San Diego, CA, United States of America

Hao Su

This inventor holds 1 USPTO granted patent and 2 published patent applications. Top assignees: Adobe, Inc., The Regents of the University of Calfornia. Active years: 2026.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Hao Su. Retrieved from https://idiyas.com/inventor/hao-su-6j46uk5o

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

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: Hao Su - Innovator in Radiance Field Reconstruction

Introduction

Hao Su is a prominent inventor based in San Diego, CA. He has made significant contributions to the field of computer vision and machine learning. His innovative work focuses on fast large-scale radiance field reconstruction, which has applications in various industries.

Latest Patents

Hao Su holds a patent for "Fast large-scale radiance field reconstruction." This patent describes a method that includes receiving a sequence of input images depicting views of a scene. It involves extracting image features using an image encoder and generating a local volume based on these features through machine learning models. Additionally, a global volume is created from the local volume, allowing for the synthesis of novel views of the scene.

Career Highlights

Throughout his career, Hao Su has worked with notable companies such as Adobe, Inc. and The Regents of the University of California. His experience in these organizations has contributed to his expertise in the field of radiance field reconstruction and machine learning.

Collaborations

Hao Su has collaborated with various professionals in his field, including his coworker Xiaoshuai Zhang. Their joint efforts have further advanced the research and development of innovative technologies.

Conclusion

Hao Su's contributions to the field of radiance field reconstruction exemplify his dedication to innovation and technology. His work continues to influence advancements in computer vision and machine learning.

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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