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I am an Associate Professor in the Department of Biostatistics at University of Michigan. Previously I was a postdoctoral fellow at the Harvard Data Science Initiative, working with Tianxi Cai and Eric Tchetgen Tchetgen in the Department of Biostatistics at the Harvard TH Chan School of Public Health. I did my Ph.D. in Biostatistics at University of Washington, under the supervision of Andrea Cook and Patrick Heagerty. I obtained my B.S. in Mathematics and Applied Mathematics with a minor in English at the Chu Kochen Honors College of Zhejiang University, China.
My research focuses on developing statistical methods to address the challenges of using real world data, including electronic health records (EHR) and claims data, in biomedical research. In particular, I advance negative control methods for causal inference with applications to comparative effectiveness and safety studies, and I develop statistical methods to improve the harmonization and analysis of multi-institutional EHR data, with the broader goal of generating more reliable and impactful real world evidence to inform public health decisions. I co-lead the Causal Inference Core of the FDA’s Sentinel Initiative, where I develop innovative statistical methods to monitor the effectiveness and safety of FDA-regulated medical products. I serve as PI on an NIH/NIGMS R01 grant focused on addressing hidden bias in post-marketing vaccine effectiveness and safety studies, an FDA Prescription Drug User Fee Act (PDUFA) VII project on automated selection of negative controls, and an FDA Sentinel project on EHR data harmonization. In addition to my research, I developed a semester-long course on EHR data analysis at the University of Michigan and have taught related short courses at leading venues, including the Joint Statistical Meetings, the Deming Conference on Applied Statistics, and the New England Statistics Symposium. I currently serve on the editorial boards for the Journal of the Royal Statistical Society: Series B (JRSSB) and the Annals of Applied Statistics (AOAS). I have received a number of honors and awards for my research including the Committee of Presidents of Statistical Societies (COPSS) Emerging Leader Award, the Institute of Mathematical Statistics (IMS) Thelma and Marvin Zelen Emerging Women Leaders in Data Science Award, the National Academy of Medicine (NAM) Emerging Leaders Forum, and the American Statistical Association (ASA) Outstanding Statistical Application Award. |
My research at a glance: data science + EHR + causal inference
Coding differences between Henry Ford Health System and Kaiser Permanente Northern California and differential utilization patterns
The future does not affect the past: past health outcome is a negative control in air pollution study to mitigate unmeasured confounding
Rare adverse event necessitates flexible propensity score methods
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Medical knowledge extraction from co-occurrence pattern in EHR and ICD code translation between Partners HealthCare and Veterans Health Administration: spherical data corrupted by mismatch
Estimation of natural indirect effect robust to unmeasured confounding and measurement error in the mediator
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