Xuanyi Chew
Sydney, New South Wales, Australia
Summary
🤩
RockstarXuanyi Chew is a software engineer and machine learning practitioner with 14 years' experience focused on building high-performance numerical and ML systems, now based in Sydney. He is the author and principal maintainer of Gorgonia, a Go library for automatic differentiation and neural computation, where he has driven SIMD and AVX-based optimizations to accelerate matrix and vector operations. Comfortable across Python, R and Go, his strengths include regression, Bayesian statistics, PCA, SVMs and sparse coding, and he enjoys applying ML and statistical methods across advertising, travel and finance. He prefers interesting, domain-driven consulting roles and combines research-grade ideas (e.g., complexity theory and evolutionary dynamics) with pragmatic performance engineering. Notably, he treats correctness and speed as co-equals—adding thorough low-level tests alongside assembly-style optimizations—and is reachable at chewxy [at] gmail.com.
14 years of coding experience
Stackoverflow
168reputation
12kreached
3answers
1question
Github Skills (12)
go10
performance-optimization10
linear-algebra10
numerical-computing9
algorithm6
cuda6
opencv6
mat6
cgo6
linker6
image-processing6
java6
Programming languages (13)
Github contributions (5)
gorgonia/gorgonia
Sep 2016 - Jul 2022
Gorgonia is a library that helps facilitate machine learning in Go.
Role in this project:
Back-end Developer and Performance Engineer
Back-end Developer and Performance EngineerContributions:29 releases, 13 reviews, 1339 commits in 5 years 11 months
Contributions summary:Xuanyi primarily contributed to performance optimizations by implementing SIMD acceleration with AVX instructions for matrix and vector operations within the Gorgonia library. They optimized numerical functions for faster execution of matrix multiplication, division, and similar operations. Furthermore, the user added tests to ensure the correctness and efficiency of these low-level optimizations, highlighting a focus on both correctness and speed in the library's numerical capabilities.
golangcomputation-graphautomatic-differentiationdeep-learningdifferentiation
gorgonia/bindgen
Feb 2018 - Feb 2021
Contributions:18 commits, 13 pushes, 1 branch in 3 years
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