San Francisco, CA, United States of America

Eran Davidov

USPTO Granted Patents = 3 

Average Co-Inventor Count = 5.0

ph-index = 2

Forward Citations = 6(Granted Patents)


Company Filing History:


Years Active: 2022-2025

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3 patents (USPTO):Explore Patents

Title: Innovations by Eran Davidov in Transportation Matching Systems

Introduction

Eran Davidov is an accomplished inventor based in San Francisco, CA. He has made significant contributions to the field of transportation matching systems, holding a total of 3 patents. His work focuses on optimizing provider resources through predictive modeling, which enhances the efficiency of transportation services.

Latest Patents

Davidov's latest patents include a groundbreaking application titled "Using a predictive request model to optimize provider resources." This application discloses an improved transportation matching system, along with corresponding methods and computer-readable media. The system trains a predictive request model to generate a metric that is predicted to trigger an increase in transportation provider activity within a specific geographic area for a given time period. Additionally, it determines a predicted gap between expected request activity and expected transportation provider activity for that area during a future time period. By utilizing the predictive request model and the predicted gap, the system generates a metric for the geographic area and creates an interactive map associated with a customized schedule based on the generated metric.

Career Highlights

Eran Davidov is currently employed at Lyft, Inc., where he continues to innovate in the transportation sector. His work has been instrumental in developing systems that improve the efficiency of transportation services, benefiting both providers and users.

Collaborations

Davidov collaborates with talented individuals such as Saurabh Bajaj and Davide Crapis, contributing to a dynamic team focused on advancing transportation technology.

Conclusion

Eran Davidov's innovative work in transportation matching systems exemplifies the impact of predictive modeling on optimizing provider resources. His contributions are paving the way for more efficient transportation solutions in the industry.

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