Sunnyvale, CA, United States of America

How Jing

USPTO Granted Patents = 3 

Average Co-Inventor Count = 4.7

ph-index = 2

Forward Citations = 7(Granted Patents)


Company Filing History:


Years Active: 2019-2023

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3 patents (USPTO):

Title: Innovator Spotlight: How Jing

Introduction: How Jing, an accomplished inventor based in Sunnyvale, CA, has made significant contributions to the field of machine learning and artificial intelligence. With three patents to his name, Jing's work at Microsoft Technology Licensing, LLC, showcases a deep understanding of complex algorithms and user interactions.

Latest Patents: Jing's most recent patents include a "Multi-task learning framework for multi-context machine learning." This innovative framework aims to infer a user's value for specific attributes by employing a multi-task machine learning process with uncertainty weighting. By recognizing that users’ values can fluctuate based on context, the framework collects signals across multiple environments to provide an accurate assessment of user attributes.

Additionally, Jing developed a "Skill-based title prediction model." This model maps various titles in a social network to high-dimensional vectors and applies optimization tests to ensure that these vectors accurately represent the relationship between titles and skills. The dynamic alterations of vector coordinates enhance the model's predictive accuracy, demonstrating Jing's commitment to refining the intersection of machine learning and social networking.

Career Highlights: Throughout his career at Microsoft Technology Licensing, LLC, How Jing has established himself as a key figure in the advancement of machine learning technologies. His innovative methodologies and dedication to research have led to impactful patents that shape current practices in the industry.

Collaborations: Jing collaborates with talented colleagues such as Jaewon Yang and Uri Merhav. These partnerships leverage diverse expertise, further enriching the research environment at Microsoft and driving forward innovative solutions tailored to modern challenges.

Conclusion: How Jing's pioneering work in the realm of machine learning is a testament to his ingenuity and dedication as an inventor. His patents not only reflect technical prowess but also a keen awareness of user-centric design. As he continues to innovate, the tech community eagerly anticipates the future contributions of this remarkable inventor.

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