NobleĀ Kennamer
Research Scientist at Netflix
Los Gatos, California, United States
Summary
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Top SchoolNoble Kennamer is a research scientist and soon-to-be Ph.D. in Computer Science from UC Irvine with 11 years of experience applying machine learning and Bayesian statistics to real-world scientific problems. He specializes in variational methods for optimal experimental design and has built active learning and uncertainty-aware deep learning systems that have been integrated into the data pipeline of the largest astronomical sky survey. His work spans graph neural nets, spatiotemporal architectures for confounding factors, and satellite-based rainfall prediction, reflecting a knack for translating domain expertise into production-ready models. Prior internships at Google and a current research role at Netflix underscore his ability to move models from research to operational settings. Based in Los Gatos, he combines rigorous physics and mathematics training with a pragmatic engineering mindset and is actively seeking full-time opportunities.
11 years of coding experience
7 years of employment as a software developer
Bachelor of Science - BS, Physics, GPA: 3.99, Bachelor of Science - BS, Physics, GPA: 3.99 at University of California, Irvine
Github Skills (29)
classification8
bayesian-statistics8
astronomy7
recommendation-system7
bayesian-inference7
data-analysis5
pymc5
data-science5
statistical-inference4
bayesian4
python4
deep-learning3
ai3
active-learning3
pytorch3
Programming languages (4)
Github contributions (5)
NobleKennamer/astro_porject
Nov 2015 - Dec 2015
Contributions:30 pushes, 1 branch, 11 comments in 15 days
NobleKennamer/Quasar-Emission-Spectrum
Jul 2015 - Aug 2015
Contributions:24 pushes, 1 branch in 1 month
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