Yujun Lin is an AI research scientist at NVIDIA with nine years of experience bridging efficient deep learning algorithms and hardware-aware system design. Trained at Tsinghua and MIT, he has worked on FPGA and ReRAM-based accelerators, distributed training systems, and computer architecture research that targets practical speed and energy gains. His trajectory combines hands-on accelerator prototyping from his early Tsinghua work with scalable system and ML research at MIT, culminating in industry research focused on making deep models both faster and more efficient. Based in Cambridge, MA, he is comfortable moving between low-level hardware design and high-level algorithmic innovation—a blend that often yields cross-layer optimizations not obvious from a single-discipline perspective.
9 years of coding experience
9 years of employment as a software developer
Doctor of Philosophy - PhD Electrical Engineering and Computer Science, Doctor of Philosophy - PhD Electrical Engineering and Computer Science at Massachusetts Institute of Technology
Bachelor of Engineering - BE Electronics Engineering, Bachelor of Engineering - BE Electronics Engineering at Tsinghua University
Contributions:2 PRs, 10 pushes in 3 years 5 months
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