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For the Inventor, By the Inventor

North Bethesda, MD, United States of America

Dong Yang

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This inventor holds 21 USPTO granted patents and 9 published patent applications, primarily in Neural Network Techniques. Top assignee: Nvidia Corporation. Active years: 2021-2026.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Dong Yang. Retrieved from https://idiyas.com/inventor/dong-yang-zfi7gu8j

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

USPTO Granted Patents = 21 

% Patents Active = 95.2

Average Co-Inventor Count = 5.3

ph-index = 2

Forward Citations = 21(Granted Patents)


Company Filing History:

goldMedal21 out of 6,208 
 
Nvidia Corporation
 patents

Years Active: 2021-2026

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Areas of Expertise:
Image Segmentation
Neural Networks
Reinforcement Learning
Machine Learning
Object Detection
Hyperparameter Optimization
Image Annotation
Parameter Estimation
Image Synthesis
Classification Techniques
Training Strategies
Federated Learning
21 patents (USPTO):Explore Patents
1. 12755388 - Image segmentation using one or more neural networks (2026-10-06),
2. 12737588 - Dynamic weight updates for neural networks (2026-09-15),
3. 12694532 - Training strategy search using reinforcement learning (2026-07-28),
4. 12620484 - Machine-learning techniques for oxygen therapy prediction using medical imaging data and clinical metadata (2026-05-05),
5. 12620139 - Neural network-based image segmentation (2026-05-05),
6. 12614062 - Techniques for classification with neural networks (2026-04-28),
7. 12602743 - Image synthesis using one or more neural networks (2026-04-14),
8. 12579655 - Three-dimensional image segmentation using neural networks (2026-03-17),
9. 12573216 - Machine-learning-based object detection system (2026-03-10),
10. 12573029 - Image annotation using one or more neural networks (2026-03-10),
11. 12572778 - Technique to perform neural network architecture search with federated learning (2026-03-10),
12. 12554796 - Optimizing parameter estimation for training neural networks (2026-02-17),
13. 12548312 - Hyperparameter optimization using one or more neural networks (2026-02-10),
14. 12511349 - Technique to perform neural network architecture search (2025-12-30),
15. 12488578 - Neural network training technique (2025-12-02),

Title: The Innovations of Dong Yang

Introduction

Dong Yang is a prominent inventor based in North Bethesda, MD (US). He has made significant contributions to the field of technology, particularly in the area of neural networks. With a total of 21 patents to his name, Yang continues to push the boundaries of innovation.

Latest Patents

Among his latest patents is the invention titled "Object detection using one or more neural networks." This patent describes apparatuses, systems, and techniques to detect objects in images, including digital representations of those objects. In at least one embodiment, one or more objects are detected in an image based, at least in part, on points corresponding to a surface of one or more objects. Another notable patent is the "Pretraining framework for neural networks," which outlines apparatuses, systems, and techniques to indicate the extent to which text corresponds to one or more images. In at least one embodiment, this extent is indicated using one or more neural networks and is used to train those networks.

Career Highlights

Dong Yang is currently employed at Nvidia Corporation, a leading company in the field of graphics processing and artificial intelligence. His work at Nvidia has allowed him to collaborate with some of the brightest minds in the industry.

Collaborations

Some of his notable coworkers include Daguang Xu and Ziyue Xu. Their collaborative efforts contribute to the innovative projects at Nvidia Corporation.

Conclusion

Dong Yang's contributions to the field of neural networks and object detection exemplify the spirit of innovation. His work continues to influence advancements in technology and artificial intelligence.

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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