Evonne Ng is a research scientist and software engineer with 10 years of experience, currently at Meta in Austin, Texas, and with a PhD in AI/Computer Vision from UC Berkeley. She bridges embedded systems, AI, and virtual reality, bringing practical engineering to research problems—most recently contributing core graph-instantiation logic and modular NeRF components to the popular nerfstudio project. Her background includes multiple Meta research roles and an EECS bachelor's from UT Austin, reflecting a blend of hardware-aware systems thinking and advanced machine learning. Known for animation-focused work on GitHub, she pairs curiosity-driven prototyping with rigorous testing and modular design to make cutting-edge vision tech reproducible and production-ready.
10 years of coding experience
2 years of employment as a software developer
Doctor of Philosophy - PhD AI / Computer Vision, Doctor of Philosophy - PhD AI / Computer Vision at University of California, Berkeley
Bachelor’s Degree Electrical Engineering and Computer Science, Bachelor’s Degree Electrical Engineering and Computer Science at The University of Texas at Austin
Contributions:4 reviews, 246 commits, 5 PRs in 6 months
Contributions summary:Evonne implemented core logic for creating and instantiating graph structures, a fundamental component of the NeRF model. They also added tests to validate the instantiation process and input dimension calculations. The user contributed to the modularization of the NeRF model by defining and implementing base classes for modules and render heads, demonstrating an understanding of the model architecture and the integration of different components.
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