Research Overview

I develop quantitative tools for summarizing and understanding high-dimensional genomic data.

Specific Methodologic Projects

• Extracting low-dimensional predictors from high-dimensional data.
• Dealing with dependence in high-dimensional data analysis.
• Quantifying noise in high-dimensional data.

Specific Applied Projects

• Reproducibility in clinical genomics.
• Batch effects in microarray and sequencing data.
• Predictive and prognistic genomic biomarkers for cancer.

New Paper: "A decision-theory approach to interpretable set analysis for high-dimensional data." See Publications .

New Paper: "Asymptotic conditional singular value decomposition for high-dimensional genomic data." See Publications .