George Armstrong
Senior Research Scientist at NVIDIA
San Diego Metropolitan Area United States
Summary
👤
Senior🎓
Top SchoolGeorge Armstrong is a Senior Research Scientist with a PhD in Bioinformatics and Systems Biology and a decade of experience applying machine learning and computational methods to genomics and microbiome data. He has driven productionization of large language models for drug discovery and built deep learning pipelines for germline variant calling and qPCR analysis while at NVIDIA and Thermo Fisher. His work bridges rigorous academic research—four first-authored papers and contributions to numerous peer-reviewed articles—with hands-on engineering to deploy models at scale in industry. Based in San Diego, he combines applied mathematics training with high-performance computing expertise to extract regulatory insights from complex biological datasets. Less obvious: he frequently translates active learning and contrastive learning ideas from research into labeling and production workflows that materially improve genomics throughput. He excels at turning theoretical statistical methods into robust, deployable solutions for biomedical problems.
10 years of coding experience
8 years of employment as a software developer
University of California, San DiegoApplied Mathematics, Applied Mathematics at Colgate University
Github Skills (127)
python10
forge10
microbiome10
computational-biology10
machine-translation10
scikit10
statistics10
ncbi10
multimodal10
nmt10
generative-ai10
phylogeny10
chatbot10
nlp-machine-learning10
rclr10
Programming languages (6)
Github contributions (5)
gwarmstrong/taxa-assign-benchmarking
Aug 2019 - Oct 2019
Snakemake workflow for benchmarking taxonomy assignments
Contributions:139 commits, 13 PRs, 114 pushes in 2 months
snakemake-workflowbenchmarkingbenchmarksnakemaketaxonomy
biocore/q2-umap
Nov 2019 - Jun 2021
Applying umap to microbiome data via QIIME2
Contributions:1 release, 2 reviews, 91 commits in 1 year 6 months
bootstrappingbioinformaticsmicrobiome-datamicrobiomesnakemake
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