Sunnyvale, CA, United States of America

Mansi Ajit Shah

USPTO Granted Patents = 4 

Average Co-Inventor Count = 4.6

ph-index = 2

Forward Citations = 25(Granted Patents)


Company Filing History:


Years Active: 2015-2020

where 'Filed Patents' based on already Granted Patents

4 patents (USPTO):

Title: Mansi Ajit Shah: Innovator in Data Synchronization Technologies

Introduction

Mansi Ajit Shah is a prominent inventor based in Sunnyvale, CA. He has made significant contributions to the field of data synchronization, holding a total of 4 patents. His work primarily focuses on enhancing the efficiency of data management across cluster filesystems.

Latest Patents

Mansi's latest patents include innovative methods for synchronizing updates across cluster filesystems. One of his notable inventions describes a system for synchronization of data in a shared pool of configurable computer resources. This invention involves creating consistency points in a source filesystem and comparing them to detect directory changes. It identifies file-level changes in a target filesystem and updates the established directory accordingly. Another patent elaborates on capturing images of filesystem changes, including data and metadata, in the form of consistency points. This method ensures that changes are communicated efficiently as filesystem operations, limited to the differences captured in the consistency points.

Career Highlights

Mansi Ajit Shah is currently employed at International Business Machines Corporation (IBM), where he continues to develop cutting-edge technologies in data synchronization. His expertise in this area has positioned him as a valuable asset to his team and the company.

Collaborations

Mansi has collaborated with notable colleagues such as Frank Bernhard Schmuck and Karan Gupta, contributing to various projects that enhance data management solutions.

Conclusion

Mansi Ajit Shah's innovative work in data synchronization technologies has made a significant impact in the field. His patents reflect a deep understanding of complex data systems and a commitment to improving data management practices.

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