Reading, MA, United States of America

Stephen R Dion

USPTO Granted Patents = 2 

Average Co-Inventor Count = 4.4

ph-index = 1


Company Filing History:


Years Active: 2024-2025

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2 patents (USPTO):Explore Patents

Title: The Innovative Contributions of Stephen R Dion

Introduction

Stephen R Dion is a notable inventor based in Reading, MA (US). He has made significant contributions to the field of predictive data analysis, holding 2 patents that showcase his innovative approach to technology. His work primarily focuses on utilizing machine learning models to enhance data analysis processes.

Latest Patents

Dion's latest patents include "Temporally Dynamic Location-Based Predictive Data Analysis." This invention provides methods, apparatus, systems, and computing devices for performing predictive data analysis that is dynamically adjusted based on location. The patent emphasizes the use of cohort generation machine learning models and cohort-based growth forecast machine learning models. Another patent, titled "Techniques for Temporally Dynamic Location-Based Predictive Data Analysis," also focuses on similar methodologies, utilizing prevalence-based, growth-based, and environment-based density modeling data objects to improve data analysis accuracy.

Career Highlights

Stephen R Dion is currently employed at UnitedHealth Group Incorporated, where he applies his expertise in data analysis and machine learning. His work at this prominent healthcare company allows him to contribute to advancements in predictive analytics, which can significantly impact healthcare delivery and patient outcomes.

Collaborations

Dion collaborates with talented professionals such as Mario M Suarez and Elijah J Fiore, who share his passion for innovation and technology. Their combined efforts contribute to the development of cutting-edge solutions in the field of data analysis.

Conclusion

Stephen R Dion's innovative work in predictive data analysis exemplifies the impact of machine learning on technology. His patents reflect a commitment to advancing the field and improving data-driven decision-making processes.

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