Mingyue Zhang | Artificial Intelligence | Best Researcher Award

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Dr. Mingyue Zhang | Artificial Intelligence | Best Researcher Award

University of South China | China

Dr. Mingyue Zhang, Ph.D., is a dynamic researcher in computer vision, intelligent systems, and human–computer interaction, currently serving in the field of computer science with a focus on gesture recognition and lightweight deep learning models for edge devices. His research integrates advanced computer vision algorithms with human–machine collaboration, emphasizing intelligent gesture recognition for rehabilitation training, embedded AI, and Internet of Things (IoT)-enabled systems. Dr. Zhang has significantly contributed to developing efficient algorithms such as lightweight convolutional neural networks, adaptive Kalman filtering, and multi-sensor fusion frameworks, which enhance real-time performance in gesture estimation, object tracking, and assistive technologies. His innovative work bridges the gap between deep learning theory and practical deployment on embedded systems and mobile platforms. With over 25 publications in high-impact journals indexed in SCI and EI, including IEEE Internet of Things Journal, Expert Systems with Applications, IEEE Access, and Journal of Supercomputing, his research has achieved growing academic recognition. Dr. Zhang’s work has been widely cited across the global impact of his contributions in computer vision and artificial intelligence. His research is currently supported by the Hunan Provincial Department of Science and Technology, focusing on intelligent gesture recognition in rehabilitation. In recognition of his outstanding contributions to scientific innovation and scholarly excellence, Dr. Zhang is honored with the Best Researcher Award for his pioneering advancements in AI-driven human–computer interaction and lightweight network modeling.

Publication Profile

Orcid

Featured Publications

  • Jiang, C., Zhang, M., Wang, Y., & Zhang, A. (2025). AHMOT: Adaptive Kalman Filtering and Hierarchical Data Association for 3D Multi-Object Tracking in IoT-Enabled Autonomous Vehicles. IEEE Internet of Things Journal.

  • Zhang, M., Zhou, Z., Tao, X., & Deng, M. (2023). Hand pose estimation based on fish skeleton CNN: Application in gesture recognition. Journal of Intelligent & Fuzzy Systems, 44, 8029–8042.

  • Zhang, M., Zhou, Z., Wang, T., & Zhou, W. (2023). A lightweight network deployed on ARM devices for hand gesture recognition. IEEE Access, 11, 45493–45503.

  • Zhang, M., Zhou, Z., & Deng, M. (2022). Cascaded hierarchical CNN for 2D hand pose estimation from a single color image. Multimedia Tools and Applications, 81, 25745–25763.

  • Zhang, M., & Zhou, Z. (2025). Speed-accuracy trade-off in lightweight-based hand pose estimation. The Journal of Supercomputing, 81, 1212

Yi Zi Lu | Artificial Intelligence | Best Researcher Award

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Ms. Yi Zi Lu | Artificial Intelligence | Best Researcher Award

Student at Tianjin University of Commerce, China

Ms. Yi Zi Lu is a talented researcher and current Master’s student in Information and Communication Engineering at Tianjin University of Commerce, China. With a Bachelor’s degree in Automation, she has developed a strong academic foundation in Artificial Intelligence, focusing on Natural Language Processing (NLP). Her primary research revolves around deep learning, recommendation systems, and intelligent algorithms. Notably, her study titled “Hybrid News Recommendation Method Based on Title-Content Matching” addresses the challenge of inaccurate user interest modeling in news recommendation systems. By utilizing innovative techniques such as interactive attention networks and Siamese Neural Networks, her research enhances recommendation accuracy, showcasing her ability to tackle complex problems with creative solutions.

 

📝professional profile

ORCID

🎓Educational Details:

Ms. Yi Zi Lu holds a Bachelor’s degree in Automation from Tianjin University of Commerce, China, and is currently pursuing a Master’s degree in Information and Communication Engineering at the same institution. Her specialization in Artificial Intelligence, particularly in Natural Language Processing, showcases her strong academic foundation and focus on cutting-edge technologies.

👨‍🏫Innovation and Extension Activities:

Ms. Lu’s research is innovative, combining neural collaborative filtering and factorization machines to tackle the challenges of title-content mismatching. This approach highlights her ability to think creatively and develop solutions with practical applications. Her work has the potential to influence the development of more accurate and user-centric recommendation systems, indicating her commitment to advancing technology in her field.

Recognition and Professional Impact:

Although Ms. Lu is still a student, her contributions to the field of Artificial Intelligence are noteworthy. Her research has been published in reputable journals, and her involvement in cutting-edge projects positions her as a promising researcher. With a focus on deep learning and AI, her work is aligned with current technological trends, making her a valuable asset to the research community.

Research :

Ms. Lu has a solid research portfolio with a focus on deep learning, recommendation systems, and intelligent algorithms. Her notable research, titled “Hybrid News Recommendation Method Based on Title-Content Matching,” addresses critical issues in news recommendation systems. The study enhances user interest modeling by utilizing an interactive attention network and Siamese Neural Network, resulting in improved recommendation performance. This research has been validated through experiments and published in peer-reviewed journals, demonstrating her ability to contribute to the academic community.

Conclusion:

Ms. Yi Zi Lu’s academic background, research contributions, and innovative approach make her a strong candidate for the Best Researcher Award. Her work in Artificial Intelligence and Natural Language Processing, particularly in developing advanced recommendation systems, demonstrates her potential to make significant contributions to the field. While she is still early in her career, her achievements thus far suggest a promising future, making her deserving of recognition through this award.

📚Publications to Noted

The publication titled “A Hybrid News Recommendation Approach Based on Title–Content Matching” was published in the journal Mathematics in July 2024. The article’s DOI is 10.3390/math12132125. The authors of this publication are:

Shuhao Jiang

Yizi Lu

Haoran Song

Zihong Lu

Yong Zhang​