Hamid Reza Zohouri

Title: Hamid Reza Zohouri: Innovator in Neural Network Technology

Introduction

Hamid Reza Zohouri is a prominent inventor based in Sunnyvale, CA (US). He has made significant contributions to the field of neural network technology, holding a total of 3 patents. His work focuses on enhancing the efficiency and capabilities of neural network accelerators.

Latest Patents

Zohouri's latest patents include innovative designs for neural network accelerators. One of his notable inventions is a "Neural network accelerator writable memory." This technology allows for neural network inference through a device that includes an accumulation memory, convolution modules, and adder modules. The accumulation memory is designed with a reconfigurable bank width, optimizing the performance of the writable memory block.

Another significant patent is the "Neural network accelerator hardware-specific division of inference into groups of layers." This invention involves dividing the inference process into groups based on a computational graph and hardware chip configuration. By estimating the duration and energy consumption, the system generates instructions for the hardware chip to perform inference sequentially by group, enhancing the overall efficiency of neural network operations.

Career Highlights

Hamid Reza Zohouri is currently employed at Edgecortix Pte. Ltd., where he continues to develop cutting-edge technologies in the field of artificial intelligence and neural networks. His work has positioned him as a key player in advancing neural network applications.

Collaborations

Zohouri collaborates with talented professionals in his field, including Nikolay Nez and Oleg Khavin. Their combined expertise contributes to the innovative projects at Edgecortix Pte. Ltd.

Conclusion

Hamid Reza Zohouri's contributions to neural network technology through his patents and work at Edgecortix Pte. Ltd. highlight his role as a leading inventor in the industry. His innovative approaches are paving the way for advancements in artificial intelligence applications.