Yunting Sun

Title: Yunting Sun: Innovator in Bayesian Hierarchical Models

Introduction

Yunting Sun is a prominent inventor based in Jersey City, NJ (US). She has made significant contributions to the field of data modeling, particularly in the development of Bayesian hierarchical models. With a total of 3 patents to her name, Yunting is recognized for her innovative approaches to data analysis and modeling.

Latest Patents

Yunting's latest patents include groundbreaking systems and methods for generating a brand Bayesian hierarchical model. This patent outlines a method that involves receiving a brand data set for various brands within a category, which includes content input across multiple media channels and responses over time. The process determines informative priors by generating a category Bayesian hierarchical model based on the brand data sets and weak priors. Additionally, she has developed systems for generating a geo-level hierarchical Bayesian model, which involves grouping geographic sub-regions and fitting a Bayesian hierarchical model based on geo-level data.

Career Highlights

Yunting Sun is currently employed at Google Inc., where she applies her expertise in data modeling to enhance the company's analytical capabilities. Her work focuses on creating models that improve the understanding of brand performance and geographic data analysis.

Collaborations

Yunting collaborates with notable colleagues, including Yuxue Jin and James Robert Koehler. These partnerships foster an environment of innovation and creativity, allowing for the development of advanced modeling techniques.

Conclusion

Yunting Sun's contributions to the field of Bayesian hierarchical models exemplify her innovative spirit and dedication to advancing data analysis. Her work at Google Inc. and her patented inventions highlight her role as a leading inventor in her field.