Kelvin Ng
Applied Scientist at Amazon Web Services (AWS)
California, United States
Summary
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Senior🎓
Top SchoolKelvin Ng is an Applied Scientist at AWS with 13 years of industry experience and a PhD in Computer and Information Science from the University of Pennsylvania, specializing in ML systems, inference frameworks, and accelerator runtimes. He currently contributes to MLSys research for AWS Trainium at Annapurna Labs and previously worked on topology-aware collective communication and in-place gradient compression at ByteDance. His PhD and internship work includes building Mimic, an approximate network simulator that used deep learning to achieve a 675x speedup for large fattree networks, highlighting his knack for combining ML with systems-level performance gains. Based in California, Kelvin bridges rigorous academic research with production-focused engineering to optimize ML inference and accelerator runtime stacks. Colleagues describe him as someone who translates complex low-level bottlenecks into practical, scalable system solutions that accelerate end-to-end ML workflows.
13 years of coding experience
The Chinese University of Hong Kong (CUHK)Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at University of Pennsylvania
Chinese, English, Chinese
Github Skills (132)
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distributed-computing8
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Programming languages (9)
Github contributions (5)
Kelvin-Ng/faiss
Jan 2019 - Jul 2019
A library for efficient similarity search and clustering of dense vectors.
Contributions:1 PR, 137 pushes, 4 branches in 5 months
approximate-nearest-neighbor-searchvectorssimilarity-searchmachine-learningsimilarity
Kelvin-Ng/Kelvin-Gentoo-Overlay
Jan 2014 - May 2016
Contributions:37 commits, 21 pushes, 1 comment in 2 years 4 months
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