Ming-xu Huang
Senior Software Engineer at NVIDIA
Old Toronto, Ontario, Canada
Summary
🤩
Rockstar🎓
Top SchoolMing-xu Huang is a Senior Software Engineer with a decade of experience, currently contributing to NVIDIA from Old Toronto. He pairs strong academic foundations—a Master's in Computer Science from 國立交通大學—with hands-on work in high-performance ML systems. His open-source contributions to PaddlePaddle include implementing automatic sparsity utilities, such as mask generation and sparsity checks, reflecting practical expertise in model optimization and distributed training. Ming-xu excels at bridging research-grade algorithms and production-ready infrastructure, with a track record of shipping performant, scalable components for industrial ML frameworks. Colleagues know him for tackling low-level efficiency problems that meaningfully reduce training cost and complexity.
11 years of coding experience
Bachelor's degree, Computer Science and Engineering, Bachelor's degree, Computer Science and Engineering at 國立中興大學Master's degree, Computer Science and Information, Master's degree, Computer Science and Information at 國立交通大學
Chinese, English
Github Skills (6)
neural-network10
paddlepaddle10
machine-learning10
deeplearning-ai10
deep-learning10
python10
Programming languages (4)
Github contributions (5)
PaddlePaddle/Paddle
May 2021 - Dec 2022
PArallel Distributed Deep LEarning: Machine Learning Framework from Industrial Practice （『飞桨』核心框架，深度学习&机器学习高性能单机、分布式训练和跨平台部署）
Role in this project:
ML Engineer
ML EngineerContributions:64 reviews, 11 commits, 20 PRs in 1 year 6 months
Contributions summary:Ming-xu contributed utilities and helper functions for automatic sparsity in the PaddlePaddle framework. The primary focus of the code changes was the implementation of automatic sparsity features. This included adding functionalities related to mask generation algorithms and sparsity checking approaches.
deep-learningmachine-learningpaddlepaddlescalabilityneural-network
mingxu1067/Paddle
May 2021 - Oct 2023
PArallel Distributed Deep LEarning: Machine Learning Framework from Industrial Practice （『飞桨』核心框架，深度学习&机器学习高性能单机、分布式训练和跨平台部署）
Contributions:99 pushes, 31 branches in 2 years 5 months
pytorchparalleldeep-learningreinforcement-learningindustrial
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