Huntsville, AL, United States of America

Grant A Rosario

This inventor holds 1 USPTO granted patent. Top assignee: The Boeing Company. Active years: 2026.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Grant A Rosario. Retrieved from https://idiyas.com/inventor/grant-a-rosario

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


% Patents Active = 100.0

Average Co-Inventor Count = 4.0

ph-index = 1


Company Filing History:


Years Active: 2026

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1 patent (USPTO):Explore Patents

Title: Grant A. Rosario: Innovator in Machine Learning Training Data Generation

Introduction

Grant A. Rosario is an accomplished inventor based in Huntsville, Alabama. He has made significant contributions to the field of machine learning through his innovative patent. His work focuses on generating training data that enhances the performance of machine learning systems.

Latest Patents

Grant A. Rosario holds a patent for a "Computing device, method and computer program product for generating training data for a machine learning system." This invention provides a computing device and method that generates training data representative of various edge scenes. The device includes a simulator that creates different scenes within a defined scenario, utilizing a physics engine to modify parametric attributes and generate diverse training data.

Career Highlights

Grant A. Rosario is currently employed at The Boeing Company, where he applies his expertise in machine learning and data generation. His innovative approach has positioned him as a valuable asset in the field of technology and engineering.

Collaborations

Some of his notable coworkers include Patrick Daniel Dees and Helen Amelia Hawkins, who contribute to the collaborative environment at The Boeing Company.

Conclusion

Grant A. Rosario's work in generating training data for machine learning systems exemplifies the innovative spirit of modern technology. His contributions are paving the way for advancements in machine learning applications.

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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