Publications: JRSS-A, JAMA Oncology, ICML 2025, JAMA Network Open, Biostatistics, Journal of the American Statistical Association; Funded Project: NIH K01 funded 'Causal Machine Learning Methods to Study Individual Vaccine Efficacy Using Multi-Source Data'; Talks: Methods Workshop at Brandeis-Harvard SPIRE Center; Discussant: Harvard Data Science Initiative Causal Seminar.
Research Experience
Assistant Professor of Biostatistics in the Department of Public Health and Health Sciences at Northeastern University and an Affiliate Investigator in the Vaccine and Infectious Disease Division at the Fred Hutch Cancer Center.
Education
PhD in Biostatistics from Harvard University, advised by Tianxi Cai and Lorenzo Trippa; Postdoc in Health Care Policy at Harvard Medical School, mentored by Sharon-Lise Normand; AM in Biostatistics from Harvard; MPhil in Healthcare Operations from the University of Cambridge; MA in Global Affairs from Tsinghua University; BS in Public Health and Biostatistics from UNC-Chapel Hill.
Background
Research focuses on developing novel statistical and machine learning methods to leverage real-world data to improve decision-making, with a focus on public health and clinical medicine. Current areas of interest include causal inference, conformal inference, data integration, federated learning, and survival analysis.
Miscellany
Outside of work, enjoys playing golf, staying up-to-date on global affairs, and cheering on the UNC Tar Heels.