Bengaluru, India

Navya Yarrabelly


Average Co-Inventor Count = 11.0

ph-index = 1

Forward Citations = 1(Granted Patents)


Company Filing History:


Years Active: 2021-2024

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2 patents (USPTO):Explore Patents

Title: Innovations by Navya Yarrabelly

Introduction

Navya Yarrabelly is an accomplished inventor based in Bengaluru, India. She has made significant contributions to the field of technology, particularly in the area of recommendation systems. With a total of two patents to her name, her work showcases her innovative approach to complex data modeling.

Latest Patents

Navya's latest patents include a "Multiple-entity-based recommendation system" and a "Message recommendation system." The multiple-entity-based recommendation system utilizes rich data by modeling items and recipients as 'complex entities.' This system allows for the integration of static sub-entities and dynamic components, leveraging multiple relationships between these sub-entities as represented in bipartite graphs. The process of generating recommendations involves creating vector representations of the sub-entities using graph-based convolutional networks. These representations are then combined to form comprehensive models of the items and users, which are subsequently fed into a classifier model. Similarly, the message recommendation system employs the same innovative approach to enhance the quality of recommendations.

Career Highlights

Navya Yarrabelly is currently employed at Microsoft Technology Licensing, LLC, where she continues to develop her groundbreaking ideas. Her work at Microsoft has allowed her to collaborate with leading experts in the field and contribute to cutting-edge technology.

Collaborations

Some of her notable coworkers include Lekshmi Menon and Amar Budhiraja, who share her passion for innovation and technology.

Conclusion

Navya Yarrabelly's contributions to the field of recommendation systems highlight her innovative spirit and dedication to advancing technology. Her patents reflect a deep understanding of complex data relationships and the potential for enhancing user experiences through intelligent recommendations.

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