Columbia University in the City of New York · Mathematics & StatisticsCohort Analytics Hub
Yifei Sun · New York, New York
Research Focus
Dr. Yifei Sun's lab focuses on developing advanced statistical methods to enhance the analysis of diverse longitudinal cohort studies, particularly in understanding COVID-19 risk factors. By addressing challenges like systematically missing data and study heterogeneity, the lab creates improved tools for clinical and epidemiological research. Their innovative approaches aim to provide reliable resources for researchers integrating data from multiple studies.
Cohort StudiesStatistical MethodsCOVID-19Data IntegrationMissing DataPredictive ModelingGeneralized Method of MomentsEpidemiological ResearchMeta-Analysis
Research Aims
4AIM 01Develop a Generalized Method of Moments framework for analyzing missing data in cohort studies.
AIM 02Create nonparametric predictive models to handle various data issues from multiple studies.
AIM 03Extend methods for analyzing time-to-event data in the presence of censoring.
AIM 04Evaluate the proposed statistical methods through simulations and real-world data applications.
Skills the Lab Values
Statistical ModelingAlgorithm DesignData AnalysisGradient BoostingSimulation StudiesCohort AnalysisProgramming in R or PythonUser Interface DevelopmentLongitudinal Data Analysis
Output against the department
Publications219bottom 47% of dept.69th of 131
this lab
most publishedleast published
Citations7.0kbottom 47% of dept.69th of 131
this lab
most citedleast cited
Career totals from OpenAlex, compared against labs that share a department. A department spans everything from one paper to tens of thousands, so bar heights are on a log scale — otherwise the largest lab would flatten every other bar to a line.