Boise, ID, United States of America

David Glen Larson


 

Average Co-Inventor Count = 5.0

ph-index = 1


Company Filing History:


Years Active: 2021

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1 patent (USPTO):

Title: **David Glen Larson: Innovator in Traceability Identification**

Introduction

David Glen Larson, an accomplished inventor based in Boise, ID, has made notable contributions to the realm of data analysis through his innovative patent. With a keen understanding of technological advancements, Larson has developed a solution aimed at enhancing the traceability of data elements, showcasing his expertise in the field.

Latest Patents

David Larson holds a patent for a method related to traceability identifiers. The patent outlines a method that includes assigning a traceability identifier to a data element. This identifier consists of multiple segments, facilitating the process of data verification for inclusion in analytics reports. This innovation not only permits greater transparency in data handling but also enhances the reliability of analytics outputs.

Career Highlights

Currently, Larson is associated with Hewlett-Packard Development Company, L.P., where he applies his inventive mind to complex problems. His contribution to the company reflects his commitment to pushing technological boundaries and improving data traceability methods in various applications.

Collaborations

Throughout his career, Larson has collaborated with talented professionals, such as Mike Alan Holmberg and Nataraj Kumar Gobbak. These collaborations highlight the collective effort and synergy involved in advancing innovative solutions in the tech industry.

Conclusion

David Glen Larson exemplifies the spirit of innovation through his singular patent and ongoing work at Hewlett-Packard. His contributions not only bolster the functionality of data analysis but also pave the way for future developments in the field of traceability identification. As technology continues to advance, Larson's work serves as a reminder of the continuous need for innovation in solving complex data challenges.

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