This inventor holds 14 USPTO granted patents and 6 published patent applications, plus 2 CIPO patents. Top assignees: Intuit, Inc., Inuit, Inc.. Active years: 2020-2026.
Location History:
- San Jose, CA (US) (2020 - 2024)
- Mountain View, CA (US) (2023 - 2024)
- Milpitas, CA (US) (2024)
Company Filing History:
Years Active: 2020-2026
Title: Runhua Zhao - Innovator in Behavior Prediction and Risk Scoring
Introduction
Runhua Zhao is a prominent inventor based in San Jose, CA (US). He has made significant contributions to the fields of behavior prediction and risk scoring, holding a total of 14 patents. His innovative work has garnered attention for its practical applications in technology and data analysis.
Latest Patents
One of Runhua Zhao's latest patents is the "Hierarchical attention time-series (HAT) model for behavior prediction." This invention provides techniques for predicting user behavior by analyzing activity data. The model segments user sessions and utilizes a hierarchical attention mechanism to generate predictions and explanatory information based on user actions. Another notable patent is for "Calibrated risk scoring and sampling." This method involves extracting features from records to generate risk scores using machine learning models. The records are then mapped to risk buckets, allowing for effective sampling and presentation of prepopulated forms to client devices.
Career Highlights
Runhua Zhao is currently employed at Intuit, Inc., where he continues to develop innovative solutions that enhance user experience and improve risk assessment processes. His work at Intuit has positioned him as a key player in the intersection of technology and data science.
Collaborations
Runhua has collaborated with talented individuals such as Chris Wang and Danni Jin, who contribute to the dynamic environment of innovation at Intuit.
Conclusion
Runhua Zhao's contributions to behavior prediction and risk scoring exemplify the impact of innovative thinking in technology. His patents reflect a commitment to advancing the field and improving user interactions through data-driven solutions.