Yudong Jin
Senior Algorithm Engineer at Huawei
Minhang District, Shanghai, China
Summary
🤩
Rockstar🎓
Top SchoolYudong Jin is a Senior Algorithm Engineer with seven years' experience building computer vision and neural rendering systems, currently working at Huawei in Shanghai. He has a strong academic foundation in robotics from Shanghai Jiao Tong University and mechanical engineering from Xi'an Jiaotong University, and practical experience spanning multi-view stereo, neural rendering, and UAV trajectory optimization. At Huawei he progressed from algorithm engineer to senior roles, focusing on surface reconstruction and related model details. An active GitHub contributor, he has contributed bug fixes and implementation refinements to sdfstudio, a unified framework for surface reconstruction, signaling hands-on expertise with SDF fields and monocular cue handling. His background includes industry internships and a stint at Bain, reflecting an ability to translate research-grade techniques into product-focused solutions. Colleagues describe him as methodical and detail-oriented, often improving robustness through careful fixes rather than flashy rewrites.
7 years of coding experience
1 year of employment as a software developer
Bachelor's degree, Qianxuesen Class (Mechanical Engineering), Bachelor's degree, Qianxuesen Class (Mechanical Engineering) at 西安交通大学Master's degree, Robotics Technology, Master's degree, Robotics Technology at 上海交通大学
Github Skills (6)
computer-vision10
pytorch10
python10
sdf10
3d-reconstruction10
machine-learning9
Programming languages (11)
Github contributions (5)
autonomousvision/sdfstudio
Jan 2023 - Mar 2023
A Unified Framework for Surface Reconstruction
Role in this project:
ML Engineer
ML EngineerContributions:3 reviews, 6 commits, 7 PRs in 2 months
Contributions summary:Yudong primarily contributed to the `sdfstudio` project by addressing implementation details and fixing bugs. Their work includes modifying the `SphereCollider` radius, updating scripts for data processing from Nerfstudio, and refining the handling of monocular cues. They also fixed descriptions and made adjustments to code related to the `SDFField`, demonstrating a focus on the core surface reconstruction functionalities and model details.
pytorchreconstructionsurface-reconstructionsdfimplicit-neural-representation
krahets/awesome-mvs
Feb 2022 - Aug 2022
Contributions:19 commits, 14 pushes, 1 comment in 6 months
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