Kirkland, WA, United States of America

Jiang Du

This inventor holds 1 USPTO granted patent. Top assignee: Amazon Technologies, Inc.. Active years: 2025.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Jiang Du. Retrieved from https://idiyas.com/inventor/jiang-du-8jweyqv5

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 = 7.0

ph-index = 1


Company Filing History:


Years Active: 2025

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1 patent (USPTO):Explore Patents

Title: Jiang Du: Innovator in Intelligent Defaulting Systems

Introduction

Jiang Du is a notable inventor based in Kirkland, WA (US). He has made significant contributions to the field of machine learning, particularly in the area of intelligent defaulting systems. His innovative approach has the potential to enhance user experience in product checkout processes.

Latest Patents

Jiang Du holds 1 patent for his invention titled "Systems and methods for intelligent defaulting using machine learning." This patent describes systems and methods that utilize machine learning models to determine a default shipment option presented to users during the checkout process. The invention involves a two-phase determination process that leverages user-specific historical data and adjusts thresholds based on various non-user-specific factors.

Career Highlights

Jiang Du is currently employed at Amazon Technologies, Inc., where he applies his expertise in machine learning to develop innovative solutions. His work focuses on improving the efficiency and effectiveness of product delivery systems, making online shopping more user-friendly.

Collaborations

Jiang has collaborated with talented coworkers such as Taeuk Jang and Tian Chen. Their combined efforts contribute to the advancement of technology within their organization.

Conclusion

Jiang Du's work in intelligent defaulting systems showcases his innovative spirit and dedication to enhancing user experiences in e-commerce. His contributions to machine learning are paving the way for more efficient online shopping solutions.

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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