Leander, TX, United States of America

Nagarajan Thiruvellore

This inventor holds 1 USPTO granted patent. Top assignee: Dell Products Inc.. Active years: 2026.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Nagarajan Thiruvellore. Retrieved from https://idiyas.com/inventor/nagarajan-thiruvellore

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

Calculating rank

Average Co-Inventor Count = 1.0


Company Filing History:


Years Active: 2026

Loading Chart...
1 patent (USPTO):Explore Patents

Title: Nagarajan Thiruvellore: Inventor in Machine Learning-Based Issue Remediation.

Introduction

Nagarajan Thiruvellore is an inventor based in Leander, Texas, and works at Dell Products Inc. His patent work addresses the use of machine learning to identify and remediate issues in application ecosystems.

Latest Patents

Thiruvellore is associated with 1 patent: “Machine learning-based issue remediation utilizing an application topology graph representation.” The invention describes a system that processes an incident’s natural-language description alongside a graph of applications and their dependencies. A machine-learning model identifies applications that may be causing the reported issues and determines resolution information. The system can then use that information to remediate the issues in the identified applications.

Career Highlights

Thiruvellore’s documented patent contribution focuses on applying machine learning and application topology representations to incident analysis and remediation. The approach connects application dependencies with automated identification of likely sources and potential resolutions.

Collaborations

His listed coworkers include Shibi Panikkar and Ravuru Vijaya Sankar. The available information identifies these professional associations but does not specify their roles in the patent.

Conclusion

Nagarajan Thiruvellore’s patent highlights an approach to application support that combines natural-language incident descriptions, dependency graphs, and machine learning to help identify and resolve software ecosystem issues.

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]
Loading…