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Mountain View, CA, United States of America

Jd.com American Technologies Corporation

USPTO Granted Patents = 58

EPO Patents = 2

Forward Citations = 139

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91 inventors (with patents filed for the assignee):

Hui Zhou (17 out of 22 patents)

Hui Ting Cheng (8 out of 54 patents)

Shanglin Yang (6 out of 6 patents)

4. Yi Xu (6 out of 26 patents)

5. Li Chen (6 out of 6 patents)

6. Shizhu Liu (5 out of 5 patents)

7. Guanghan Ning (4 out of 6 patents)

8. Chi Zhang (4 out of 10 patents)

9. Huasong Shan (4 out of 4 patents)

10. Jimmy Su (4 out of 4 patents)

11. Wei Xi (3 out of 3 patents)

12. Min Li (3 out of 3 patents)

13. Xiaochuan Fan (3 out of 5 patents)

14. Yueh-Hsun Lin (3 out of 4 patents)

15. Soonhac Hong (3 out of 3 patents)

Core Competencies:

Graph Neural Network

3D Try-On

Product Recommendation

Knowledge Graph

Autonomous Vehicles

Time Series Forecasting

Object Detection

Semantic Segmentation

Virtual Fitting

Augmented Reality

Malware Analysis

E-Commerce

58 patents: Sort by Forward Citations

1. 12299566 - Method and system for relation learning by multi-hop attention graph neural network (2025-05-13),

2. 11941770 - System and method for 3D try-on based on human pose and body shape estimation (2024-03-26),

3. 11935106 - System and method for product recommendation based on multimodal fashion knowledge graph (2024-03-19),

4. 11861311 - System and method for knowledge graph construction using capsule neural network (2024-01-02),

5. 11748999 - System and method for recognizing intersection by autonomous vehicles (2023-09-05),

6. 11710168 - System and method for scalable tag learning in e-commerce via lifelong learning (2023-07-25),

7. 11704487 - System and method for fashion attributes extraction (2023-07-18),

8. 11593560 - System and method for relation extraction with adaptive thresholding and localized context pooling (2023-02-28),

9. 11587122 - System and method for interactive perception and content presentation (2023-02-21),

10. 11586880 - System and method for multi-horizon time series forecasting with dynamic temporal context learning (2023-02-21),

11. 11574351 - System and method for quality assessment of product description (2023-02-07),

12. 11568138 - System for entity and evidence-guided relation prediction and method of using the same (2023-01-31),

13. 11551277 - System and method for automatic generation of knowledge-powered content planning (2023-01-10),

14. 11531748 - Method and system for autonomous malware analysis (2022-12-20),

15. 11514498 - System and method for intelligent guided shopping (2022-11-29),

Company Overview

Jd.com American Technologies Corporation, headquartered in Mountain View, CA, specializes in advanced artificial intelligence solutions. The company focuses on developing innovative technologies such as Graph Neural Networks and Knowledge Graphs, enhancing product recommendation systems and 3D try-on experiences. Their expertise extends to autonomous vehicles, time series forecasting, object detection, and semantic segmentation, positioning them at the forefront of AI-driven applications across various industries.

Profile summary synthesized from public USPTO records and patent filings.

Company Badge

USPTO Data Jan 1 1976 - Oct 13 2026

58 Patents

#58 in Mountain View, CA

#1,445 in California

#6,157 in US

#12,395 in the World

Mountain View, CA, United States of America

Jd.com American Technologies Corporation

Forward Citations = 139

91 inventors:

Hui Zhou (17 out of 22 patents)

Hui Ting Cheng (8 out of 54 patents)

Shanglin Yang (6 out of 6 patents)

4. Yi Xu (6 out of 26 patents)

5. Li Chen (6 out of 6 patents)

IDiyas Innovation Intelligence. (2026). Company Patent Portfolio: Jd.com American Technologies Corporation. Retrieved from https://idiyas.com/company/jd-com-american-technologies

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

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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