Yonggan Fu
Research Scientist at NVIDIA
California, United States
Summary
🤩
Rockstar🎓
Top SchoolYonggan Fu is a Research Scientist at NVIDIA Research with about eight years of experience at the intersection of computer science and applied physics, holding a PhD from Georgia Tech and doctoral work at Rice. He has a strong research internship pedigree including multiple stints at NVIDIA and Meta and focuses on full-stack optimization and software frameworks for cognitive systems. Based in California, he translates deep academic training into practical systems research that targets performance and deployment challenges for AI workloads. Notably, his trajectory includes SRC Research Scholars work bridging hardware-aware optimization with software frameworks, signaling a knack for end-to-end co-design rather than isolated algorithmic work.
8 years of coding experience
Doctor of Philosophy - PhD Computer Science, Doctor of Philosophy - PhD Computer Science at Georgia Institute of TechnologyDoctor of Philosophy - PhD Electrical & Computer Engineering, Doctor of Philosophy - PhD Electrical & Computer Engineering at Rice UniversityBachelor of Science - BS Applied Physics & Computer Science, Bachelor of Science - BS Applied Physics & Computer Science at University of Science and Technology of China
Github Skills (20)
cuda8
inference8
amd8
pytorch8
chatgpt7
deep-learning7
transformer7
gpt7
quantization6
mlops6
tpu6
llm6
quantum-computing5
llmops5
llama5
Programming languages (3)
Github contributions (5)
VITA-Group/AGD
Jul 2020 - Oct 2020
Contributions:8 commits, 10 pushes, 34 comments in 3 months
GATECH-EIC/CPT
Mar 2021 - Feb 2022
[ICLR 2021] "CPT: Efficient Deep Neural Network Training via Cyclic Precision" by Yonggan Fu, Han Guo, Meng Li, Xin Yang, Yining Ding, Vikas Chandra, Yingyan Lin
Contributions:4 commits, 35 pushes, 3 branches in 10 months
efficient-traininglow-precision-trainingpytorchquantization
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