Jinan, China

Kai Gao

This inventor holds 1 USPTO granted patent and 1 EPO patent. Top assignee: Inspur Electronic Information Industry Co., Ltd.. Active years: 2026.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Kai Gao. Retrieved from https://idiyas.com/inventor/kai-gao-3wqo98sl

Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile


% Patents Active = 100.0


Average Co-Inventor Count = 4.0

ph-index = 1


Company Filing History:


Years Active: 2026

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1 patent (USPTO):Explore Patents

Title: The Innovative Contributions of Kai Gao

Introduction

Kai Gao is a prominent inventor based in Jinan, China. He has made significant strides in the field of computing, particularly in the development of convolutional neural network models. His work is characterized by a focus on improving the efficiency and flexibility of computing tasks.

Latest Patents

Kai Gao holds a patent for a "Computing method and apparatus for convolutional neural network model." This innovative method involves acquiring a computing model of a training task for a convolutional neural network. The process includes splitting multiply-accumulate operations into multiple tasks, confirming the appropriate computing device for each task, and computing each task using the designated device. This approach enhances the flexibility of migrating CNN model training tasks across different computing devices and improves overall computing speed. He has 1 patent to his name.

Career Highlights

Kai Gao is currently employed at Inspur Electronic Information Industry Co., Ltd., where he continues to contribute to advancements in computing technology. His work has been instrumental in pushing the boundaries of what is possible in the realm of neural networks.

Collaborations

Some of his notable coworkers include Zhenhua Guo and Li Wang, who collaborate with him on various projects within the company.

Conclusion

Kai Gao's innovative contributions to computing, particularly in convolutional neural networks, highlight his role as a key figure in the industry. His patent reflects a commitment to enhancing computing efficiency and flexibility, marking him as an inventor to watch in the future.

Profile summary based on public USPTO records.
Data Sources: USPTO Patent Grant XML, Patent Center, EPO & CIPO • Normalized by IDiyas Innovation Graph. Methodology & provenance architecturePlease report any incorrect information to [email protected]
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