Yuan Yao
City of Ithaca, New York, United States
Summary
🤩
Rockstar🎓
Top SchoolYuan Yao is a Senior Deep Learning Architect at NVIDIA with a PhD in Computer Science from Zhejiang University and four years of industry experience building high-performance ML systems. His background blends computer architecture, architectural simulation, and deep learning compilers, informed by a postdoctoral stint at Harvard and research work at NUS. At NVIDIA he focuses on bridging research and production, optimizing model execution and hardware-aware compiler stacks. An active open-source contributor, he has implemented advanced ONNX operators (e.g., GroupNormalization, DeformConv) to broaden interoperability for cutting-edge models, and has a track record of improving precision and test quality in widely used ML tooling. Based in California, he brings a research-first mindset to practical, performance-driven engineering.
4 years of coding experience
Bachelor of Science - BS, Honours Physics, Bachelor of Science - BS, Honours Physics at The University of British ColumbiaDoctor of Philosophy - PhD, Physics, Doctor of Philosophy - PhD, Physics at Cornell University
Github Skills (12)
machine-learning10
deep-learning10
onnx10
python10
cprogramming-language9
c-language9
pytorch8
neural-network8
deep-neural-networks8
tensorflow8
f7
numpy7
Programming languages (5)
Github contributions (5)
onnx/onnx
Aug 2022 - Nov 2022
Open standard for machine learning interoperability
Role in this project:
ML Engineer
ML EngineerContributions:2 releases, 107 reviews, 2 commits in 3 months
Contributions summary:Yuan Yao made several substantial contributions to the ONNX project, primarily focused on enhancing and expanding the library's capabilities in the area of machine learning. Their work involved implementing new ONNX operators, such as GroupNormalization and DeformConv, which are critical for supporting advanced deep learning models. Further, they updated existing operators by adding new features and features for better precision, reflecting an active involvement in expanding the ONNX ecosystem to cater to more advanced and performant AI models. The user also actively worked on fixing various linting and testing errors.
pytorchmxnetdeep-learninginteroperabilitymachine-learning
yuanyao-nv/onnx
Jul 2022 - Apr 2025
Open standard for machine learning interoperability
Contributions:82 pushes, 24 branches in 2 years 9 months
caffe2mxnetdeep-learninginteroperabilitymachine-learning
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