Wilmington, DE, United States of America

Nina Chang



Average Co-Inventor Count = 3.0

ph-index = 1

Forward Citations = 26(Granted Patents)


Company Filing History:


Years Active: 2019-2022

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2 patents (USPTO):Explore Patents

Title: Nina Chang: Innovator in Automated Data Cleansing

Introduction

Nina Chang is a prominent inventor based in Wilmington, DE (US). She has made significant contributions to the field of data cleansing, particularly in the context of automated robotic traffic. With a total of 2 patents to her name, Nina is recognized for her innovative approaches to improving data analysis processes.

Latest Patents

Nina's latest patents focus on systems and methods for cleansing automated robotic traffic from sets of usage logs. These exemplary embodiments provide solutions for cleansing data generated by servers in response to database interactions. The technology involves analyzing log entries corresponding to events during a session to determine relationships between those events. The usage logs can then be classified based on these relationships, distinguishing between human behavior and automated software robot behavior. Logs identified as corresponding to automated software robot behavior can be removed from further analysis, enhancing the accuracy of data interpretation.

Career Highlights

Nina Chang is currently employed at Camelot UK Bidco Limited, where she continues to develop her innovative ideas. Her work has been instrumental in advancing the understanding of automated interactions with databases, making her a valuable asset to her company and the industry.

Collaborations

Nina has collaborated with notable coworkers, including Jacob Sisk and James Pringle. Their combined expertise contributes to the success of their projects and the advancement of their shared goals.

Conclusion

Nina Chang is a trailblazer in the field of automated data cleansing, with her innovative patents paving the way for more efficient data analysis. Her contributions are shaping the future of how automated interactions are understood and managed.

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