John Vivian
Senior Bioinformatics Scientist
Oxnard, California, United States
Summary
🤩
Rockstar🎓
Top SchoolJohn Vivian is a Senior Bioinformatics Scientist with 11 years of experience applying scalable computational methods to immune repertoire and oncology datasets, routinely analyzing hundreds of millions of antibody sequences. He holds a PhD from UC Santa Cruz where he co-developed Toil—a widely used open-source distributed workflow engine—and built cloud-native pipelines and a Bayesian framework for detecting gene expression outliers to inform drug selection. At Atreca and as a freelancer he designs Python/Nextflow pipelines, implements assay methods, and brings production-grade engineering practices (CI/CD, containerization, resource management) to bioinformatics workloads. Comfortable moving between research and production, he combines deep statistical modeling skills with systems-level engineering, and even brings a bit of technical metal and drumming to his multidisciplinary curiosity.
12 years of coding experience
10 years of employment as a software developer
University of California Santa Cruz
Github Skills (12)
testing10
batch10
docker10
batchfile10
python10
dockers10
batch-processing10
cicd10
mesos9
devops8
aws8
workflow-engine7
Programming languages (12)
Github contributions (5)
DataBiosphere/toil
May 2015 - Jan 2017
A WDL, CWL and Python API supporting easy-to-use workflow engine. It is scalable, efficient and cross-platform (Linux/macOS).
Role in this project:
Backend Developer & DevOps Engineer
Backend Developer & DevOps EngineerContributions:44 commits, 5 PRs, 51 pushes in 1 year 8 months
Contributions summary:John contributed significantly to the project by implementing and testing core functionalities within the Toil workflow engine, focusing on batch system integration. The user added new tests and refactored existing ones, specifically targeting the `SingleMachineBatchSystem` and the `GridEngineBatchSystem`. They also made improvements to the CI/CD pipeline and overall system infrastructure by incorporating Docker containers and entry points for pip installation. Additionally, the user addressed resource management concerns by modifying the resource request system.
linuxmacospythonwdlworkflow-engine
jvivian/gene-outlier-detection
Mar 2019 - May 2020
A Bayesian model for identifying gene expression outliers for individual single samples (N-of-1) when compared to a cohort of background datasets.
Contributions:130 commits, 56 PRs, 107 pushes in 1 year 1 month
bayesian
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