Bioinformatics at the intersection of data, software, and biology
I am a bioinformatics scientist at the Frederick National Laboratory for Cancer Research. I build practical, reproducible analysis systems that turn complex sequencing measurements into results researchers can explore, evaluate, and share.
My work spans single-cell and multimodal analysis, protein proximity and spatial data, epigenomics, long-read RNA modification analysis, and production sequencing workflows. Across these areas, I focus on scalable computation, traceable methods, accessible visualization, testing, and documentation.
What I work on
- Scientific software: interactive and reusable tools that move analysis beyond one-off notebooks.
- Single-cell and multi-omics: workflows for expression, protein abundance, spatial organization, and multimodal interpretation.
- Epigenomics and RNA modification: computational approaches for DNA methylation and direct-RNA m6A analysis.
- Reproducible infrastructure: tested workflows for HPC, containers, quality control, and production sequencing operations.
Featured work
ProxiomeVis provides an interactive Python Shiny workflow for exploring single-cell protein proximity data, including abundance, clustering, colocalization, differential analysis, patch analysis, and three-dimensional cell graphs.
scChromatic treats biological color assignments as persistent, auditable data so cell identities remain visually consistent across filtering, reordering, and separate figures. View the project.
ViewBS is a toolkit for visualizing high-throughput bisulfite sequencing data. View the software or read the paper.