about

About

I’m a bioinformatics scientist and tool developer working at the intersection of genomics, neuroscience data, and open-source software.

I have 0+ years in human-disease genomics — cancer, aging, and, most recently, adolescent brain development. I did my PhD in Genetics, Genomics & Bioinformatics at UC Riverside, and I now lead data-software development at the J. Craig Venter Institute.

I build the infrastructure and tools that make large-scale biological data usable: reproducible analysis pipelines (WGS/WES, bulk and single-cell RNA-seq, ChIP-seq) that run on laptops, HPC, and the cloud, plus the databases, APIs, and interactive apps researchers actually click through. I’ve authored 0+ R/Bioconductor packages and contributed to 0+ open-source projects.

A lot of my work lives at the seam between analysis and interface. I’m a long-time Shiny / web developer (top 0% on StackOverflow under “shiny”, runner-up in the 3rd global Shiny Contest), and I care about turning one-off analyses into shareable, maintainable software — from the systemPipe workflow ecosystem to the portal and score packages powering the ABCD Study.

Focus

  • Disease genomics
  • Reproducible pipelines
  • Data engineering
  • R / Bioconductor
  • Shiny / web apps
  • Machine learning
  • Data visualization

Experience

  • 2025 — Present

    Senior Bioinformatics Scientist / Engineer / J. Craig Venter Institute

    Lead production data software for the ABCD Study — ABCDscores, NBDCtools, and the DEAP backend — and standardized data ingestion and QC across the team.

  • 2023 — 2025

    Data Scientist / Engineer / UC San Diego Health

    Built the data infrastructure and ETL pipelines (Docker, Kubernetes, GitHub Actions, Airflow) for the ABCD Study, serving hundreds of internal scientists across 24 sites and thousands of external researchers.

  • 2023

    Postdoc Researcher / UC Riverside

    Developed bioinformatics tooling for computational drug discovery and built web-accessible drug-discovery databases and APIs.

  • 2018 — 2019

    Bioinformatician / Aspen Neuroscience

    Analyzed sequencing data for the safety of Parkinson’s autologous stem-cell therapy and built 100TB+ data infrastructure.