206-660-3027

Applications:
Healthcare Research, Social Science
Methodologies:
Artificial Intelligence, Causal Inference, Computing, Data Integration, Data Mining, Data Visualization, Databases and Data management, Machine Learning, Mathematical and Statistical Modeling, Natural Language Processing, Security and Privacy, Statistics, Survey Methodology
Relevant Projects:

NIH, FDA


Xu Shi

Assistant Professor

Department of Biostatistics

My methodological research focus on developing statistical methods for routinely collected healthcare databases such as electronic health records (EHR) and claims data. I aim to tackle the unique challenges that arise from the secondary use of real-world data for research purposes. Specifically, I develop novel causal inference methods and semiparametric efficiency theory that harness the full potential of EHR data to address comparative effectiveness and safety questions. I develop scalable and automated pipelines for curation and harmonization of EHR data across healthcare systems and coding systems.