Research Projects
I am broadly interested in statistics and biostatistics, with a current focus on statistical learning, precision medicine, integrative analysis, behavioral task analysis, missing data, survival data, conformal inference, nonparametric and semiparametric statistics, and applications in mental health and diabetes. This page provides an overview of the main projects I have worked on and am currently pursuing. Click on each project title for more details, including related papers and presentations. If you prefer to view my papers by year, please see this link.
This work employs several machine learning techniques to predict Titanic passenger survival, confirming that women and wealthy individuals were more likely to survive, with the Conditional Forest method achieving the highest accuracy of 81.34%.
