Yongqiang Huang
高性能计算库工程师 at 寒武纪
Beijing, China
Summary
👤
Senior🎓
Top SchoolYongqiang Huang is a high-performance computing library engineer at Cambricon in Beijing with eight years of experience combining deep academic research and production engineering. He holds a Ph.D. in Computer Science and built a celebrated recurrent neural network model for robotic liquid pouring that matches human speed and grace while outperforming state-of-the-art methods on unseen containers. His expertise spans RNNs, imitation learning, time-series regression and robotic motion generation, and he has translated research insights into practical, high-throughput implementations for hardware-accelerated environments. Notably, his work demonstrates rare rigor in generalization: low average pouring errors (4.12–12.35 mL) on containers excluded from training, indicating strong transfer capability.
8 years of coding experience
Master of Science (M.S.), Electrical Engineering, Master of Science (M.S.), Electrical Engineering at North Carolina State UniversityDoctor of Philosophy (Ph.D.), Computer Science, Doctor of Philosophy (Ph.D.), Computer Science at University of South FloridaBachelor of Engineering (B.Eng.), Electronics Engineering, Bachelor of Engineering (B.Eng.), Electronics Engineering at Beijing University of Posts and Telecommunications
Chinese, English
Github Skills (4)
spider6
api5
python4
python-requests4
Programming languages (2)
Github contributions (5)
tsmotlp/Attentions-on-Image
Apr 2019 - May 2019
Contributions:27 commits, 25 pushes, 1 branch in 15 days
Deep-Imaging-Group/SDSR-OCT
Apr 2019 - Dec 2020
Contributions:22 commits, 21 pushes, 1 branch in 1 year 8 months
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