Lakewood, CO, United States of America

Alyssa Hester

USPTO Granted Patents = 4 


Average Co-Inventor Count = 3.0

ph-index = 1


Company Filing History:


Years Active: 2022-2025

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4 patents (USPTO):Explore Patents

Title: Alyssa Hester: Innovator in Machine Learning and Database Systems

Introduction

Alyssa Hester is a prominent inventor based in Lakewood, CO (US). She has made significant contributions to the field of machine learning and database systems, holding a total of 4 patents. Her innovative work focuses on enhancing the efficiency of database recommendations through advanced machine-learning techniques.

Latest Patents

One of Alyssa's latest patents is a machine-learned database recommendation model. This central database system trains a machine-learned model based on training data that identifies characteristics of account holder entities, characteristics of account provider entities, and the relationships between them. For a target entity, the system identifies a target set of account provider entities and applies the trained model to identify a subset of these entities. The identified subset consists of account provider entities that are most likely to establish a relationship with the target entity. A recommendation is then generated for display, identifying the subset of account provider entities and including interface elements that, when selected, notify the corresponding account provider entity of the target entity.

Career Highlights

Alyssa currently works at Zenpayroll, Inc., where she continues to develop innovative solutions in the realm of database systems and machine learning. Her work has been instrumental in advancing the capabilities of recommendation systems, making them more effective and user-friendly.

Collaborations

Alyssa collaborates with talented individuals such as Victoria Huang and Rebecca Carter, contributing to a dynamic and innovative work environment.

Conclusion

Alyssa Hester is a trailblazer in the field of machine learning and database systems, with a focus on creating effective recommendation models. Her contributions are shaping the future of how databases interact with users and provide tailored recommendations.

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