Ruoyun Huang

Title: The Innovations of Ruoyun Huang

Introduction

Ruoyun Huang is an accomplished inventor based in Kirkland, WA (US). He has made significant contributions to the field of technology, particularly in the areas of demographic inference and user attribute determination. With a total of 2 patents, Huang's work has garnered attention for its innovative approaches to data analysis and user classification.

Latest Patents

Huang's latest patents include groundbreaking methods and systems for demographic inference calibration. These methods involve computer programs encoded on a computer-readable storage medium for labeling user identifiers. The process identifies a set of unlabeled identifiers and determines the probability of their inclusion in a specific class of multi-class demographic characteristics based on known user behavior. This innovative approach allows for the adjustment of probabilities based on internet distribution, ultimately assigning accurate labels to the identifiers.

Another notable patent focuses on determining an attribute of an online user using user device data. This computer-implemented method utilizes a host computing device to identify model data from various computing devices, including location and access data. By training a classification model with this data, Huang's method can accurately categorize online users based on their device information.

Career Highlights

Ruoyun Huang is currently employed at Google Inc., where he continues to develop and refine his innovative ideas. His work at Google has allowed him to collaborate with other talented professionals in the field, further enhancing his contributions to technology.

Collaborations

Some of Huang's notable coworkers include Arthur Asuncion and Yong Sheng. Their collaborative efforts have likely played a role in the successful development of Huang's patents and innovations.

Conclusion

Ruoyun Huang's contributions to technology through his patents demonstrate his expertise and innovative thinking. His work in demographic inference and user attribute determination continues to influence the field, showcasing the importance of data-driven approaches in understanding user behavior.