She develops statistical methods, tools and software for the analysis of genomics data. Her research addresses statistical challenges in epigenomics, functional genomics and single-cell genomics such as the pre-processing, normalization, analysis of raw, noisy high-throughput data (microarray and next-generation sequencing) leading to improved quantification and understanding of biological variability. She taught the major data science course at Harvard before joining the faculty at Johns Hopkins. She also writes the blog Statistical Recipes which combines statistics and cooking (yum!).