Gilbert, AZ, United States of America

Gerard Warrens

This inventor holds 1 USPTO granted patent and 3 published patent applications. Top assignee: Oracle International Corporation. Active years: 2026.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Gerard Warrens. Retrieved from https://idiyas.com/inventor/gerard-warrens

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

Calculating rank
USPTO Granted Patents = 1 

Average Co-Inventor Count = 1.0

ph-index = 1


Company Filing History:


Years Active: 2026

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1 patent (USPTO):Explore Patents

Title: Gerard Warrens and Autonomous Situation Awareness

Introduction

Gerard Warrens is an inventor based in Gilbert, Arizona. His patent work includes a system for autonomous situation awareness that uses ambient intelligence, machine-learning estimates, and anomaly detection to support adjustments to asset controls.

Latest Patents

Warrens is associated with 1 patent: “Autonomous Situation Awareness with Ambient and Reflexive Context and Anomaly-Driven Predicates.” The invention describes accessing multivariate observations of system status and command variables, supplementing them with machine-learning estimates of ambient variables, and identifying anomalies through residuals between observed values and estimates. Predicates are then used to select a command variable for adjustment. The system predicts future system values, generates a suggested adjustment, and issues an electronic alert to help align asset controls with that suggestion.

Career Highlights

Warrens is associated with Oracle International Corporation. His patent reflects work on applying machine learning and anomaly-driven analysis to autonomous monitoring and control.

Collaborations

Warrens’s listed coworker is Esraa Maher Mounir Samy Moustafa. The available information does not specify their roles or the nature of their collaboration.

Conclusion

Gerard Warrens’s patent focuses on combining ambient context, machine-learning predictions, and anomaly detection to guide control adjustments, highlighting an approach to autonomous situation awareness.

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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