About me
Hello! I am a lecturer at the School of Computer Science and Artificial Intelligence, Zhengzhou University of Light Industry. I received my Ph.D. in Software Engineering from Zhengzhou University in 2026, under the supervision of Prof. Yangdong Ye, and also collaborated closely with Prof. Zhen Tian. My research focuses primarily on data mining, with a particular interest in Knowledge Representation Learning (KRL) and its applications. In recent years, I have published many research papers in highly influential journals or conferences, including IEEE Transactions on Image Processing, IEEE Transactions on Systems, Man, and Cybernetics: Systems, IEEE/ACM Transactions on Computational Biology and Bioinformatics, Expert Systems with Applications， Neural Networks， ACM International Conference on Multimedia, International Joint Conferences on Artificial Intelligence, and IEEE International Conference on Bioinformatics and Biomedicine.
Research Interests
Knowledge graphs organize human knowledge using a graph structure, storing facts and expressing semantics through triples composed of entities (nodes) and relations (edges). With deepening applications, knowledge graphs have evolved from traditional graphs recording static facts to temporal knowledge graphs incorporating timestamps, and further to multimodal knowledge graphs integrating multi-source data such as images and text. To support efficient computation, knowledge representation learning maps these symbolic elements to a low-dimensional vector space to preserve structure and semantics. Ultimately, knowledge graphs combined with representation learning demonstrate powerful application capabilities, widely empowering intelligent search, knowledge recommendation, drug interaction prediction, and providing a knowledge foundation for large language models, becoming a key infrastructure in the AI era.
