San Jose, CA, United States of America

Mayank Bansal

This inventor holds 1 USPTO granted patent. Top assignee: Ebay, Incorporated. Active years: 2017.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Mayank Bansal. Retrieved from https://idiyas.com/inventor/mayank-bansal-8knlnjaa

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


% Patents Active = 100.0

Average Co-Inventor Count = 5.0

ph-index = 1

Forward Citations = 43(Granted Patents)


Company Filing History:


Years Active: 2017

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1 patent (USPTO):Explore Patents

Title: Mayank Bansal: Innovator in Anomaly Detection

Introduction

Mayank Bansal is a prominent inventor based in San Jose, CA (US). He has made significant contributions to the field of technology, particularly in the area of predictive modeling and anomaly detection. His innovative work has led to the development of a unique patent that addresses critical challenges in network monitoring.

Latest Patents

Mayank holds a patent for a "Predictive model for anomaly detection and feedback-based scheduling." In this invention, clusters of nodes in a network are monitored, and the monitored data is stored in an open time-series database. The data is then labeled as training data, which is used to build a machine learning model. Additional unlabeled data is retrieved from the database, and anomalies in this data are computed using the model, resulting in prediction outcomes and metrics.

Career Highlights

Mayank Bansal is currently employed at eBay, Incorporated, where he applies his expertise in machine learning and data analysis. His work focuses on enhancing the efficiency and reliability of network systems through innovative solutions.

Collaborations

Some of Mayank's notable coworkers include Chaitali Gupta and Tzu-Cheng Chuang, who contribute to the collaborative environment at eBay.

Conclusion

Mayank Bansal's contributions to the field of anomaly detection through his innovative patent demonstrate his commitment to advancing technology. His work not only enhances network monitoring but also showcases the potential of machine learning in solving complex problems.

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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