Research

I am a Biostatistics PhD student at UNC-Chapel Hill, working in statistical and computational genomics in the Won Lab. I am interested in how genetic variation affects gene regulation and cellular function, and in statistical methods that help interpret genomic experiments.

Single-cell genomics

My interests include cell-type-specific perturbation responses, differential gene expression, and gene programs in single-cell data. CROP-seq connects genetic perturbations with single-cell transcriptional readouts.

Functional and regulatory genomics

I work with high-throughput functional experiments, including massively parallel reporter assays (MPRA), to study regulatory activity and the effects of genetic variants. My research interests span MPRA, single-cell MPRA, and CRISPR perturbation data.

Statistical methodology

I am interested in statistical modeling and scalable computation for high-dimensional genomic data, including count data and differential expression in perturbation studies.

Publications and preprints · Software & Packages

Earlier work and study notes

My background includes dimension reduction, optimization, quantum computing, Bayesian statistics, and statistical theory. The Blog & Archive preserves these notes and teaching materials.