Anthony Zhang
Applied Scientist at Amazon
Berkeley, California, United States
Summary
🤩
Rockstar🎓
Top SchoolAnthony Zhang is an applied scientist based in Berkeley with five years of experience at the intersection of computer graphics, 3D reconstruction, human motion, and machine learning. Currently advising and developing under Prof. Angjoo Kanazawa while contributing to high-profile open-source work like Nerfstudio, he focuses on making NeRF tooling and data pipelines more robust and user-friendly. Anthony has research and engineering credits spanning Berkeley AI Research publications (CVPR/ICCV/CoRL 2025 highlights) and production work at Amazon FAR Lab and Anatomage, blending systems engineering with cutting-edge 4D and humanoid research. Comfortable shipping end-to-end systems—from Colab demos and caching optimizations to medical imaging and robot sim pipelines—he pairs rigorous EECS training at UC Berkeley with a knack for turning research prototypes into practical, reproducible tools.
5 years of coding experience
1 year of employment as a software developer
Master of Science - MS Electrical Engineering & Computer Science, Master of Science - MS Electrical Engineering & Computer Science at UC Berkeley Electrical Engineering & Computer Sciences (EECS)Bachelor of Arts - BA Computer Science Applied Mathematics, Bachelor of Arts - BA Computer Science Applied Mathematics at University of California, BerkeleyHigh School Diploma, High School Diploma at Wylie High School
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (12)
computer-vision10
machine-learning10
f10
n10
3d-reconstruction10
3d10
pytorch9
python9
deeplearning-ai9
deep-learning9
data-engineering8
3d-graphics7
Programming languages (3)
Github contributions (5)
nerfstudio-project/nerfstudio
Jan 2024 - Apr 2025
A collaboration friendly studio for NeRFs
Role in this project:
ML Engineer
ML EngineerContributions:19 reviews, 19 PRs, 3 pushes in 1 year 2 months
Contributions summary:Anthony primarily contributed to the NeRFstudio project by addressing issues related to the Colab demo environment, specifically fixing installation and configuration issues. They also implemented improvements to the data loading pipeline, including caching mechanisms and optimization strategies. Furthermore, the user fixed assertion issues related to exporting NeRFs. These contributions demonstrate a focus on optimizing the user experience and streamlining the training and export processes within the NeRF framework.
pytorchphotogrammetrydeep-learningcomputer-vision3d-reconstruction
AntonioMacaronio/nerfstudio
Jan 2024 - Apr 2025
A collaboration friendly studio for NeRFs
Contributions:247 pushes, 19 branches in 1 year 2 months
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