Shenzhen, China

Daosheng Wang

This inventor holds 1 USPTO granted patent. Top assignees: Shenzhen Langcheng Technology Co., Ltd, Shenzhen University, Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou). Active years: 2025.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Daosheng Wang. Retrieved from https://idiyas.com/inventor/daosheng-wang

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: 2025

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1 patent (USPTO):Explore Patents

Title: Daosheng Wang: Innovator in Drift Velocity Prediction

Introduction

Daosheng Wang is a prominent inventor based in Shenzhen, China. He has made significant contributions to the field of environmental science and technology, particularly in predicting drift velocity of floating objects. His innovative approach combines deep learning techniques with environmental data to enhance prediction accuracy.

Latest Patents

Wang holds a patent for a "Method, device, computing equipment, and storage medium for predicting drift velocity." This invention provides a comprehensive method for predicting the drift of floating objects by obtaining environmental characteristic parameters, including wave characteristics. The method utilizes a deep learning model trained on sample drift data to accurately forecast wave-induced drift velocity.

Career Highlights

Throughout his career, Daosheng Wang has worked with notable institutions such as Shenzhen University and the Southern Marine Science and Engineering Guangdong Laboratory in Guangzhou. His work has focused on integrating advanced computational methods with practical applications in marine science.

Collaborations

Wang has collaborated with esteemed colleagues, including Lin Mu and Yan Li, to further his research and development efforts in the field of drift prediction.

Conclusion

Daosheng Wang's innovative contributions to predicting drift velocity demonstrate the potential of combining technology with environmental science. His work continues to influence advancements in this critical area of research.

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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