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For the Inventor, By the Inventor

San Carlos, CA, United States of America

Seyed Mohammad Khansari Zadeh

This inventor holds 17 USPTO granted patents and 5 published patent applications and 9 EPO patents, primarily in Robotic Control Policies. Top assignees: Google Inc., X Development LLC. Active years: 2019-2026.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Seyed Mohammad Khansari Zadeh. Retrieved from https://idiyas.com/inventor/seyed-mohammad-khansari-zadeh

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

Calculating rank
USPTO Granted Patents = 17 

% Patents Active = 94.1

 

Average Co-Inventor Count = 2.6

ph-index = 3

Forward Citations = 26(Granted Patents)


Location History:

  • Mountain View, CA (US) (2019 - 2023)
  • San Carlos, CA (US) (2020 - 2024)

Company Filing History:

goldMedal11 out of 34,018 
 
Google Inc.
 patents
silverMedal6 out of 1,228 
 
X Development LLC
 patents

Years Active: 2019-2026

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Areas of Expertise:
Robotic Manipulation
Imitation Learning
Meta-Learning
Vision-Based Robotics
Deep Neural Networks
Robotic Grasping
3D Representations
Kinesthetic Teaching
Action Image
Reinforcement Learning
17 patents (USPTO):Explore Patents
1. 12766734 - Determining environment-conditioned action sequences for robotic tasks (2026-10-20),
2. 12498677 - Mitigating reality gap through training a simulation-to-real model using a vision-based robot task model (2025-12-16),
3. 12226920 - System(s) and method(s) of using imitation learning in training and refining robotic control policies (2025-02-18),
4. 12134199 - Determining environment-conditioned action sequences for robotic tasks (2024-11-05),
5. 12112494 - Robotic manipulation using domain-invariant 3D representations predicted from 2.5D vision data (2024-10-08),
6. 12083678 - Efficient adaption of robot control policy for new task using meta-learning based on meta-imitation learning and meta-reinforcement learning (2024-09-10),
7. 11887363 - Training a deep neural network model to generate rich object-centric embeddings of robotic vision data (2024-01-30),
8. 11872699 - Generating a robot control policy from demonstrations collected via kinesthetic teaching of a robot (2024-01-16),
9. 11772272 - System(s) and method(s) of using imitation learning in training and refining robotic control policies (2023-10-03),
10. 11607807 - Machine learning methods and apparatus for automated robotic placement of secured object in appropriate location (2023-03-21),
11. 11607802 - Robotic control using action image(s) and critic network (2023-03-21),
12. 11554485 - Generating a robot control policy from demonstrations collected via kinesthetic teaching of a robot (2023-01-17),
13. 11554483 - Robotic grasping prediction using neural networks and geometry aware object representation (2023-01-17),
14. 11007642 - Machine learning methods and apparatus for automated robotic placement of secured object in appropriate location (2021-05-18),
15. 10864631 - Robotic grasping prediction using neural networks and geometry aware object representation (2020-12-15),

Title: Seyed Mohammad Khansari Zadeh: Innovator in Robotic Control Policies

Introduction

Seyed Mohammad Khansari Zadeh is a prominent inventor based in San Carlos, California. He has made significant contributions to the field of robotics, particularly in the area of robotic control policies. With a total of 15 patents to his name, his work focuses on enhancing the capabilities of robots through advanced learning techniques.

Latest Patents

Among his latest patents, one notable invention is a system and method for using imitation learning in training and refining robotic control policies. This innovation involves training robotic control policies based on human demonstrations of various tasks. The system allows for refinement through human interventions during task performance. Additionally, it can determine potential failures in task execution and prompt human intervention when necessary. Another significant patent involves determining environment-conditioned action sequences for robotic tasks. This invention utilizes a machine learning model to predict a set of actions and their specific order for robots to complete tasks effectively.

Career Highlights

Seyed has worked with leading companies in the tech industry, including Google Inc. and X Development LLC. His experience in these organizations has allowed him to develop and refine his innovative ideas in robotics.

Collaborations

He has collaborated with notable colleagues such as Yunfei Bai and Mrinal Kalakrishnan, contributing to the advancement of robotic technologies.

Conclusion

Seyed Mohammad Khansari Zadeh's work in robotic control policies showcases his innovative spirit and dedication to enhancing robotic capabilities. His contributions are paving the way for future advancements in the field of robotics.

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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