Beijing, China

Ruichang Cheng

USPTO Granted Patents = 1 

Average Co-Inventor Count = 8.0

ph-index = 1


Company Filing History:


Years Active: 2025

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1 patent (USPTO):

Title: Ruichang Cheng: Innovator in Machine Learning Resource Management

Introduction

Ruichang Cheng is a notable inventor based in Beijing, China. He has made significant contributions to the field of machine learning, particularly in optimizing resource allocation for processing tasks. His innovative approach has led to the development of a unique patent that enhances the efficiency of machine learning services.

Latest Patents

Ruichang Cheng holds a patent titled "System on chip parallel computing of ML services and applications for partitioning resources based on the inference times." This system is designed to obtain a performance profile corresponding to the times taken to perform inferencing by a machine learning model. It utilizes various processing resources to determine optimal groupings for efficient resource partitioning. The system calculates performance speeds for each grouping and identifies the one with the best performance speed, thereby optimizing the inferencing process.

Career Highlights

Throughout his career, Ruichang Cheng has worked with prominent companies in the technology sector. He has been associated with Baidu USA LLC and Baidu.com Times Technology (Beijing) Co. Ltd. His experience in these organizations has allowed him to refine his skills and contribute to cutting-edge projects in machine learning and artificial intelligence.

Collaborations

Ruichang Cheng has collaborated with talented individuals in his field, including Haofeng Kou and Davy Huang. These partnerships have fostered innovation and have been instrumental in advancing their shared goals in technology development.

Conclusion

Ruichang Cheng's work in machine learning resource management exemplifies the impact of innovative thinking in technology. His patent and career achievements highlight his commitment to enhancing the efficiency of machine learning applications.

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