Providence, RI, United States of America

Qi Zhao

This inventor holds 1 USPTO granted patent. Top assignees: Brown University, Honda Motor Ltd., Ltd.. Active years: 2026.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Qi Zhao. Retrieved from https://idiyas.com/inventor/qi-zhao-tg0cqgi6

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

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Average Co-Inventor Count = 1.0


Company Filing History:


Years Active: 2026

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1 patent (USPTO):Explore Patents

Title: Qi Zhao and Video-Based Action Anticipation.

Introduction

Qi Zhao is an inventor associated with Providence, Rhode Island. His patent work explores how neural language models can help anticipate actions in videos, connecting computer vision with language-based prediction.

Latest Patents

Zhao is associated with 1 patent: “Using Neural Language Models for Long-Term Action Anticipation from Videos.” The invention describes an electronic device that analyzes a video of objects performing a physical task and generates tags representing an observed sequence of actions. It then uses those tags to prompt a neural language model, which predicts tags for a subsequent sequence of actions. The device can use the predicted tags to display information about the anticipated actions.

Career Highlights

The provided information associates Zhao with Honda Motor and Brown University. These affiliations connect his profile with both an industrial organization and a university research environment.

Collaborations

Zhao’s listed coworkers include Ce Zhang and Changcheng Fu. Their names provide context for the professional and research connections associated with his work.

Conclusion

Qi Zhao’s patent focuses on using neural language models to predict what may happen next in a video, illustrating an approach to long-term action anticipation.

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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