Santa Clara, CA, United States of America

Weiheng Chai

This inventor holds 1 USPTO granted patent and 1 published patent application. Top assignee: Nvidia Corporation. Active years: 2026.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Weiheng Chai. Retrieved from https://idiyas.com/inventor/weiheng-chai

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

Calculating rank
USPTO Granted Patents = 1 

Average Co-Inventor Count = 1.0

ph-index = 1


Company Filing History:


Years Active: 2026

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1 patent (USPTO):Explore Patents

Title: Weiheng Chai and Data Mining Using Group Classifiers.

Introduction

Weiheng Chai is an inventor based in Santa Clara, California, and is associated with Nvidia Corporation. His patent work addresses data mining methods for autonomous and semi-autonomous systems.

Latest Patents

Chai is named on 1 patent: “Data Mining Using Group Classifiers.” The invention describes systems and methods that train classifiers through repeated iterations to identify data samples associated with a group, such as positive images, and distinguish them from samples that are not associated with that group. As training progresses, the classifier can improve its identification accuracy. A separate classifier can then classify objects represented in the identified samples, and the samples and classifications can be stored in databases.

Career Highlights

The patent reflects work on machine-learning approaches to organizing and classifying data for autonomous and semi-autonomous applications. Chai’s listed company affiliation is Nvidia Corporation.

Collaborations

Chai’s listed coworkers include Anurag Singh and Yifang Xu. The patent description focuses on a system involving group classifiers, iterative training, and the storage of classified data.

Conclusion

Weiheng Chai’s patent presents a classifier-based approach to improving the identification and categorization of data samples, with potential applications in autonomous and semi-autonomous systems.

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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