Nathan Beck
Applied Scientist at Amazon
Dallas-Fort Worth Metroplex United States
Summary
👤
Senior🎓
Top SchoolNathan 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.
14 years of coding experience
1 year of employment as a software developer
Doctor of Philosophy - PhD, Computer Science, 4.0, Doctor of Philosophy - PhD, Computer Science, 4.0 at The University of Texas at DallasHigh School Diploma, 4.0, High School Diploma, 4.0 at Claremore High School
Github Skills (7)
gpu9
solver9
multicore9
pypi8
pypy8
application8
python7
Programming languages (2)
Github contributions (4)
llnl/ExaCMech
Nov 2018 - May 2021
A GPU-friendly materials library with a focus on crystal plasticity methods
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
gpusolvermath-physics
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