Jane Zhou
Sales-manager at Key Stone Electronic
Shenzhen, Guangdong Province, China
Summary
🤩
Rockstar🎓
Top SchoolJane Zhou is a sales manager specializing in distribution of HPC and AI components—GPUs, CPUs, SSDs, HDDs and servers—bridging technical supply chains between vendors like NVIDIA, Mellanox, Intel, AMD and enterprise clients across Hong Kong, Shenzhen, South Korea and Singapore. With six years’ experience and a strong VIP client base (e.g., CMHK, VIVO), she combines commercial acumen with hands-on technical support enabled by field application engineers and ODM services. Unusually for a sales leader, Jane also contributes to open-source ML projects like PaddlePaddle, where she has implemented and optimized core operators and tests, giving her deep visibility into customers’ software-hardware integration needs. Based in Shenzhen and fluent in business English, she’s positioned to translate complex AI component shortages into reliable supply solutions for enterprise customers.
6 years of coding experience
6 years of employment as a software developer
商务英语, 商务英语 at 湘南学院
Github Skills (27)
pytorch10
benchmark10
c-language10
testing10
machine-learning10
benchmarking10
deeplearning-ai10
deep-learning10
cuda10
paddlepaddle10
cprogramming-language10
optimization10
distributed-training9
convolutional-neural-networks9
python9
Programming languages (6)
Github contributions (5)
PaddlePaddle/benchmark
Nov 2021 - Mar 2022
Role in this project:
ML Engineer
ML EngineerContributions:14 reviews, 9 commits, 21 PRs in 3 months
Contributions summary:Jane primarily contributed to the project by adding and modifying tests for PaddlePaddle's dynamic API benchmark, focusing on operations related to convolutional neural networks (conv1d), matrix operations (bmm, eigh, matrix_rank), and group normalization. Their commits involved implementing new tests, fixing existing ones, and ensuring compatibility with both PaddlePaddle and PyTorch. The user also updated the testing framework to include new features like the 'atol' parameter.
PaddlePaddle/Paddle
Jul 2021 - Jun 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:Back-end Developer & ML Engineer
Back-end Developer & ML EngineerContributions:141 reviews, 29 commits, 72 PRs in 10 months
Contributions summary:Jane primarily contributed to the optimization and implementation of core functionalities within the PaddlePaddle deep learning framework. Their work focused on optimizing the backward pass of the `index_select` and `gelu` operators and implementing new operators for `eigh`, `gather_tree`, and `broadcast_sub`, `broadcast div`. These changes involved significant code modifications within the C++ and CUDA kernels of the framework. The user demonstrated a strong understanding of deep learning concepts and framework internals.
pytorchpythonparalleldeep-learningpaddlepaddle
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