Bingkun Huang
Software Engineer at Google
Nanjing City, Jiangsu, China
Summary
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Rockstar🎓
Top SchoolBingkun Huang is a software engineer at Google with eight years of experience building production systems and researching video representation learning, with Google Scholar citations exceeding 800. He combines deep research chops—co-author of CVPR and ICCV-accepted work on video self-supervision—with practical engineering roles including internships at Google, NVIDIA, SenseTime, and Shanghai AI Lab. His open-source contributions to the widely used OpenMMLab mmaction2 project focused on robust test automation and data pipeline validations, improving reliability for large-scale video understanding benchmarks. At NVIDIA he prototyped an IR-based performance model, demonstrating a fluency across both algorithmic research and low-level performance engineering. Based in Nanjing, he holds B.S. and M.S. degrees in Computer Science from Nanjing University and brings a rare blend of reproducible research impact and production-focused software craftsmanship.
8 years of coding experience
2 years of employment as a software developer
Master's degree, Computer Science, Master's degree, Computer Science at Nanjing University
Github Skills (12)
unit-testing10
openmmlab10
data-loading10
test-framework10
pytest10
python10
pipeline10
testing10
video-understanding9
action-recognition8
pytorch7
deep-learning7
Programming languages (7)
Github contributions (5)
open-mmlab/mmaction2
Nov 2020 - Dec 2021
OpenMMLab's Next Generation Video Understanding Toolbox and Benchmark
Role in this project:
QA Engineer / Test Automation Engineer
QA Engineer / Test Automation EngineerContributions:209 reviews, 46 commits, 55 PRs in 1 year
Contributions summary:Bingkun primarily contributed to the testing framework of the mmaction2 repository. Their commits added and modified unit tests, focusing on the testing of data loading functionalities, pipeline augmentations (e.g., lazy operations, flip, multi-scale crop), and various dataset implementations. The contributions involved comprehensive testing of core data processing components and ensured the reliability of the video understanding toolbox.
openmmlabvideo-understandingaction-recognitiontemporal-action-localizationpytorch
congee524/Video-Swin-Transformer
Dec 2021 - Mar 2022
Contributions:7 commits, 5 pushes, 2 branches in 3 months
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