Austin, TX, United States of America

James Robert Eskew

This inventor holds 2 USPTO granted patents. Top assignee: Avathon, Inc.. Active years: 2026.

IDiyas Innovation Intelligence. (2026). Inventor Profile: James Robert Eskew. Retrieved from https://idiyas.com/inventor/james-robert-eskew

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

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Average Co-Inventor Count = 3.0

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Company Filing History:


Years Active: 2026

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2 patents (USPTO):Explore Patents

Title: James Robert Eskew: Inventor in Behavior Modeling and Anomaly Detection.

Introduction

James Robert Eskew is an inventor based in Austin, Texas, whose patent work focuses on behavior modeling, state prediction, and monitoring for anomalies. He is associated with Avathon, Inc. His listed portfolio includes 2 patents.

Latest Patents

Eskew’s listed inventions address the reliability of state predictions and the detection of unusual behavior.

“State prediction reliability modeling” describes a method that uses behavior-model output to generate an initial state prediction. When that prediction indicates a particular state, the method calculates statistics using the prediction and historical predictions for the same state. A classifier then uses those statistics to assess whether the initial prediction is reliable.

“Anomaly detection based on normal behavior modeling” describes monitoring an asset with trained behavior models. The method uses model output to determine a risk score and feature-importance data, then considers both when deciding whether to generate an alert.

Career Highlights

Eskew’s listed patent work connects predictive modeling with operational monitoring. The inventions describe ways to evaluate confidence in predicted states and use risk and feature importance to inform alert decisions.

Collaborations

Eskew is associated with Avathon, Inc. His listed coworkers include Kevin Gullikson and Uche Ohafia.

Conclusion

James Robert Eskew’s listed inventions focus on making behavior-based predictions more reliable and supporting anomaly alerts with model-derived risk and feature information.

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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