Education
- Ph.D. Chemical and Systems Biology, Stanford University
- M.Phil. Computational Biology, University of Cambridge
- B.S. Chemical Engineering, Michigan State University
Experience
Parker Institute for Cancer Immunotherapy
Senior Data Scientist (2022 Apr – 2023 Mar)
Data Scientist (2018 May – 2022 Mar)
- Analyzed high-dimensional data from patient samples to understand pharmacodynamic responses to treatment and to identify relevant prognostic and predictive biomarkers.
- Led the data analysis efforts for a multi-arm prostate cancer trial studying novel drug combinations.
- Led collaborative projects with NanoString to analyze transcriptomic datasets from immuno-oncology trials and to validate spatial transcriptomic technology for use in Parker Institute projects.
- Developed internal software packages and infrastructure for reproducible data processing and statistical analysis.
- Coordinated with large cross-functional teams to deliver analyses for external presentations, publications, and regulatory filings.
Insight Data Science
Health Data Science Fellow (2018 Jan – Apr)
- Processed high-dimensional bacterial abundance data from a pediatric Crohn’s disease cohort.
- Predicted disease states from microbiome data using supervised learning methods.
UC Berkeley
Post-doc research in Michael Eisen’s lab (2016 – 2017)
- Modified developmental genes in Drosophila to determine how specific sequences affect patterning.
- Performed live confocal imaging at single-nucleus resolution to track and quantify promoter activation.
Stanford University
Ph.D. student in David Kingsley’s lab (2008 – 2015)
- Mapped genetic loci associated with phenotype differences in fish populations (threespine stickleback) using QTL mapping, and identified specific mutations underlying evolved changes in morphology.
- Compared gene expression between marine and freshwater fish within rapidly evolving genomic regions, as part of a large-scale project to describe genetic variation across many stickleback populations.
- Designed custom gene expression microarrays for stickleback eQTL studies, using SNP data from next-gen sequencing to optimize probe design.
- Taught summer courses on how to perform genetic mapping and how to create transgenic fish.
University of Cambridge
Master’s student in Michele Vendruscolo’s lab (2007)
- Collected protein structural data from public databases and generated initial states for simulations.
- Ran parallel protein dynamics simulations on a managed compute cluster to generate ensembles of protein conformations, which were subjected to constraints derived from experimental NMR data.