Xiaoyang Wu
Summary
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RockstarXiaoyang Wu is a PhD candidate in Computer Science at The University of Hong Kong with seven years of experience spanning research, R&D, technical consulting, and sales across automotive and IT industries. He has held research internships at leading labs including Meta Reality Labs, Apple, Shanghai AI Lab, Alibaba’s autonomous driving team, and SenseTime, focusing on spatio-temporal representations and applied machine learning. A strong quantitative foundation from Sun Yat-sen University and UC Berkeley (mathematics/statistics) complements his hands-on work on perception and electrification-driven digitalization problems. Comfortable in multicultural environments, he combines rapid learning with practical cross-functional collaboration, uniquely bridging academic research and industry deployment. Colleagues describe him as inquisitive and team-oriented, with a track record of translating advanced research into product-relevant solutions.
8 years of coding experience
Github Skills (59)
pytorch10
convolutional-neural-networks10
memory-efficient10
siggraph10
merlin10
point-cloud10
docker-image9
ss9
trojan9
xray9
asuswrt-merlin9
self-supervised-learning9
v2ray9
octree9
3d-reconstruction9
Programming languages (6)
Github contributions (5)
Gofinge/CheXpert_Baseline_PyTorch
Aug 2019 - Mar 2020
A simple baseline model for CheXpert - DenseNet121. Contain train and test module. Also a simple and easy-used deep learning framework by PyTorch!
Contributions:15 commits, 12 pushes, 1 branch in 7 months
deep-learningpytorch
Gofinge/Analysis-of-Stock-High-Frequent-Data-with-LSTM
Aug 2018 - Mar 2019
A simply framework of researching stock data through LSTM by Tensorflow
Contributions:35 commits, 2 PRs, 16 pushes in 6 months
lstmtensorflow
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