Princeton, NJ, United States of America

Zecheng He

This inventor holds 3 USPTO granted patents and 6 published patent applications. Top assignees: Google Inc., Sri International. Active years: 2022-2025.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Zecheng He. Retrieved from https://idiyas.com/inventor/zecheng-he

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

USPTO Granted Patents = 3 

% Patents Active = 100.0

Average Co-Inventor Count = 6.7

ph-index = 1


Company Filing History:


Years Active: 2022-2025

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3 patents (USPTO):Explore Patents

Title: Zecheng He: Innovator in User Interface Prediction

Introduction

Zecheng He is a prominent inventor based in Princeton, NJ (US). He has made significant contributions to the field of user interface understanding through his innovative patents. With a total of 3 patents, He has focused on the development of machine-learned models that enhance user interaction.

Latest Patents

His latest patents include "Machine-learned models for user interface prediction, generation, and interaction understanding." This patent is directed towards user interface understanding, specifically relating to the training and utilization of machine-learned models for user interface prediction and generation. The machine-learned interface prediction model can be pre-trained using various tasks for eventual downstream task training and utilization, such as interface prediction and generation.

Career Highlights

Zecheng He has worked with notable companies, including Google Inc. and SRI International. His experience in these organizations has allowed him to refine his skills and contribute to cutting-edge technologies in user interface design.

Collaborations

He has collaborated with talented individuals such as Srinivas Kumar Sunkara and Xiaoxue Zang, further enhancing his work in the field.

Conclusion

Zecheng He is a key figure in the innovation of user interface technologies, with a focus on machine learning applications. His contributions continue to shape the future of user interaction and interface design.

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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