Belmont, CA, United States of America

Seyed Parsa Beheshti

USPTO Granted Patents = 1 

Average Co-Inventor Count = 4.0

ph-index = 1


Company Filing History:


Years Active: 2025

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1 patent (USPTO):Explore Patents

Title: Seyed Parsa Beheshti: Innovator in Autonomous Vehicle Technology

Introduction

Seyed Parsa Beheshti is a notable inventor based in Belmont, California. He has made significant contributions to the field of autonomous vehicles, particularly in the area of sound determination systems. His innovative approach aims to enhance the interaction between autonomous vehicles and their environments.

Latest Patents

Seyed Parsa Beheshti holds a patent titled "Autonomous vehicle sound determination by a model." This patent discusses techniques for determining audio data for output by an autonomous vehicle. The system can identify audio data representing different frequencies and sound levels for various object types in the environment. The audio data can be tailored for specific entities, such as humans or animals, and can be adjusted based on environmental factors like noise levels, weather, and ambient light. The model is designed to provide continuous audio output in proximity to specific objects or regions, with sound levels adjusted over time based on the likelihood of an intersection between a vehicle's path and an object's path.

Career Highlights

Seyed Parsa Beheshti is currently employed at Zoox, Inc., a company focused on developing autonomous vehicle technology. His work at Zoox has positioned him as a key player in advancing the capabilities of self-driving cars.

Collaborations

He collaborates with talented individuals such as William Randolph Geddings, Jr. and Anoop Jatavallabha Vijayakumar, contributing to a dynamic team dedicated to innovation in the automotive industry.

Conclusion

Seyed Parsa Beheshti's work in autonomous vehicle sound determination exemplifies the innovative spirit driving advancements in transportation technology. His contributions are paving the way for safer and more efficient autonomous vehicles.

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