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Menlo Park, CA, United States of America

Cyngn, Inc.

Calculating rank

USPTO Granted Patents = 25

Trademarks = 4

Forward Citations = 6

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15 inventors (with patents filed for the assignee):

Biao Ma (21 out of 23 patents)

Lior Tal (19 out of 19 patents)

Michael W Lowe (4 out of 24 patents)

4. Andrea Mariotti (4 out of 4 patents)

5. Pranav Bajoria (4 out of 4 patents)

6. Ain McKendrick (4 out of 33 patents)

7. Akash Joshi (2 out of 2 patents)

8. I-Chung Joseph Lin (1 out of 1 patent)

9. Elena Ramona Stefanescu (1 out of 1 patent)

10. Dhivya Sukumar (1 out of 1 patent)

11. Sumit Saxena (1 out of 1 patent)

12. Manny LaCarrubba (1 out of 1 patent)

13. Eitan Slavik (1 out of 1 patent)

14. Michael Ansell (1 out of 1 patent)

15. Nicholas Liotta (1 out of 1 patent)

Core Competencies:

Vehicle System Identification

Modular Sensor System

Off-Board Computation

High-Definition Mapping

Object-Based Decision Making

Motion Compensation

Traffic Rule Decision Making

Computation Acceleration

Trajectory Prediction

Obstacle Detection

LiDAR-Camera Synchronization

3D Object Detection

25 patents: Sort by Forward Citations

1. 12530029 - System and method of adaptive, real-time vehicle system identification for autonomous driving (2026-01-20),

2. 12332083 - Modular sensor system for automated guided vehicles (2025-06-17),

3. 12246733 - System and method of off-board-centric autonomous driving computation (2025-03-11),

4. 12181890 - High-definition mapping (2024-12-31),

5. 12039867 - System and methods of adaptive object-based decision making for autonomous driving (2024-07-16),

6. 12032099 - Adaptive motion compensation of perception channels (2024-07-09),

7. 11851074 - System and method of large-scale autonomous driving validation (2023-12-26),

8. 11837090 - System and methods of adaptive traffic rule-based decision making for autonomous driving (2023-12-05),

9. 11837089 - Modular extensible behavioral decision system for autonomous driving (2023-12-05),

10. 11767034 - System and method of computation acceleration for autonomous driving systems (2023-09-26),

11. 11760368 - System and method of same-loop adaptive simulation for autonomous driving (2023-09-19),

12. 11747454 - Granularity-flexible existence-based object detection (2023-09-05),

13. 11745762 - System and methods of adaptive trajectory prediction for autonomous driving (2023-09-05),

14. 11745750 - System and method of large-scale automatic grading in autonomous driving using a domain-specific language (2023-09-05),

15. 11745747 - System and method of adaptive distribution of autonomous driving computations (2023-09-05),

Company Overview

Cyngn, Inc. is a technology company based in Menlo Park, California, specializing in advanced autonomous vehicle solutions. The organization focuses on developing software platforms that enhance the operational efficiency and safety of self-driving vehicles across various industries. With a commitment to innovation, Cyngn integrates artificial intelligence and machine learning technologies to create scalable and adaptable systems for fleet management and logistics, positioning itself at the forefront of the autonomous mobility sector.

Profile summary synthesized from public USPTO records and patent filings.

Company Badge

USPTO Data Jan 1 1976 - Nov 10 2026

25 Patents

#64 in Menlo Park, CA

#3,166 in California

#13,398 in US

#25,794 in the World

Menlo Park, CA, United States of America

Cyngn, Inc.

Forward Citations = 6

15 inventors:

Biao Ma (21 out of 23 patents)

Lior Tal (19 out of 19 patents)

Michael W Lowe (4 out of 24 patents)

4. Andrea Mariotti (4 out of 4 patents)

5. Pranav Bajoria (4 out of 4 patents)

IDiyas Innovation Intelligence. (2026). Company Patent Portfolio: Cyngn, Inc.. Retrieved from https://idiyas.com/company/cyngn

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

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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