I am a Ph.D. candidate in Biostatistics at Johns Hopkins University, jointly advised by Dr. Jiayi (Jessie) Tong and Dr. Elizabeth A. Stuart.
My primary research interests focus on real-world evidence synthesis, causal inference, and federated learning. Specifically, I have developed efficient and lossless distributed algorithms for multivariate longitudinal healthcare data across institutions while preserving patient privacy.
Beyond methodology, I am passionate about biostatistics education and have served as the lead organizer for the Biostatistics Education & Student Training (BEST) Seminar and the Johns Hopkins Causal Inference Working Group.
Education
Johns Hopkins University | Baltimore, MD Ph.D. in Biostatistics | Aug 2024 - Present
Duke University | Durham, NC M.S. in Statistical Science | Aug 2022 - May 2024 | Advised by Dr. Hwanhee Hong & Dr. Alexander Volfovsky
Carleton College | Northfield, MN B.A. in Statistics & Political Science | Aug 2018 - June 2022 | Advised by Dr. Andrew Poppick & Dr. Greg Marfleet
Honors & Awards
- ICSA Student Paper Award Winner (2026)
- PHAISE AI Research Day Student Award at Johns Hopkins University (2026)
- Teaching Assistant of the Year Award at Duke University (2024)
- Honorable Mention for BEST Award for Student Research at Duke University (2024)
- Dean’s Research Award for Master’s Students at Duke University (2023)
- Dean’s Research Award for Master’s Students at Duke University (2022)
- Phi Beta Kappa Society & Sigma Xi Society at Carleton College (2022)
- Magna Cum Laude at Carleton College (2022)
- Dean’s Honor List (Top 10% of Class, 2021)