206-660-3027

Applications:
Bioinformatics, Clinical Research, Computational Linguistics, Electronic Medical Record Data, Epidemiology, Learning Health Systems, Medical Informatics, Precision Health, Precision Medicine, Public Health, Research Reproducibility, Survey Research
Methodologies:
Algorithms, Artificial Intelligence, Causal Inference, Computational Tools for Data Science, Data Collection Design, Data Management, Data Mining, Data Quality, Data Security and Privacy, Data Visualization, Decision Science, Deep Learning, Digital Data Curation, Econometrics, Heterogeneous Data Integration, High-Dimensional Data Analysis, Longitudinal Data Analysis, Machine Learning, Missing Data and Imputation, Natural Language Processing, Predictive Modeling, Real-time Data Processing, Statistical Inference, Statistical Modeling, Statistics, Survey Methodology, Time Series Analysis
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.