Kelvin Ng

Applied Scientist at Amazon Web Services (AWS)

California, United States
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Summary

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Senior
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Top School
Kelvin 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.
code13 years of coding experience
bookThe Chinese University of Hong Kong (CUHK)
bookDoctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at University of Pennsylvania
languagesChinese, English, Chinese
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Github Skills (99)

lsh10
audio9
nodejs-client9
clustering9
approximate-nearest-neighbor-search9
ffmpeg9
cities-skylines-game8
cpp8
orientdb8
tablet8
mpv8
cities-skylines8
typescript8
mplayer7
ipados7

Programming languages (10)

C#TypeScriptC++ShellSchemeCRustJavaScript

Github contributions (5)

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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
Contributions:37 commits, 21 pushes, 1 comment in 2 years 4 months
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