Location History:
- Santa Clara, CA (US) (2022)
- Sunnyvale, CA (US) (2023)
Company Filing History:
Years Active: 2022-2023
Title: Conghui Fu: Innovator in Machine Learning and Ride-Sharing Technology
Introduction
Conghui Fu is a prominent inventor based in Santa Clara, CA, known for his contributions to the field of machine learning and ride-sharing technology. With a total of 2 patents, Fu has made significant strides in enhancing the efficiency and safety of ride-sharing services.
Latest Patents
One of Fu's latest patents is focused on machine learning-based real-time guest rider identification. This innovative technique involves automatically detecting when a ride requester has requested a ride-share ride on behalf of a guest rider. The system utilizes chat logs between the driver and ride requester to identify potential guest rider behavior. By training an artificial intelligence model, the server can analyze these communications to predict and confirm guest rider actions.
Another notable patent by Fu addresses mismatched driver detection. This invention identifies mismatched drivers based on passenger evaluations. By obtaining a set of evaluations regarding whether a current driver matches a registered driver, the system computes an identification rate. If this rate exceeds a predetermined threshold, the driver's identity is validated; otherwise, the driver is flagged as mismatched.
Career Highlights
Conghui Fu is currently employed at Beijing Didi Infinity Technology and Development Co., Ltd., where he continues to develop innovative solutions in the ride-sharing sector. His work has significantly impacted the way ride-sharing services operate, enhancing user experience and safety.
Collaborations
Fu collaborates with talented individuals such as Zihan Yi and Zetian Ni, contributing to a dynamic team focused on advancing technology in the transportation industry.
Conclusion
Conghui Fu's innovative patents and contributions to machine learning and ride-sharing technology demonstrate his commitment to improving the industry. His work not only enhances the efficiency of ride-sharing services but also prioritizes user safety and experience.