Kun Gao

Researcher at Zhongguancun Academy

Beijing, China
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Summary

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Rockstar
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Top School
Kun Gao is a research scientist based in Beijing with a PhD from Peking University and five years of experience at the intersection of explainable AI, symbolic reasoning, and applied time-series analysis. His work spans inducive logic programming, injecting symbolic rules into deep models, and interpretable solutions for finance, healthcare, and industrial cloud logs—grounded in practical internships at Microsoft, IHPC, and Japan’s National Institute of Informatics. Comfortable with TensorFlow, PyTorch, cloud platforms and classical ML techniques, he bridges theory and engineering to make black-box models auditable and rule-aware. Notably, his research emphasizes differentiable rule learning from real-world knowledge graphs and temporal data, reflecting a rare blend of symbolic and deep learning expertise focused on interpretable, deployable systems.
code5 years of coding experience
job3 years of employment as a software developer
bookDoctor of Philosophy - PhD Computer Science, Doctor of Philosophy - PhD Computer Science at Peking University
bookBachelor's degree Information Security, Bachelor's degree Information Security at University of Science and Technology Beijing
languagesChinese, English
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Github Skills (22)

ranking10
science10
computer-science10
react10
python6
ai5
deep-learning5
machine-learning5
incremental-learning5
data-science5
artificial-intelligence5
pytorch5
representation-learning4
language-modeling4
3d4

Programming languages (2)

TeXPython

Github contributions (5)

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3D高斯论文,持续更新,欢迎交流讨论。
Contributions:1 review, 6 PRs, 584 pushes in 2 years 6 months
3dgs3d-gaussian-splattinggaussian-splattingnovel-view-synthesis
gqk/pic

Dec 2023 - Apr 2026

Contributions:44 pushes, 2 branches in 2 years 4 months
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