Bengaluru, India

Maria Charles Maria Selvam

This inventor holds 1 USPTO granted patent. Top assignee: Hewlett Packard Enterprise Development LP. Active years: 2026.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Maria Charles Maria Selvam. Retrieved from https://idiyas.com/inventor/maria-charles-maria-selvam

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

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Company Filing History:


Years Active: 2026

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1 patent (USPTO):Explore Patents

Title: Maria Charles Maria Selvam: Innovator in Machine Learning for Network Analysis

Introduction

Maria Charles Maria Selvam is a prominent inventor based in Bengaluru, India. She has made significant contributions to the field of machine learning, particularly in the area of root cause analysis for computer networks. Her innovative approach combines artificial intelligence with network telemetry data to enhance the efficiency of network management.

Latest Patents

Maria holds a patent for a groundbreaking invention titled "Machine learning assisted root cause analysis for computer networks." This system utilizes one or more processors to receive telemetry data from various network devices. It applies an AI anomaly detection model, trained on historical telemetry data, to identify anomalies in the received data. Furthermore, it employs an AI root cause analysis model to determine the underlying issues causing these anomalies.

Career Highlights

Maria is currently employed at Hewlett Packard Enterprise Development LP, where she continues to push the boundaries of technology. Her work focuses on integrating machine learning techniques into practical applications that improve network reliability and performance.

Collaborations

Some of her notable coworkers include Ajit Krishna Patankar and Kihwan Han. Their collaborative efforts contribute to the advancement of innovative solutions in the tech industry.

Conclusion

Maria Charles Maria Selvam is a trailblazer in the field of machine learning and network analysis. Her contributions are paving the way for more efficient and intelligent network management systems.

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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