Foster City, CA, United States of America

Ruitao Yi

This inventor holds 2 USPTO granted patents and 1 published patent application. Top assignee: Zoox, Inc.. Active years: 2026.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Ruitao Yi. Retrieved from https://idiyas.com/inventor/ruitao-yi

Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile

USPTO Granted Patents = 2 

% Patents Active = 100.0

Average Co-Inventor Count = 2.0

ph-index = 1


Company Filing History:


Years Active: 2026

Loading Chart...
2 patents (USPTO):Explore Patents

Title: Ruitao Yi: Innovator in Prediction Error Classification

Introduction

Ruitao Yi is a notable inventor based in Foster City, CA (US). He has made significant contributions to the field of prediction error classification. His innovative techniques are designed to enhance the accuracy of machine learning models.

Latest Patents

Ruitao Yi holds a patent for "Prediction errors classification." This patent describes techniques for determining and aggregating prediction errors. A prediction may be determined for an object within a region based on first sensor data. A prediction error is calculated based on the difference between the prediction and second sensor data. The prediction error is classified by one or more error types and aggregated by the same error type. The aggregated prediction error can be utilized to train a machine-learned prediction model. He has 1 patent to his name.

Career Highlights

Ruitao Yi is currently employed at Zoox, Inc., where he applies his expertise in developing advanced technologies. His work focuses on improving the efficiency and reliability of predictive models in various applications.

Collaborations

Due to space constraints, the collaborations section has been omitted.

Conclusion

Ruitao Yi is a pioneering inventor whose work in prediction error classification is paving the way for advancements in machine learning. His contributions are essential for the development of more accurate predictive models.

Profile summary based on public USPTO records.
Data Sources: USPTO Patent Grant XML, Patent Center, EPO & CIPO • Normalized by IDiyas Innovation Graph. Methodology & provenance architecturePlease report any incorrect information to [email protected]
Loading…