Hangzhou, China

Sizhong Li



 

Average Co-Inventor Count = 5.8

ph-index = 1

Forward Citations = 3(Granted Patents)


Company Filing History:


Years Active: 2020-2023

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2 patents (USPTO):Explore Patents

Title: **Sizhong Li: Innovator in Machine Learning Technologies**

Introduction

Sizhong Li, an accomplished inventor based in Hangzhou, China, has made significant contributions to the field of machine learning. With two patents to his name, his work focuses on optimizing the deployment and computation processes involved in machine learning models.

Latest Patents

Li's latest patents showcase his innovative approach to enhancing machine learning applications. The first patent, titled "Separate deployment of machine learning model and associated embedding," describes a method that allows a model running environment to efficiently handle input data. It involves sending a query to an embedding running environment for low-dimensional conversion, ultimately leading to an improved prediction process. His second patent, "Fast computation of a convolutional neural network," outlines a computer-implemented method that leverages pre-computed factors to optimize the performance of convolutional layers in neural networks, thereby accelerating the overall computation.

Career Highlights

Throughout his career, Sizhong Li has worked for notable companies such as Alibaba Group Holding Limited and Advanced New Technologies Co., Ltd. These experiences have contributed to his expertise in the field and provided him with the platform to develop his groundbreaking patents.

Collaborations

Li has collaborated with talented individuals in his field, including Yongchao Liu and Qiyin Huang. These collaborations have fostered an environment for innovation and enabled the advancement of their collective projects.

Conclusion

Sizhong Li continues to be a significant force in the machine learning arena with his inventive capabilities and strategic approach to problem-solving. His patents not only reflect his talent as an inventor but also emphasize the evolving landscape of machine learning technologies.

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