For the Inventor, By the Inventor

Enter assignee name

Boston, MA, United States of America

Perceptive Automata Inc.

USPTO Granted Patents = 24

Trademarks = 2

Forward Citations = 234

Loading Chart...

Loading Chart...

11 inventors (with patents filed for the assignee):

Samuel English Anthony (17 out of 22 patents)

Avery Wagner Faller (11 out of 11 patents)

Kshitij Misra (7 out of 7 patents)

4. Jacob Reinier Maat (4 out of 5 patents)

5. Till S Hartmann (3 out of 3 patents)

6. Jeffrey D Zaremba (2 out of 2 patents)

7. Dylan James Rose (1 out of 1 patent)

8. Kevin W Sylvestre (1 out of 1 patent)

9. Stephen Cope (1 out of 1 patent)

10. Elon Gaffin-Cahn (1 out of 1 patent)

11. Mel McCurrie (1 out of 1 patent)

24 patents: Sort by Forward Citations

1. 12097878 - Generating training data for machine learning based models for autonomous vehicles (2024-09-24),

2. 12012118 - Generating training datasets for training machine learning based models for predicting behavior of traffic entities for navigating autonomous vehicles (2024-06-18),

3. 11993291 - Neural networks for navigation of autonomous vehicles based upon predicted human intents (2024-05-28),

4. 11987272 - System and method of predicting human interaction with vehicles (2024-05-21),

5. 11981352 - System and method of predicting human interaction with vehicles (2024-05-14),

6. 11919545 - Scenario identification for validation and training of machine learning based models for autonomous vehicles (2024-03-05),

7. 11840261 - Ground truth based metrics for evaluation of machine learning based models for predicting attributes of traffic entities for navigating autonomous vehicles (2023-12-12),

8. 11772663 - Neural network based modeling and simulation of non-stationary traffic objects for testing and development of autonomous vehicle systems (2023-10-03),

9. 11763163 - Filtering user responses for generating training data for machine learning based models for navigation of autonomous vehicles (2023-09-19),

10. 11753046 - System and method of predicting human interaction with vehicles (2023-09-12),

11. 11733703 - Automatic braking of autonomous vehicles using machine learning based prediction of behavior of a traffic entity (2023-08-22),

12. 11667301 - Symbolic modeling and simulation of non-stationary traffic objects for testing and development of autonomous vehicle systems (2023-06-06),

13. 11615266 - Adaptive sampling of stimuli for training of machine learning based models for predicting hidden context of traffic entities for navigating autonomous vehicles (2023-03-28),

14. 11572083 - Neural network based prediction of hidden context of traffic entities for autonomous vehicles (2023-02-07),

15. 11551030 - Visualizing machine learning predictions of human interaction with vehicles (2023-01-10),

Company Overview

Perceptive Automata Inc., based in Boston, MA, specializes in artificial intelligence solutions aimed at enhancing the safety and efficiency of autonomous vehicles. The company focuses on developing advanced algorithms that enable machines to understand human behavior and predict actions in complex environments. By integrating insights from psychology and machine learning, Perceptive Automata aims to create systems that improve interaction between humans and autonomous technologies, contributing to the future of transportation.

Profile summary synthesized from public USPTO records and patent filings.

Company Badge

USPTO Data Jan 1 1976 - Oct 13 2026

24 Patents

#99 in Boston, MA

#833 in Massachusetts

#13,884 in US

#26,660 in the World

Boston, MA, United States of America

Perceptive Automata Inc.

Forward Citations = 234

11 inventors:

Samuel English Anthony (17 out of 22 patents)

Avery Wagner Faller (11 out of 11 patents)

Kshitij Misra (7 out of 7 patents)

4. Jacob Reinier Maat (4 out of 5 patents)

5. Till S Hartmann (3 out of 3 patents)

IDiyas Innovation Intelligence. (2026). Company Patent Portfolio: Perceptive Automata Inc.. Retrieved from https://idiyas.com/company/perceptive-automata

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]

Loading…