Vickie Ye
Member Of Technical Staff at Anthropic
Berkeley, California, United States
Summary
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Rockstar🎓
Top SchoolVickie Ye is a Member of Technical Staff at Anthropic and a PhD-trained computer vision and machine learning engineer with about 10 years of experience, based in Berkeley. She completed a PhD at UC Berkeley's BAIR lab after undergraduate studies in CS and Physics at MIT, blending rigorous research training with systems engineering. Her work spans from core research to production: notable contributions to the PixelNeRF official repository—adding multi-object rendering, training, and data pipelines—pair with applied autonomy work on 3D long-range terrain mapping at Skydio. A string of quantitative internships at D.E. Shaw, Hudson River Trading, and Jump Trading underscore an unusually strong quantitative and systems foundation for an ML researcher. She’s known for turning cutting-edge 3D ML research into practical, production-ready pipelines across both academia and industry.
11 years of coding experience
3 years of employment as a software developer
Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at University of California, BerkeleyBachelor of Science (B.S.), Computer Science and Physics, Bachelor of Science (B.S.), Computer Science and Physics at Massachusetts Institute of Technology
Github Skills (9)
computer-vision10
pytorch10
machine-learning10
python10
modeling9
trainings9
deep-learning9
3d-rendering9
blender7
Programming languages (2)
Github contributions (5)
sxyu/pixel-nerf
Dec 2020 - Jan 2021
PixelNeRF Official Repository
Role in this project:
ML Engineer
ML EngineerContributions:18 commits, 1 push in 1 month
Contributions summary:Vickie's contributions primarily involve developing and integrating code related to training and rendering 3D models using neural radiance fields (NeRF). They added code for training on ShapeNet datasets and modified existing model components. Furthermore, the user made changes to the rendering script and data loading pipelines to support multi-object scenes. These changes indicate a focus on the practical implementation and enhancement of the pixelNeRF framework.
deep-learningpytorchcomputer-vision
vye16/slahmr
Feb 2023 - Mar 2023
Contributions:33 commits, 3 PRs, 37 pushes in 19 days
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