Bryn Mawr, PA, United States of America

Matthew David Johnson

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

IDiyas Innovation Intelligence. (2026). Inventor Profile: Matthew David Johnson. Retrieved from https://idiyas.com/inventor/matthew-david-johnson-oo3ghj0j

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


Average Co-Inventor Count = 1.0


Company Filing History:


Years Active: 2026

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1 patent (USPTO):Explore Patents

Title: Innovations of Matthew David Johnson

Introduction

Matthew David Johnson is an accomplished inventor based in Bryn Mawr, PA. He has made significant contributions to the field of machine learning through his innovative patent. His work focuses on enhancing the capabilities of computing systems to better understand and predict data.

Latest Patents

Matthew holds a patent for a "System and method for training a machine learning model." This invention involves a computing system that collects input data related to an object or environment. The system executes a feature extractor to extract features from the input data, clusters the data elements based on similarities, and generates a training dataset. This dataset is then used to train a machine learning model to predict labels for new input data. His patent demonstrates a sophisticated approach to machine learning, showcasing his expertise in the field.

Career Highlights

Matthew is currently employed at The Boeing Company, where he applies his skills in machine learning and data analysis. His role involves developing innovative solutions that enhance the company's technological capabilities. His experience at Boeing has allowed him to work on cutting-edge projects that push the boundaries of what is possible in aerospace technology.

Conclusion

Matthew David Johnson is a notable inventor whose work in machine learning has the potential to transform how data is processed and understood. His contributions to the field are significant, and his patent reflects his commitment to innovation.

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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