Ruilong Li
Berkeley, California, United States
Summary
🤩
Rockstar🎓
Top SchoolRuilong Li is a PhD candidate focused on computer vision and graphics based in Berkeley with nine years of experience building research-driven ML systems. He holds MS and BS degrees from Tsinghua University and is pursuing doctoral work in CV & CG, blending rigorous theory with production-minded engineering. Early industry experience includes algorithm internships at ByteDance and DeepGlint, where he shipped a real-time mobile CNN for hair matting and contributed to vision research. An active open-source contributor to the widely used nerfstudio project, he optimized the PDFSampler using torch.searchsorted and added CUDA-backed Instant-NGP and density-grid improvements to boost rendering speed and PSNR. Ruilong is known for turning ray-sampling theory into high-performance PyTorch/CUDA implementations that bridge research prototypes and practical rendering systems.
9 years of coding experience
University of California, BerkeleyDoctor of Philosophy - PhD, CV & CG, Doctor of Philosophy - PhD, CV & CG at University of Southern CaliforniaMaster of Science - MS, Computer Science and Technology, Master of Science - MS, Computer Science and Technology at Tsinghua University
English, Chinese
Github Skills (10)
cuda10
raytracing10
computer-vision10
pytorch10
serf10
3d-reconstruction9
3d9
machine-learning9
deep-learning9
3d-graphics8
Programming languages (4)
Github contributions (5)
nerfstudio-project/nerfstudio
Jul 2022 - Dec 2022
A collaboration friendly studio for NeRFs
Role in this project:
ML Engineer
ML EngineerContributions:6 reviews, 20 commits, 26 PRs in 5 months
Contributions summary:Ruilong primarily focused on optimizing the `PDFSampler` implementation within the `nerfstudio` project, specifically targeting performance improvements. Their commits reveal a deep understanding of ray sampling techniques, including the use of `torch.searchsorted` for faster bin calculations. They also addressed issues related to axis arguments in PyTorch functions and updated Instant-NGP and Density Grid with CUDA support to enhance rendering speed and PSNR. Further contributions involved bug fixes and improvements to various samplers within the project.
pytorchphotogrammetrydeep-learningcomputer-vision3d-reconstruction
nerfstudio-project/gsplat
Oct 2023 - Mar 2025
CUDA accelerated rasterization of gaussian splatting
Contributions:16 releases, 154 reviews, 204 PRs in 1 year 5 months
gaussian-splatting
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