Camden Shultz
Software Engineer at The Johns Hopkins University Applied Physics Laboratory
Baltimore, Maryland, United States
Summary
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Rockstar🎓
Top SchoolCamden Shultz is a software and machine learning engineer with 7 years of experience, currently building robust forecasting, anomaly detection, and decision-making systems at The Johns Hopkins Applied Physics Laboratory. He focuses on efficient, deployment-ready ML for high-stakes, real-world problems and previously developed on-device epilepsy prediction models at the Center for Implantable Devices. Camden pairs academic rigor—MEng and BS from Johns Hopkins—with hands-on internship and teaching experience across NLP, data structures, and physics, making him comfortable translating research into production. Based in Baltimore, he enjoys tackling complex problems where model robustness and resource constraints matter, and he brings a practical bent for making high-impact systems both reliable and operational.
7 years of coding experience
3 years of employment as a software developer
Johns Hopkins UniversityInternational Baccalaureate, HL: Mathematics, Physics, Chemistry - SL: English, German, Geography, International Baccalaureate, HL: Mathematics, Physics, Chemistry - SL: English, German, Geography at International School of Basel
German, English
Github Skills (59)
watson10
monitor10
python10
data-mining10
incremental-learning10
machine-learning10
gluon10
dvc10
java10
scale10
deep-learning10
privacy-preserving10
sql10
fairness-ml10
golang10
Programming languages (8)
Github contributions (5)
CenterforImplantableDevices/CenterforImplantableDevices.github.io
Aug 2022 - Aug 2023
Built version of the Lab's website: cid.wse.jhu.edu
Contributions:2 releases, 2 PRs, 244 pushes in 11 months
CWrecker/DrinkMaker
Mar 2019 - Jul 2021
Contributions:8 commits, 7 pushes, 1 branch in 2 years 3 months
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