Dr. Ming Zhang

Address:

Hubei University  
Wuhan, China

Academic Metrics

Research Interests:

• Machine Learning  
• Deep Learning  
• Natural Language Processing  
• Big Data Analytics  
• Financial Data Modeling  
• Signal Processing  
• Artificial Intelligence Applications  
• Data Mining  
• Computational Intelligence  
• Predictive Modeling

Biography:

Dr. Ming Zhang is currently affiliated with the School of Integrated Circuits at Hubei University, China. He received his PhD from the University of Chinese Academy of Sciences in 2024. His research focuses on machine learning, deep learning, and natural language processing, with applications in finance, hardware security, and signal processing.

He has authored more than 20 peer-reviewed scientific publications in reputed journals, including several as first and corresponding author. His work primarily explores data-driven modeling, intelligent systems, and advanced computational techniques applied across multiple domains.

Dr. Zhang is actively involved in the academic community and has contributed as an editorial board member and reviewer for various international journals and conferences in artificial intelligence, information processing, and computational sciences.

Achievements

• Published 23+ SCI-indexed research articles
• Editorial Board Member of multiple international journals
• Active reviewer for IEEE and SCI-indexed journals
• Contributed to conferences such as IEEE SMC and IEEE IJCNN

Current Research Focus

• Artificial Intelligence for Anomalous Sound Detection
• Natural Language Processing for Multi-document Summarization
• Graph Neural Networks and Deep Learning Models
• Machine Learning Applications in Financial Forecasting
• AI-driven Signal Processing and Hardware Security

Academic Profiles of Dr. Ming Zhang

Explore his academic and professional presence across trusted platforms:

• Hubei University Profile
• GitHub
• Google Scholar

Publications:

Dr. Ming Zhang has a strong research background in artificial intelligence, machine learning, and big data analytics. His work primarily focuses on natural language processing, financial data modeling, and intelligent computational systems. His contributions emphasize data-driven approaches and advanced learning models applied across interdisciplinary domains. The publications below highlight his recent and impactful research in AI-driven data analysis and predictive modeling.

• Zhang, M., Cheng, L., Guan, W., et al. (2025). Towards curriculum learning of multi-document summarization using difficulty-aware mixture-of-experts. Applied Soft Computing, 114088.
• Zhang, M., Lu, J., Yang, J., et al. (2024). From coarse to fine: Enhancing multi-document summarization with multi-granularity relationship-based extractor. Information Processing and Management, 61(3):103696.
• Zhang, M., Li, C., Wan, M., et al. (2024). ROUGE-SEM: Better evaluation of summarization using ROUGE combined with semantics. Expert Systems with Applications, 237:121364.
• Zhang, M., Yang, J., Wan, M., et al. (2022). Predicting long-term stock movements with fused textual features of Chinese research reports. Expert Systems with Applications, 210:118312.
• Yang, J., Zhang, M., Feng, S., et al. (2024). A hierarchical deep model integrating economic facts for stock movement prediction. Engineering Applications of Artificial Intelligence, 133:108320.
• Yang, J., Fang, R., Zhang, M., et al. (2025). Enhancing stock ranking forecasting by modeling returns with heteroscedastic Gaussian Distribution. Physica A: Statistical Mechanics and its Applications, 664:130442.

Last Updated on April 01, 2026