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Central China Normal University

USPTO Granted Patents = 29

% Expired Patents = 17.2

EPO Patents = 2

Forward Citations = 71

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74 inventors (with patents filed for the assignee):

Zongkai Yang (13 out of 14 patents)

Zheng Zhong (8 out of 12 patents)

Zhicheng Dai (7 out of 7 patents)

4. Sannyuya Liu (7 out of 7 patents)

5. Di Wu (5 out of 8 patents)

6. Liang Zhao (4 out of 4 patents)

7. Zengzhao Chen (3 out of 3 patents)

8. Lizhi Zhang (3 out of 3 patents)

9. Jianwen Sun (3 out of 3 patents)

10. Jian Xu (3 out of 7 patents)

11. Dejian Liu (3 out of 6 patents)

12. Shengming Wang (3 out of 3 patents)

13. Xiaoliang Zhu (3 out of 3 patents)

14. Hao Peng (2 out of 8 patents)

15. Ke Wu (2 out of 3 patents)

Core Competencies:

Voice Detection

Fatigue Detection

Neural Networks

Teaching Videos

Identity Recognition

Autism Learning

Educational Metaverse

Big Data Analysis

Classroom Behavior

Virtual Learning

Facial Expression Recognition

Water Treatment

29 patents: Sort by Forward Citations

1. 12664998 - Multi-speaker overlapping voice detection method and system thereof (2026-06-23),

2. 12478318 - Non-contact fatigue detection method and system (2025-11-25),

3. 12450473 - Anti-radiation low-latency chip for neural network inference acceleration (2025-10-21),

4. 12400428 - Automatic classification method and system of teaching videos based on different presentation forms (2025-08-26),

5. 12315392 - Training method and system for autism language barrier based on adaptive learning scaffold (2025-05-27),

6. 12310718 - Millimeter-wave (mmWave) radar-based non-contact identity recognition method and system (2025-05-27),

7. 12254784 - Emotional evolution method and terminal for virtual avatar in educational metaverse (2025-03-18),

8. 12254692 - Construction method and system of descriptive model of classroom teaching behavior events (2025-03-18),

9. 12212869 - High-speed CMOS pixel detector (2025-01-28),

10. 12125406 - Semantic reasoning method and terminal for learning target in education metaverse (2024-10-22),

11. 12036021 - Non-contact fatigue detection system and method based on RPPG (2024-07-16),

12. 11967175 - Facial expression recognition method and system combined with attention mechanism (2024-04-23),

13. 11908344 - Three-dimensional (3D) integrated teaching field system based on flipped platform and method for operating same (2024-02-20),

14. 11727915 - Method and terminal for generating simulated voice of virtual teacher (2023-08-15),

15. 11568012 - Method and system for analyzing educational big data on basis of maps (2023-01-31),

Company Overview

Central China Normal University, located in Wuhan, China, is a prominent institution dedicated to higher education and research. It specializes in a wide range of disciplines, including education, science, engineering, and the humanities. The university is known for its commitment to advancing knowledge through innovative research and fostering academic excellence. With a focus on interdisciplinary collaboration, it plays a significant role in the educational landscape of central China, contributing to both local and national development.

Profile summary synthesized from public USPTO records and patent filings.

Company Badge

USPTO Data Jan 1 1976 - Oct 20 2026

29 Patents

#19 in Wuhan

#1,055 in China

#22,570 in the World

Central China Normal University

Forward Citations = 71

74 inventors:

Zongkai Yang (13 out of 14 patents)

Zheng Zhong (8 out of 12 patents)

Zhicheng Dai (7 out of 7 patents)

4. Sannyuya Liu (7 out of 7 patents)

5. Di Wu (5 out of 8 patents)

IDiyas Innovation Intelligence. (2026). Company Patent Portfolio: Central China Normal University. Retrieved from https://idiyas.com/company/central-china-normal-university

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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