Santa Clara, CA, United States of America

Mehdi Sajjadi Mohammadabadi

USPTO Granted Patents = 3 

Average Co-Inventor Count = 16.0

ph-index = 1

Forward Citations = 38(Granted Patents)


Company Filing History:


Years Active: 2021-2025

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3 patents (USPTO):Explore Patents

Title: Innovations of Mehdi Sajjadi Mohammadabadi

Introduction

Mehdi Sajjadi Mohammadabadi is a notable inventor based in Santa Clara, CA. He has made significant contributions to the field of autonomous vehicle technology. With a total of three patents to his name, his work focuses on enhancing the safety and efficiency of self-driving vehicles.

Latest Patents

One of Mehdi's latest patents involves the real-time detection of lanes and boundaries by autonomous vehicles. In this innovation, sensor data representative of an image from a vehicle's field of view is received and applied to a machine learning model. The model computes a segmentation mask that represents portions of the image corresponding to lane markings on the driving surface. Analysis of this segmentation mask allows for the determination of lane marking types. Lane boundaries are generated by performing curve fitting on the lane markings corresponding to each type. The data representing these lane boundaries is then sent to a vehicle component to assist in navigating through the driving surface.

Career Highlights

Mehdi currently works at Nvidia Corporation, a leading company in graphics processing and AI technology. His role involves developing advanced algorithms that improve the functionality of autonomous systems. His expertise in machine learning and computer vision has positioned him as a key player in the field.

Collaborations

Mehdi collaborates with talented individuals such as Yifang Xu and Xin Liu. Together, they work on innovative projects that push the boundaries of technology in autonomous vehicles.

Conclusion

Mehdi Sajjadi Mohammadabadi's contributions to the field of autonomous vehicle technology are noteworthy. His patents reflect a commitment to improving vehicle navigation and safety through advanced machine learning techniques. His work continues to influence the future of transportation.

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