About Me

Hello and welcome! 👋

I am currently a Postdoctoral Fellow in the Biostatistics Branch, Division of Cancer Epidemiology and Genetics (DCEG), National Cancer Institute (NCI), National Institutes of Health (NIH). I have the great privilege of working with Senior Principal Investigators Paul S. Albert and Jianxin Shi, whose mentorship continues to shape how I think about statistics, science, and meaningful research questions.

I earned my Ph.D. in Mathematical Statistics (2025) from the University of Maryland, College Park (UMD). I was very fortunate to be advised by Prof. Doron Levy and co-mentored by Senior Principal Investigators Paul S. Albert, Jianxin Shi and Hyokyoung G. Hong through the NIH Graduate Partnerships Program (GPP).

Before UMD, I received my Master’s degree in Mathematics (2016) from the University of Science and Technology of China (USTC), mentored by Profs. Xinan Ma and Hui Liu. I completed my Bachelor’s degree in Mathematics and Applied Mathematics (2014) at Nanjing Normal University (NNU), under the guidance of Prof. Yujun Dong.

In short: I have been happily doing math for quite a while now—and somehow it keeps getting more interesting. 😊

Research Interests

My research sits at the intersection of statistics and public health. I am broadly interested in developing state-of-the-art statistical methods while asking scientifically meaningful questions about the etiology of human diseases.

More specifically, I work on:

• Statistical modeling for correlated biomedical outcomes, including longitudinal analysis of repeated measurements, diagnostic testing, and biomarker studies, where data are often complex, dependent, and high-dimensional.
• Statistical and computational methods in genetics and genomics for analyzing electronic health records (EHR), real-world data (RWD), and large-scale population studies (e.g., the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial), with particular emphasis on genome-wide analyses for precision risk stratification, early detection, and risk prediction of prostate cancer.
• Statistical and machine learning approaches in epidemiologic research, including machine learning (ML), deep learning, and large language models (LLMs), with applications in cancer genetic epidemiology, nutritional epidemiology, and metabolomics.

I am especially motivated by problems where rigorous methodology meets real-world clinical impact.

Hobbies

Beyond research, I enjoy staying active and spending time outdoors—hiking, camping, kayaking, skating, and skiing—as well as dancing, swimming and playing badminton. If it involves fresh air or movement, I’m usually in.

I also love exploring new places and restaurants (statistical sampling, but for food). I’m an avid reader, particularly books on art, aesthetics, philosophy, and history, and I maintain a regular meditation practice to stay grounded—which turns out to be quite helpful when models refuse to converge.

In addition, I have a deep appreciation for classical music and the performing arts. I enjoy attending symphony concerts and opera performances, and I occasionally play the Guzheng, a traditional Chinese string instrument.

I also enjoy writing as a way to reflect on daily life and express my thoughts and feelings, particularly my appreciation for beauty and the subtle grace of imperfection (wabi-sabi). I also enjoy card games and painting—one grounded in strategy, the other in quiet creativity.

Recent News

• 2026-08-03: Thrilled to present our work on uncovering the heritability of longitudinal EHR traits under informative measurement processes (with Xing Hua, Xiaoyu Wang, Samuel Anyaso-Samuel, Jianxin Shi, and Paul S. Albert) at the JSM 2026 in Boston, Massachusetts, United States.
• 2026-07: Thrilled to be invited to present our work on heritability analysis for longitudinal phenotypes (with Xiaoyu Wang, Jianxin Shi, and Paul S. Albert) at the International Biometric Conference (IBC) 2026 in Seoul, South Korea.
• 2026-04: Thrilled to announce that our paper, Estimating the Heritability of Longitudinal Rate-of-Change: Genetic Insights into PSA Velocity in Prostate Cancer-Free Individuals, has been accepted for publication in the Biostatistics.
• 2026-03: Honored to receive the Institute of Mathematical Statistics (IMS) New Researchers Travel Award and the National Science Foundation (NSF) Travel Support Award.
• 2026-03: Honored to serve as a committee member for the NIH Fellows Award for Research Excellence (FARE) 2027.
• 2025-07-08: Honored to receive the NIH Fellows Award for Research Excellence (FARE) 2026 (top 25% of all applicants).
• 2025-03-22: Thrilled to announce that our paper, Mixed Modeling Approach for Characterizing the Genetic Effects in a Longitudinal Phenotype, has been accepted for publication in the Annals of Applied Statistics.