Westfield, NJ, United States of America

Christopher J Leasor

USPTO Granted Patents = 1 

Average Co-Inventor Count = 13.0

ph-index = 1


Company Filing History:


Years Active: 2023

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1 patent (USPTO):Explore Patents

Title: Christopher J Leasor: Innovator in Payment Solutions

Introduction

Christopher J Leasor is an accomplished inventor based in Westfield, NJ (US). He has made significant contributions to the field of payment applications through his innovative patent. His work focuses on enhancing the efficiency of searching for billers using advanced machine learning techniques.

Latest Patents

Christopher holds a patent titled "System and method for searching billers with service area popularity model and machine learning." This patent discloses various methods, apparatuses, systems, and media for implementing a payment application module for searching billers. The invention utilizes a plurality of data sources, including customer profile data, customer payment history data, biller information data, and biller directory data. A processor, operatively coupled to these data sources via a communication network, builds a customer profile service area popularity model. It receives search query data for searching a biller, builds a biller search machine learning model to optimize weights applied to the search query data, and ranks search results by utilizing the machine learning model in response to the search query data. Christopher has 1 patent to his name.

Career Highlights

Christopher is currently employed at JPMorgan Chase Bank, N.A., where he applies his expertise in payment solutions. His role involves leveraging his innovative ideas to improve the bank's services and enhance customer experiences.

Collaborations

Christopher has collaborated with talented individuals such as Jiangling Wang and Song Ting Ceng. Their combined efforts contribute to the advancement of payment technologies and innovative solutions in the financial sector.

Conclusion

Christopher J Leasor is a notable inventor whose work in payment applications showcases the potential of machine learning in optimizing financial transactions. His contributions continue to influence the industry and improve user experiences.

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