Focus areas: data science: Python, pandas, R, computational cancer genomics, cancer genomics tools development, multi-omics analysis pipelines, methods development, tumor classification, machine learning: random forests, SVMs, ensembles, deep learning: TensorFlow, scVI, DNA methylation profiling, single-cell analysis.

Creating tools and methods to better diagnose, classify, understand, and target cancer.

Outside of work, I like to create tools to optimize stuff.

Circos plot of a cancer genome: chromosomes around the circle, with copy-number, mutation and expression tracks inside

Latest · Oct 2026

Minty: designing a self-hosted personal finance aggregator

A private dashboard for every bank and card transaction, running on your own free Cloudflare and...

Sep 2026

Museum Reciprocal Finder: from schematic to implementation

A static web app that tells you which museums your membership gets you into free or...

Apr 2026

Tidy sample metadata with pandas before any modeling

Clean sample IDs, validate every join and fix dtypes in pandas before metadata problems quietly break...

Nov 2025

A neural network methylation classifier in TensorFlow, and when it beats a random forest

A Keras MLP for DNA methylation tumor classification, built and compared fairly against a random forest...

Focus areas RPythonTensorFlow

Recent publications All →

  1. 2025DNA Methylation-Based Classification of Kidney Neoplasms
  2. 2025Tumor heterogeneity underlies clinical outcome and MEK inhibitor response in somatic NF1-mutant glioblastoma
  3. 2025Longitudinal multimodal profiling of IDH-wildtype glioblastoma reveals the molecular evolution and cellular phenotypes underlying prognostically different treatment responses
  4. 2023Novel SOX10 indel mutations drive schwannomas through impaired transactivation of myelination gene programs

Career

Currently
Research Engineer @ Stanford
Previously
Clinical Informatics Specialist @ UCSF
Education
PhD @ UC Merced

Publications

17 peer-reviewed papers
665citations
13h-index

Get in touch