I develop computational methods and open-source software that connect genomic and transcriptomic variation to the proteins expressed by tumors. My work focuses on making proteogenomic analysis comprehensive, reproducible, and scalable—from workflow engineering and non-canonical peptide identification to the interpretation of cancer genomes and proteomes.

I apply these methods to questions in cancer diagnosis, prognosis, treatment response, sex differences, and neoantigen discovery. I am particularly interested in translating robust computational tools into biological and clinical insight.