Bengaluru, India

Debamalya Choudhury

USPTO Granted Patents = 1 

Average Co-Inventor Count = 5.0

ph-index = 1


Company Filing History:


Years Active: 2025

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1 patent (USPTO):Explore Patents

Title: Debamalya Choudhury: Innovator in Evaluating Contract Worthiness of Performing Artists

Introduction

Debamalya Choudhury is a notable inventor based in Bengaluru, India. He has made significant contributions to the field of evaluating contract worthiness for performing artists. His innovative approach utilizes machine learning to assess various metrics related to artists' performance and engagement.

Latest Patents

Debamalya holds a patent titled "Method and system for evaluating contract worthiness of performing artists." This patent describes a comprehensive method that includes receiving consolidated data for a set of performing artists. The process involves classifying topics in the text data into multiple categories using a machine learning classification model. It also determines user engagement behavior segments based on sentiment scores and calculates a contract worthiness score using a trained model. This innovative system aims to evaluate the contract worthiness of performing artists effectively.

Career Highlights

Debamalya Choudhury is currently employed at Infosys Limited, where he applies his expertise in machine learning and data analysis. His work focuses on developing systems that enhance the evaluation processes within the entertainment industry. His contributions have been instrumental in advancing the methodologies used to assess performing artists.

Collaborations

Debamalya has collaborated with talented coworkers such as Romi Malik and Vinay Govindan Muralidharan. Their combined efforts have led to the development of innovative solutions in their respective fields.

Conclusion

Debamalya Choudhury's work in evaluating contract worthiness for performing artists showcases his innovative spirit and dedication to advancing technology in the entertainment sector. His patent reflects a significant step forward in utilizing machine learning for practical applications.

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