Casey Graff
Chief Technology Officer at ComplyAuto
Irvine, California, United States
Summary
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Senior🎓
Top SchoolCasey Graff is a technology leader and Chief Technology Officer at ComplyAuto with 11 years of software and research experience building cloud-native RegTech solutions. He combines academic rigor from a PhD in Computer Science at UC Irvine with hands-on engineering, having published work on convolutional neural networks and developed forecasting tools for wildfire ignition and spread. Prior roles span bioinformatics programming at Scripps, software development at Qualcomm, and research that fused satellite data with weather reanalysis—an uncommon crossover that informs his data-driven approach to compliance automation. Based in Irvine, CA, he focuses on turning complex scientific models into production-ready systems that scale for regulated industries.
11 years of coding experience
7 years of employment as a software developer
University of California San DiegoComputer Science, Computer Science at College of the CanyonsUniversity of California, Irvine
Github Skills (24)
knn-classification10
predict9
prediction-model9
linear-regression9
modis9
logistic-regression9
regression8
lru6
regression-models6
python6
cache-storage5
machine-learning5
caching5
api3
computation3
Programming languages (3)
Github contributions (5)
caseyagraff/dagma
Feb 2020 - Jan 2022
A lightweight pipelining tool for computation.
Contributions:14 PRs, 30 pushes, 11 branches in 1 year 11 months
computationpipelining
UCIDataLab/fire_prediction
Aug 2017 - Jan 2020
Using statistical regression models to predict MODIS fire counts.
Contributions:78 commits, 2 PRs, 52 pushes in 2 years 5 months
regressionpythonregression-modelsknn-classificationlogistic-regression
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