt of the AWSM Collaboration Award, highlighting my contributions to advancing team science.

About

I received a BA and an MA in Statistics from Yonsei University, and a PhD in Biostatistics from Columbia University. My dissertation, co-advised by Drs. Min Qian and Ken Cheung, focused on statistical methods for optimal treatment regimes in personalized medicine and mobile health. After completing my PhD, I worked as a Postdoctoral Researcher at the University of Pennsylvania under the supervision of Dr. Jinbo Chen. Upon finishing my postdoc, I joined Northwell Health as an Assistant Professor.

News

• [2026] Received the AWSM Jack Weintraub Educational Advancement Award, Feinstein Institutes for Medical Research.
• [2026] Serving as Subaward PI on NIH NHLBI R01HL182015 (Cardiovascular Risk Prediction and Reduction in Men with Prostate Cancer).