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For the Inventor, By the Inventor

Los Altos, CA, United States of America

Jie Li

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This inventor holds 39 USPTO granted patents and 8 published patent applications, primarily in 3D Object Detection. Top assignees: Toyota Research Institute, Inc., Toyota Jidosha Kabushiki Kaisha, Leland Stanford Junior University. Active years: 2005-2026.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Jie Li. Retrieved from https://idiyas.com/inventor/jie-li-en9ja04o

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

USPTO Granted Patents = 39 

% Patents Active = 84.6

Average Co-Inventor Count = 3.6

ph-index = 5

Forward Citations = 74(Granted Patents)


Location History:

  • Ann Arbor, MI (US) (2005 - 2020)
  • Mountain View, CA (US) (2020 - 2023)
  • Los Altos, CA (US) (2021 - 2024)

Company Filing History:

goldMedal38 out of 879 
 
Toyota Research Institute, Inc.
 patents
silverMedal8 out of 38,970 
 
Toyota Jidosha Kabushiki Kaisha
 patents
bronzeMedal3 out of 5,515 
 
Leland Stanford Junior University
 patents
4. 1 out of 2,538 
 
Warner-Lambert Company
 patents
where one patent can have more than one assignee

Years Active: 2005-2026

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Areas of Expertise:
3D Object Detection
Depth Estimation
Multi-Object Tracking
Machine Learning
Semantic Features
Neural Architecture
Panoptic Segmentation
Trajectory Forecasting
Sensor Fusion
Image Segmentation
Ego-Motion Estimation
Adversarial Learning
39 patents (USPTO):Explore Patents
1. 12633144 - System and method for training a multi-view 3D object detection framework (2026-05-19),
2. 12633128 - Systems and methods for target assignment for end-to-end three-dimensional (3D) detection (2026-05-19),
3. 12488477 - Systems and methods for multi-object tracking (2025-12-02),
4. 12469152 - System and method for three-dimensional multi-object tracking (2025-11-11),
5. 12361575 - Depth estimation with sparse range sensor depth and uncertainty projection (2025-07-15),
6. 12307786 - Systems and methods for detecting lanes using a segmented image and semantic context (2025-05-20),
7. 12243325 - Self-calibration for decoration based sensor fusion method (2025-03-04),
8. 12227204 - Systems and methods for detecting roadway lane boundaries (2025-02-18),
9. 12159423 - Multi-camera cost volumes for self-supervised depth estimation (2024-12-03),
10. 12073632 - Structural object detector for hierarchical ontology for traffic light handling (2024-08-27),
11. 12067785 - Evaluation process for a multi-task network (2024-08-20),
12. 12039438 - Systems and methods for trajectory forecasting according to semantic category uncertainty (2024-07-16),
13. 12020489 - Network architecture for monocular depth estimation and object detection (2024-06-25),
14. 12008818 - Systems and methods to train a prediction system for depth perception (2024-06-11),
15. 11967141 - Neural architecture search for fusing multiple networks into one (2024-04-23),

Title: Jie Li: Innovator and Inventor in Sensor Fusion and Lane Detection Technologies

Introduction

Jie Li, based in Los Altos, California, is a prolific inventor with an impressive portfolio of 33 patents. His work primarily revolves around advancements in sensor fusion technologies and roadway detection systems, contributing significantly to the fields of machine learning and automotive safety.

Latest Patents

Among Jie Li's latest inventions is a method for self-calibrating alignment between image data and point cloud data using a machine learning model. This innovative technique involves receiving image data from a vision sensor and point cloud data from a depth sensor. The system implements an electronic control unit that aligns data, detects differences, and adjusts calibration, ultimately outputting a calibrated feature map.

Another significant patent focuses on systems and methods for detecting roadway lane boundaries. This invention includes receiving image data of a roadway section and historical vehicle trajectory data to generate a heatmap. This heatmap serves as supervisory data to train a neural network, which is then used in vehicles to map out roadway lane boundaries, enhancing navigation and driving safety.

Career Highlights

Jie Li has held key positions at prominent institutions, including the Toyota Research Institute and Toyota Jidosha Kabushiki Kaisha. His work in these companies showcases his commitment to pushing the boundaries of automotive technology, especially in the realms of artificial intelligence and sensor applications.

Collaborations

Throughout his career, Jie Li has collaborated with talented individuals like Adrien David Gaidon and Vitor Guizilini. These partnerships have likely contributed to the innovative solutions he has developed, reinforcing the importance of teamwork in technological advancements.

Conclusion

Jie Li stands out as a leading inventor in sensor fusion and lane detection technologies. His 33 patents not only highlight his innovative spirit but also underscore his significant contributions to enhancing the safety and efficiency of automotive systems. As technology continues to evolve, Jie Li's work will likely play a vital role in shaping the future of transportation.

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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