This inventor holds 1 USPTO granted patent. Top assignees: Zhejiang Lab, Zhejiang University. Active years: 2026.
Company Filing History:
1 out of 182 
1 out of 1,271 
Years Active: 2026
Title: Innovations of Xiaofei Jin in Neural Network Acceleration
Introduction
Xiaofei Jin is a prominent inventor based in Zhejiang, China. He has made significant contributions to the field of neural network acceleration. His innovative work focuses on improving the efficiency of convolution computations, which are crucial for various applications in artificial intelligence.
Latest Patents
Xiaofei Jin holds a patent for a "Parallel method and device for convolution computation and data loading of neural network accelerator." This invention discloses a method that requires two input feature maps and two convolution kernel cache blocks. It sequentially stores the input feature maps and 64 convolution kernels into cache sub-blocks according to a loading length. This approach allows for the execution of convolution computation while simultaneously loading data for the next group of 64 convolution kernels. He has 1 patent to his name.
Career Highlights
Throughout his career, Xiaofei Jin has worked with notable institutions such as Zhejiang Lab and Zhejiang University. His experience in these organizations has allowed him to develop and refine his innovative ideas in the field of neural networks.
Collaborations
Xiaofei Jin has collaborated with several professionals in his field, including Guoquan Zhu and De Ma. These collaborations have contributed to the advancement of his research and inventions.
Conclusion
Xiaofei Jin's work in neural network acceleration showcases his innovative spirit and dedication to advancing technology. His contributions are paving the way for more efficient computational methods in artificial intelligence.