Hyderabad, India

Jinka Sai Sagar

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

IDiyas Innovation Intelligence. (2026). Inventor Profile: Jinka Sai Sagar. Retrieved from https://idiyas.com/inventor/jinka-sai-sagar

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

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USPTO Granted Patents = 1 

Average Co-Inventor Count = 1.0

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Company Filing History:


Years Active: 2026

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1 patent (USPTO):Explore Patents

Title: Jinka Sai Sagar and Multimodal Pose Tracking.

Introduction

Jinka Sai Sagar is an inventor based in Hyderabad, India, and is associated with Qualcomm Incorporated. His patent work focuses on techniques for predicting human body poses by combining visual and motion-tracking information.

Latest Patents

Sagar is associated with 1 patent, titled “Multi-modal full body pose tracking.” The invention describes a process that combines image features detected from an image with estimated image features, then temporally encodes the resulting information. It also combines detected motion-tracking information with estimated motion-tracking information and temporally encodes that data. The system spatially encodes the visual and motion information together and predicts a body pose by regressing the resulting multimodal representation.

Career Highlights

Sagar’s patent reflects work on multimodal pose prediction, bringing together image analysis, motion tracking, and temporal and spatial encoding. This approach is designed to use complementary data sources to support body-pose estimation.

Collaborations

His listed coworkers include Vishnu Menon and Kinal Mehta. The patent is associated with Qualcomm Incorporated.

Conclusion

Jinka Sai Sagar’s patent contribution centers on combining visual and motion-tracking data to advance multimodal full-body pose prediction.

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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