Northumberland, United Kingdom

Alex Bowyer


Average Co-Inventor Count = 4.0

ph-index = 3

Forward Citations = 24(Granted Patents)


Location History:

  • Montreal, CA (2016)
  • Northumberland, GB (2019 - 2023)

Company Filing History:


Years Active: 2016-2025

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5 patents (USPTO):Explore Patents

Title: The Innovative Mind of Alex Bowyer

Introduction

Alex Bowyer is a notable inventor based in Northumberland, GB. He has made significant contributions to the field of technology, particularly in the area of auto-classification systems. With a total of five patents to his name, Bowyer's work exemplifies the intersection of innovation and practical application.

Latest Patents

One of Bowyer's latest patents is an auto-classification system and method with dynamic user feedback. This system allows for the importation of example documents that exemplify a content category into a classification model. The model is then tested for accuracy, and based on the results, feedback is provided to the user. This iterative process enables users to refine the classification model, enhancing its accuracy over time. If no user refinement is desired, the system can classify documents using the existing model. This technology significantly improves the transparency and defensibility of the auto-classification process.

Career Highlights

Throughout his career, Alex Bowyer has worked with prominent companies such as Open Text Corporation and Crowdstrike, Inc. His experience in these organizations has allowed him to develop and refine his innovative ideas, contributing to advancements in technology.

Collaborations

Bowyer has collaborated with talented individuals in the field, including Charles-Olivier Simard and Daniel Leclerc. These partnerships have fostered a creative environment that encourages the exchange of ideas and the development of groundbreaking technologies.

Conclusion

Alex Bowyer's contributions to the field of auto-classification systems highlight his innovative spirit and dedication to improving technology. His patents and collaborations reflect a commitment to enhancing the efficiency and accuracy of classification processes.

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