William Judge
Senior Data Scientist
Greater Chicago Area United States
Summary
👤
Senior🎓
Top SchoolWilliam Judge is a Senior Data Scientist and machine learning researcher with eight years of experience applying advanced AI to energy storage and materials science, currently driving battery safety and health analytics at LG Energy Solution Vertech. He bridges lab-scale materials work—casting cathode materials and tomographic reconstruction contributions to tomopy—with production ML systems that assess State of Safety, Health, and Degradation for Li-ion packs at scale. At Element Energy he built cloud-deployed CI/CD pipelines, high-throughput time-series classifiers and sub-second anomaly detectors (AUROC/F1 >99%), and led data strategy efforts that turned battery analytics into recurring SaaS revenue. His Argonne collaborations produced distributed ML tooling for large-scale ptychography and a TomoSuite package for ML-driven tomography, reflecting a rare mix of experimental, algorithmic, and systems expertise. Proven at turning terabytes of complex scientific data into robust, monitored production services, he focuses on making batteries safer, more reliable, and more efficient.
8 years of coding experience
10 years of employment as a software developer
Doctor of Philosophy - PhD Materials Chemistry, Doctor of Philosophy - PhD Materials Chemistry at University of Illinois ChicagoBachelor of Science (B.S.) Chemistry, Bachelor of Science (B.S.) Chemistry at Baylor University
Github Skills (9)
image-reconstruction10
tomography10
python10
recovery10
image-processing10
numpy10
3d-reconstruction10
testing9
scipy8
Programming languages (6)
Github contributions (5)
tomopy/tomopy
Nov 2021 - Nov 2021
Tomographic Reconstruction in Python
Role in this project:
Data Scientist
Data ScientistContributions:5 reviews, 18 commits, 1 PR in 3 days
Contributions summary:William primarily contributed to the `tomopy` repository by implementing and refining image processing functions. Their work focused on improving the handling of non-finite values within the 3D image data, specifically by developing and enhancing a median filter. This includes adding a selective median filter, incorporating a callback function for progress tracking, and adding tests to ensure the function's robustness. These changes focused on improving the quality of tomographic reconstruction.
pythontomographyreconstructiontoolbox
WilliamJudge94/tomosuitepy
Jan 2021 - Jan 2024
TomoSuitePY is a culmination of machine learning networks and data preparation methods for those networks to enhance poor-quality tomographic datasets.
Contributions:2 PRs, 31 pushes, 2 branches in 3 years
machine-learning
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