Zelin Zhao
Research Scientist
Atlanta, Georgia, United States
Summary
🤩
Rockstar🎓
Top SchoolZelin Zhao is a Ph.D. candidate in Machine Learning at Georgia Tech with seven years of research and engineering experience building geometry-aware, physics-informed, and world-model-based AI systems that bridge perception, reasoning, and generation. He has multiple first-author papers at ICLR, CVPR, ECCV, NeurIPS, and AAAI—one of which was a CVPR 2024 Best Paper Award Candidate—and has conducted research at Caltech Anima Lab, MIT CSAIL, and SJTU ThinkLab under renowned advisors. Zelin blends academic rigor with product-focused internships, including roles at ByteDance and currently Waymo, where he applies generative and vision models to real-world problems. Based in Menlo Park, he combines deep technical expertise in computer vision and generative modeling with a knack for translating theory into scalable prototypes for AI4Science. An interesting detail: his trajectory includes a visiting stint at MIT and sustained cross-institutional collaborations that accelerate moving ideas from lab to industry.
7 years of coding experience
1 year of employment as a software developer
Visiting Student Computer Science, Visiting Student Computer Science at Massachusetts Institute of TechnologyDoctor of Philosophy - PhD Machine Learning, Doctor of Philosophy - PhD Machine Learning at Georgia Institute of TechnologyBachelor's degree Computer Science, Bachelor's degree Computer Science at Shanghai Jiao Tong University
Github Skills (200)
benchmark10
python10
toolbox10
annotations10
datasets10
deep-learning10
instance-segmentation10
gpu10
vision-transformer10
faster-rcnn10
efficientnet10
openmmlab10
optimizer10
video-understanding10
numpy10
Programming languages (9)
Github contributions (5)
sjtuytc/betapose
Dec 2018 - May 2023
Betapose for 6D pose estimation
Contributions:2 PRs, 8 pushes, 1 branch in 4 years 5 months
computer-visionpose-estimation6d-pose-estimationestimationpose
sjtuytc/UnboundedNeRFPytorch
Jul 2022 - Jan 2023
1. Non-official implementation of Block-NeRF and Mega-NeRF in Pytorch. 2. Train your large-scale NeRF in the wild. 3. Weekly classified NeRF literature.
Contributions:2 releases, 48 commits, 34 PRs in 6 months
classifiedchinese-translationblock-nerfnerf-wpytorch-lightning
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