Shenzhen, China

Chengda Wu

This inventor holds 1 USPTO granted patent and 1 published patent application. Top assignee: Huawei Technologies Co., Limited. Active years: 2025.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Chengda Wu. Retrieved from https://idiyas.com/inventor/chengda-wu

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

USPTO Granted Patents = 1 

% Patents Active = 100.0

Average Co-Inventor Count = 2.0

ph-index = 1


Company Filing History:


Years Active: 2025

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1 patent (USPTO):Explore Patents

Title: Chengda Wu: Innovator in Database Data Compression

Introduction

Chengda Wu is a notable inventor based in Shenzhen, China. He has made significant contributions to the field of data compression, particularly in the context of relational databases. His innovative approach has led to the development of a unique method that enhances data storage efficiency.

Latest Patents

Chengda Wu holds a patent for a "Database data compression method and storage device." This application discloses a method applicable to lossless compression of a relational database. The method involves parsing a first data block to obtain multiple pieces of first data, which are classified using machine learning or deep learning algorithms. The transformed data is then compressed to achieve efficient storage.

Career Highlights

Chengda Wu is currently employed at Huawei Technologies Co., Limited, a leading global provider of information and communications technology (ICT) infrastructure and smart devices. His work at Huawei has allowed him to focus on innovative solutions that address modern data challenges.

Collaborations

Chengda Wu collaborates with Yongbing Huang, contributing to advancements in data compression technologies. Their combined expertise enhances the development of efficient data management solutions.

Conclusion

Chengda Wu's contributions to database data compression exemplify the importance of innovation in technology. His work not only improves data storage efficiency but also showcases the potential of machine learning in practical applications.

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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