Geoff Stanley
Learning Sabbatical
Palo Alto, California, United States
Summary
👤
Senior🎓
Top SchoolGeoff Stanley is a software engineer and data scientist with eight years of experience building evaluation frameworks, monitoring pipelines, and production-ready ML systems for high-stakes products. He led technical efforts at GRAIL that unlocked a 10x data increase, drove SOTA classifier validations, and cut failure rates in half through statistical process modeling and monitoring. Currently he applies that eval and monitoring expertise to Tesla Autopilot and FSD/Robotaxi validation while also pursuing CS coursework and an educational LLM RL framework during a learning sabbatical at Stanford. Trained as a PhD biophysicist with a strong computational genomics background, he’s comfortable bridging wet-lab insight and large-scale ML engineering. Notably, his work on uncovering and fixing data artifacts in graduate research yielded dramatic reductions in contamination and drew mainstream attention, illustrating a knack for finding subtle failure modes others miss. Based in Palo Alto, he blends rigorous research instincts with hands-on production delivery in safety-critical ML.
8 years of coding experience
8 years of employment as a software developer
Physiology Summer Course, Physiology Summer Course at Woods Hole Oceanographic InstitutionUniversity of California, San DiegoDoctor of Philosophy (PhD) Biophysics, Doctor of Philosophy (PhD) Biophysics at Stanford University
Github Skills (30)
structural-variation10
tabula10
single-cell-analysis10
cancer-genomics9
variants9
transcriptomics9
biomedical9
fusion9
annotations8
microscopy7
rna-seq7
image-analysis6
neuroimaging5
rna-velocity5
python5
Programming languages (5)
Github contributions (5)
gmstanle/nf-core-scisoseq
Nov 2019 - Aug 2020
Contributions:32 pushes, 1 branch in 8 months
gmstanle/cs231n
Jun 2020 - Feb 2021
Contributions:18 pushes, 1 branch in 7 months
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