Computational cancer biologist and Adjunct Assistant Professor at UCLA. I build the pipelines, tools, and analyses that turn high-dimensional sequencing and spatial data into biological and therapeutic insight. I want to ensure that these are reproducible and usable by other scientists.
- 🔬 Focus: cancer immunogenomics · neoantigen/HLA analysis · spatial single-cell · bioinformatics tooling · LLM/agent tooling for biology
- 🧰 Work in: Python · R · Docker · WDL/Nextflow · cloud data pipelines
- 🤝 Collaborate with academic, biotech, and nonprofit teams to ship tools biologists actually use.
| Project | What it does |
|---|---|
| HLA-HAT (docs) | HLA Haplotype Analysis Toolkit — analyzes HLA genes in DNA/RNA sequencing data (Python, Dockerized, WDL) |
| bio-agent | Agentic interface to biological databases (UniProt, Ensembl, NCBI) with input guardrails, evals, and a drug-target dossier mode (Python) |
| GenVisR | Co-developed R/Bioconductor package for genomic-cohort visualization (~68K downloads on Bioconductor) |
| CIViC · DGIdb | Open-source knowledgebases for clinical variant interpretation & drug–gene interactions |
| MORRISON-1 | Harmonized melanoma immune-checkpoint-therapy sequencing cohorts (public dataset release) |
| SpaceBender | Deep-learning method to denoise spatial-transcriptomics data (senior author; preprint) |