Nathan Beck

Applied Scientist at Amazon

Dallas-Fort Worth Metroplex United States
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Summary

👤
Senior
🎓
Top School
Nathan Beck is an applied scientist and PhD candidate in computer science at UT Dallas with 14 years of hands-on experience advancing active learning, NLP/LLMs, computer vision, and optimization. He combines academic rigor—4.0 across BS/MS/PhD studies—with industry impact from internships at Lawrence Livermore National Laboratory and an applied science role at Amazon, where he now contributes to production-scale classification and policy platforms. His research-driven approach to active learning informs practical solutions that reduce labeling costs and improve model efficiency, bridging theoretical methods and deployed systems. Based in the Dallas–Fort Worth area, he’s a lifelong learner who thrives on translating cutting-edge ML research into real-world applications.
code14 years of coding experience
job1 year of employment as a software developer
bookDoctor of Philosophy - PhD, Computer Science, 4.0, Doctor of Philosophy - PhD, Computer Science, 4.0 at The University of Texas at Dallas
bookHigh School Diploma, 4.0, High School Diploma, 4.0 at Claremore High School
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Github Skills (10)

solver9
pypy8
crossword8
application8
ssreflect8
pypi8
gpu7
multicore7
cuda6
python6

Programming languages (2)

C++Python

Github contributions (4)

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LLNL/ExaCMech

Nov 2018 - May 2021

Contributions:17 reviews, 114 commits, 17 pushes in 2 years 6 months
gpumath-physics
LLNL/SNLS

Sep 2018 - Aug 2020

GPU-friendly Small Non-Linear Solvers (SNLS)
Contributions:11 reviews, 81 commits, 1 PR in 1 year 11 months
ssreflectcrosswordsolverlinearnon-linear
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