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For the Inventor, By the Inventor

Redmond, WA, United States of America

Ruchi Bhargava

USPTO Granted Patents = 19 

 

Average Co-Inventor Count = 7.5

ph-index = 5

Forward Citations = 42(Granted Patents)


Location History:

  • Redmond, WA (US) (2014 - 2024)
  • Santa Clara, CA (US) (2024)

Company Filing History:

goldMedal12 out of 5,442 
 
Nvidia Corporation
 patents
silverMedal3 out of 54,719 
 
Microsoft Technology Licensing, LLC
 patents
where one patent can have more than one assignee

Years Active: 2014-2025

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19 patents (USPTO):Explore Patents
1. 12437412 - Deep neural network for segmentation of road scenes and animate object instances for autonomous driving applications (2025-10-07),
2. 12399253 - Deep neural network for detecting obstacle instances using radar sensors in autonomous machine applications (2025-08-26),
3. 12164059 - Top-down object detection from LiDAR point clouds (2024-12-10),
4. 12080078 - Multi-view deep neural network for LiDAR perception (2024-09-03),
5. 12072443 - Segmentation of lidar range images (2024-08-27),
6. 12051206 - Deep neural network for segmentation of road scenes and animate object instances for autonomous driving applications (2024-07-30),
7. 12050285 - Deep neural network for detecting obstacle instances using radar sensors in autonomous machine applications (2024-07-30),
8. 12001958 - Future trajectory predictions in multi-actor environments for autonomous machine (2024-06-04),
9. 11885907 - Deep neural network for detecting obstacle instances using radar sensors in autonomous machine applications (2024-01-30),
10. 11874663 - Systems and methods for computer-assisted shuttles, buses, robo-taxis, ride-sharing and on-demand vehicles with situational awareness (2024-01-16),
11. 11788861 - Map creation and localization for autonomous driving applications (2023-10-17),
12. 11713978 - Map creation and localization for autonomous driving applications (2023-08-01),
13. 11698272 - Map creation and localization for autonomous driving applications (2023-07-11),
14. 11532168 - Multi-view deep neural network for LiDAR perception (2022-12-20),
15. 11531088 - Deep neural network for detecting obstacle instances using radar sensors in autonomous machine applications (2022-12-20),

Title: Ruchi Bhargava: Innovator in Advanced Object Detection Technologies

Introduction

Ruchi Bhargava is an accomplished inventor based in Redmond, WA, known for his significant contributions to the field of object detection technologies. With a remarkable portfolio of 15 patents, Ruchi has made a profound impact in the realm of computer vision and autonomous systems.

Latest Patents

Among his latest innovations are two notable patents: "Top-down object detection from LiDAR point clouds" and "Segmentation of LiDAR range images." Both patents revolve around the use of deep neural networks (DNN) to analyze and interpret sensor data from three-dimensional environments. These technologies enable autonomous vehicles to detect, classify, and navigate safely by creating 2D and 3D bounding boxes along with class labels for various objects, enhancing the safety and efficiency of autonomous navigation systems.

Career Highlights

Ruchi has worked with leading companies in the technology sector, including Nvidia Corporation and Microsoft Technology Licensing, LLC. His expertise has helped advance the capabilities of machine learning algorithms, particularly in the processing of complex sensor data for autonomous applications. His innovations not only contribute to technological advancements but also pave the way for future research in autonomous navigation.

Collaborations

Throughout his career, Ruchi Bhargava has collaborated with notable colleagues like David Nister and Nikolai Smolyanskiy. Their combined efforts in developing cutting-edge object detection technologies have further solidified Ruchi's reputation as a leading figure in the field of computer vision.

Conclusion

Ruchi Bhargava’s inventive spirit and dedication to advancing object detection technologies make him a valuable contributor to the tech industry. His patents reflect a keen understanding of the complexities involved in autonomous systems, and his work continues to influence the development of smarter and safer technologies for the future.

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