Sugar Land, TX, United States of America

Ji Zang


Average Co-Inventor Count = 5.0

ph-index = 1

Forward Citations = 7(Granted Patents)


Company Filing History:


Years Active: 2022

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1 patent (USPTO):Explore Patents

Title: The Innovative Contributions of Ji Zang

Introduction

Ji Zang is an accomplished inventor based in Sugar Land, Texas. He has made significant contributions to the field of data clustering and risk forecasting, particularly in the insurance sector. His innovative approach combines advanced data analysis techniques with practical applications to enhance predictive modeling.

Latest Patents

Ji Zang holds a patent for "Systems and methods for clustering data to forecast risk and other metrics." This patent outlines methods and systems for clustering data to train models that predict loss metrics for insurance. The process involves cleaning and aggregating historical data to a quarterly time granularity and a zip code geographic granularity. Features for generating clusters are selected, and various clustering algorithms are employed to create and evaluate these clusters. The best set of clusters is then chosen to train development and forecast models for the loss metric. The accuracy of these models is continuously evaluated, and the clustering process is refined until satisfactory accuracy and stability are achieved.

Career Highlights

Ji Zang is currently employed at Datalnfocom USA, Inc., where he applies his expertise in data clustering and predictive modeling. His work focuses on enhancing the accuracy of risk assessments in the insurance industry through innovative data analysis techniques.

Collaborations

Ji collaborates with talented colleagues, including Wensu Wang and Chun Wang, who contribute to the development of advanced data solutions. Their teamwork fosters a creative environment that drives innovation and enhances the effectiveness of their projects.

Conclusion

Ji Zang's contributions to data clustering and risk forecasting exemplify the impact of innovative thinking in the insurance industry. His patent and collaborative efforts highlight the importance of data-driven solutions in predicting and managing risk.

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