Jia Zhang's Homepage

Short Biography: I am now a lecturer at the College of Information Science and Technology, Jinan University.

I received the Ph.D. degree from the School of Informatics, Xiamen University, Xiamen, China, in 2020, supervised by Prof. Shaozi Li. I was a visiting scholar at City University of Hong Kong, supervised by Prof. Kay Chen Tan. My research interests include machine learning, data mining, and human-computer interaction. I am generally interested in design, analysis, and implementation of algorithms for scientific computing problems.

Email: jiazhang@jnu.edu.cn

Selected Publications (More Details in Google Scholar Link)

G. Du, J. Zhang, M. Jiang, J. Long, Y. Lin, S. Li, K. C. Tan. Graph-based class-imbalance learning with label enhancement. IEEE Transactions on Neural Networks and Learning Systems (Early Access), 2021.
J. Zhang, S. Li, M. Jiang, K. C. Tan. Learning from weakly labeled data based on manifold regularized sparse model. IEEE Transactions on Cybernetics (Early Access), 2020. [code]
Z.-A. Huang, J. Zhang, Z. Zhu, E. Q. Wu, K. C. Tan. Identification of autistic risk candidate genes and toxic chemicals via multi-label learning. IEEE Transactions on Neural Networks and Learning Systems, 2021, 32(9): 3971-3984.
G. Du, J. Zhang, F. Ma, M. Zhao, Y. Lin, S. Li. Towards graph-based class-imbalance learning for hospital readmission. Expert Systems with Applications, 2021, 176: 114791.
J. Zhang, Y. Lin, M. Jiang, S. Li, Y. Tang, K. C. Tan. Multi-label feature selection via global relevance and redundancy optimization. In Proceedings of the 29th International Joint Conference on Artificial Intelligence (IJCAI’20), Yokohama, Japan, 2020, pp. 2512–2518. [code] [report] [poster]
J. Zhang, Z. Luo, C. Li, C. Zhou, S. Li. Manifold regularized discriminative feature selection for multi-label learning. Pattern Recognition, 2019, 95: 136-150. [code]
J. Zhang, C. Li, Z. Sun, Z. Luo, C. Zhou, S. Li. Towards a unified multi-source-based optimization framework for multi-label learning. Applied Soft Computing, 2019, 76: 425-435.
J. Zhang, C. Li, D. Cao, Y. Lin, S. Su, L. Dai, S. Li. Multi-label learning with label-specific features by resolving label correlations. Knowledge-Based Systems, 2018, 159: 148-157.
J. Zhang, C. Li, Y. Lin, Y. Shao, S. Li. Computational drug repositioning using collaborative filtering via multi-source fusion. Expert Systems with Applications, 2017, 84: 281-289.
J. Zhang, Y. Lin, M. Lin, J. Liu. An effective collaborative filtering algorithm based on user preference clustering. Applied Intelligence, 2016, 45(2): 230–240.
Y. Lin, Q. Hu, J. Zhang, X. Wu. Multi-label feature selection with streaming labels. Information Sciences, 2016, 372: 256-275.

Teaching Experience

AI Principles (for undergraduate students), Fall, 2021
Computer Fundamentals (for undergraduate students, in English), Fall, 2021

Professional Activities

Journal Reviewer: IEEE Transactions on Knowledge and Data Engineering; IEEE Transactions on Cybernetics; IEEE Transactions on Neural Networks and Learning Systems; Pattern Recognition; Information Sciences; Knowledge-Based Systems; Applied Intelligence
Program Committee: AAAI 2022; IJCNN 2021