Mountain View, CA, United States of America

Jing Huang

USPTO Granted Patents = 5 

Average Co-Inventor Count = 3.9

ph-index = 1

Forward Citations = 1(Granted Patents)


Company Filing History:


Years Active: 2023-2025

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5 patents (USPTO):

Title: Innovations and Achievements of Inventor Jing Huang

Introduction

Jing Huang, an accomplished inventor based in Mountain View, California, has made significant contributions to the field of knowledge graphs and relation extraction. With a total of three patents to her name, she has developed innovative methods that enhance the functionality and accuracy of technology used in data analysis.

Latest Patents

Huang's latest patents include groundbreaking advancements such as a "Method and system for relation learning by multi-hop attention graph neural network" and "System and method for completing knowledge graph." The first patent focuses on a computing device designed to process an incomplete knowledge graph consisting of nodes and edges. This system calculates an attention matrix and utilizes multi-head diffusion attention to update the knowledge graph for improved results. Her second patent centers on a system that employs adaptive thresholding and localized context pooling to predict relations between entities in a document through enhanced language modeling.

Career Highlights

Throughout her career, Jing Huang has been associated with notable companies, including Beijing Wodong Tianjun Information Technology Co., Ltd. and Jd.com American Technologies Corporation, where she applied her expertise to develop cutting-edge technologies. Her innovative contributions have positioned her as a respected figure in the tech industry.

Collaborations

Huang has had the opportunity to work alongside talented individuals such as Kevin Huang and Guangtao Wang. These collaborations have strengthened her projects and fostered a creative environment conducive to innovation.

Conclusion

Jing Huang continues to lead the way in her field with her remarkable patents and contributions to technology. Her work not only advances understanding of knowledge graphs and relation extraction but also sets a benchmark for future inventions in related domains.

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