Mountain View, CA, United States of America

Mayank Gupta

USPTO Granted Patents = 7 

Average Co-Inventor Count = 3.9

ph-index = 1

Forward Citations = 4(Granted Patents)


Company Filing History:


Years Active: 2022-2024

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7 patents (USPTO):

Title: Innovations by Mayank Gupta in Autonomous Driving Technology

Introduction

Mayank Gupta is an accomplished inventor based in Mountain View, CA, with a focus on advancements in autonomous driving technology. He holds a total of seven patents that contribute significantly to the field of machine learning and data processing in vehicles. His work is pivotal in enhancing the safety and efficiency of autonomous navigation systems.

Latest Patents

Among his latest patents, Gupta has developed methods and apparatus for automatically labeling data processing events in autonomous driving vehicles via machine learning. This innovative method involves receiving sensor data from an autonomous vehicle and identifying events based on this data. The processor extracts attributes associated with these events and generates labels for unrecognized events, thereby improving the vehicle's understanding of its environment. Another notable patent focuses on mapping and detection for safe navigation. This patent outlines operations for determining map and detection data, identifying changes in the environment, and generating control data to ensure safe navigation.

Career Highlights

Gupta's career is marked by his contributions to Plusai Limited, where he applies his expertise in machine learning and data processing. His innovative approaches have positioned him as a key player in the development of autonomous vehicle technologies.

Collaborations

Gupta collaborates with talented individuals such as Anurag Ganguli and Timothy Patrick Daly, Jr., who share his vision for advancing autonomous driving solutions.

Conclusion

Mayank Gupta's work in the field of autonomous driving technology showcases his commitment to innovation and safety. His patents reflect a deep understanding of machine learning and its applications in real-world scenarios.

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