McLean, VA, United States of America

Daniel Barcklow

This inventor holds 2 USPTO granted patents and 1 published patent application. Top assignee: Capital One Services, LLC. Active years: 2026.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Daniel Barcklow. Retrieved from https://idiyas.com/inventor/daniel-barcklow

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

USPTO Granted Patents = 2 

% Patents Active = 50.0

Average Co-Inventor Count = 6.0

ph-index = 1


Company Filing History:


Years Active: 2026

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2 patents (USPTO):Explore Patents

Title: The Innovations of Daniel Barcklow

Introduction

Daniel Barcklow is an accomplished inventor based in McLean, VA (US). He has made significant contributions to the field of machine learning, particularly in determining the quality of model outputs. His innovative approach has garnered attention in the tech community.

Latest Patents

Barcklow holds a patent titled "Determining quality of machine learning model output." This patent addresses the generation of uninformative features that can be added to a dataset of real features. These uninformative features do not correlate with the model's predictions, while the real features do. The patent outlines a method for training a machine learning model on a dataset that includes both types of features, allowing for better feature attributions for model output.

Career Highlights

Currently, Daniel Barcklow works at Capital One Services, LLC, where he applies his expertise in machine learning to enhance financial technologies. His work focuses on improving the accuracy and reliability of predictive models, which is crucial in the banking sector.

Collaborations

One of his notable coworkers is Samuel Sharpe, with whom he collaborates on various projects related to machine learning and data analysis.

Conclusion

Daniel Barcklow's contributions to machine learning and his innovative patent demonstrate his commitment to advancing technology in meaningful ways. His work continues to influence the field and improve the quality of 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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