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For the Inventor, By the Inventor

Cupertino, CA, United States of America

Ke Chen

This inventor holds 20 USPTO granted patents and 12 published patent applications and 1 EPO patent. Top assignees: Nvidia Corporation, Intel Corporation, Tahoe Research, Ltd.. Active years: 2017-2026.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Ke Chen. Retrieved from https://idiyas.com/inventor/ke-chen-s27mhz02

Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile

USPTO Granted Patents = 20 

% Patents Active = 95.0

 

Average Co-Inventor Count = 7.3

ph-index = 2

Forward Citations = 19(Granted Patents)


Location History:

  • Cupertino, CA (US) (2017 - 2023)
  • Sunnyvale, CA (US) (2022 - 2024)

Company Filing History:

goldMedal8 out of 6,195 
 
Nvidia Corporation
 patents
silverMedal7 out of 56,322 
 
Intel Corporation
 patents
bronzeMedal2 out of 85 
 
Tahoe Research, Ltd.
 patents
4. 1 out of 43,562 
 
Apple Inc.
 patents
where one patent can have more than one assignee

Years Active: 2017-2026

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20 patents (USPTO):Explore Patents
1. 12676007 - Freespace detection using machine learning for autonomous systems and applications (2026-07-07),
2. 12651465 - Multi-view deep neural network for LiDAR perception (2026-06-09),
3. 12525031 - Multi-view deep neural network for LiDAR perception (2026-01-13),
4. 12482118 - Landmark perception for localization in autonomous systems and applications (2025-11-25),
5. 12437412 - Deep neural network for segmentation of road scenes and animate object instances for autonomous driving applications (2025-10-07),
6. 12322126 - Predicting image warping for structure from motion using neural networks (2025-06-03),
7. 12165275 - Face augmentation in video (2024-12-10),
8. 12164059 - Top-down object detection from LiDAR point clouds (2024-12-10),
9. 12072443 - Segmentation of lidar range images (2024-08-27),
10. 12051206 - Deep neural network for segmentation of road scenes and animate object instances for autonomous driving applications (2024-07-30),
11. 11871052 - Multi-band rate control (2024-01-09),
12. 11741682 - Face augmentation in video (2023-08-29),
13. 11532168 - Multi-view deep neural network for LiDAR perception (2022-12-20),
14. 11328496 - Scalable real-time face beautification of video images (2022-05-10),
15. 10872230 - Low-cost face recognition using Gaussian receptive field features (2020-12-22),

Title: Inventor Ke Chen: Revolutionizing Technology in Cupertino

Introduction: Ke Chen, a visionary inventor based in Cupertino, CA, is renowned for his groundbreaking contributions to the field of technology. With a keen eye for innovation, he has consistently pushed the boundaries of what is possible in the digital realm.

Latest Patents: Ke Chen's latest patents include cutting-edge advancements in artificial intelligence, machine learning, and data analytics. His inventions have garnered widespread acclaim for their potential to transform industries and improve efficiency.

Career Highlights: Throughout his illustrious career, Ke Chen has held key positions at leading tech companies, where he has spearheaded research and development initiatives. His expertise in emerging technologies has led to the successful implementation of numerous projects that have reshaped the tech landscape.

Collaborations: Ke Chen is known for his collaborative spirit, having worked with top engineers, researchers, and developers on various projects. His ability to bring together diverse talents and perspectives has resulted in the creation of innovative solutions that address complex challenges.

Conclusion: In conclusion, Ke Chen stands as a trailblazing inventor whose passion for technology and relentless pursuit of excellence have cemented his reputation as a true pioneer in the field. His contributions continue to inspire and shape the future of innovation in Cupertino and beyond.

Profile summary based on public USPTO records.
Data Sources: USPTO Patent Grant XML, Patent Center, EPO & CIPO • Normalized by IDiyas Innovation Graph. Methodology & provenance architecturePlease report any incorrect information to [email protected]
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