I am an Assistant Professor in the department of Biostatistics at UCLA. Previously, I was a postdoctoral research fellow working with Dr. Rui Duan in the Biostatistics Department at Harvard T.H. Chan School of Public Health.  I received my Ph.D. in Biostatistics from the University of Washington, where I was advised by Dr. Alex Luedtke. 

I am interested in developing efficient statistical methods for learning from imperfect, heterogeneous real-world data. A central theme of my work is to enable valid inference when key variables are missing,

delayed, expensive to measure, or only available across complementary data sources.  These scientific questions of interest often concern estimands arising from the fields of causal inference and optimization. Specifically, my goals are: 

1. Identification and efficiency: to identify parameters of interests and extract information from heteheterogeneous data sources in an unbiased and efficiency way. 

2. Implementation: to address challenges inherent in real-world applications of data fusion.

Keywords:

Methods: semiparametric efficiency theory; causal inference; data fusion; federated learning; transfer learning.

Applications: clinical trial; electronic health record data; infectious disease; mental health; health equity; model fairness. 

You can find my cv here.