Overland Park, KS, United States of America

Diksha Agarwal


Average Co-Inventor Count = 6.0

ph-index = 1

Forward Citations = 1(Granted Patents)


Company Filing History:


Years Active: 2023

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1 patent (USPTO):Explore Patents

Title: Innovations of Diksha Agarwal in Cell Site Maintenance

Introduction

Diksha Agarwal is an accomplished inventor based in Overland Park, Kansas. She has made significant contributions to the field of telecommunications, particularly in the area of cell site maintenance. Her innovative approach has led to the development of a unique machine learning system designed to enhance the efficiency of cell site repairs.

Latest Patents

Diksha holds a patent for a "Cell Site Repair Part Prediction Machine Learning System." This system is designed to streamline the maintenance of cell sites by utilizing a combination of data stores, processors, and a part replacement prediction application. The application extracts features from the data stores and executes multiple part machine learning models. Each model analyzes specific features through a multi-label classification approach, ultimately predicting the probability that a particular part can resolve issues associated with a trouble ticket. When the probability exceeds a predefined threshold, the system determines which part should be retrieved from inventory for service.

Career Highlights

Diksha is currently employed at T-Mobile Innovations LLC, where she continues to develop cutting-edge solutions for the telecommunications industry. Her work focuses on integrating advanced technologies to improve operational efficiency and service reliability.

Collaborations

Diksha collaborates with talented professionals in her field, including Hui-Lin Chang and Lance Paul Lukens. These partnerships enhance her innovative projects and contribute to the overall success of her initiatives.

Conclusion

Diksha Agarwal's contributions to the telecommunications sector through her innovative patent demonstrate her commitment to improving cell site maintenance. Her work not only showcases her technical expertise but also highlights the importance of machine learning in modern telecommunications.

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