Jia Zhang, Xiamen University

Short Biography

I am currently working towards the Ph.D. degree in the Artificial Intelligence Department of Xiamen University (XMU), supervised by Prof. Shaozi Li. During the period of doctoral study, I visited Kay Chen Tan’s group in the City University of Hong Kong for three months.

Email: zhangjia_gl@163.com or j.zhang@stu.xmu.edu.cn

Mailing Address: #304, Scientific Research Building, Haiyun Campus, Xiamen, P.R. China, 361005

What’s Happening

Research Interests

I am interested in machine learning and data mining. In particular, I am interested in classification (multi-label learning, weakly supervised learning, class-imbalance learning), feature selection and sparse learning, deep learning, data fusion, and recommendation systems. I am also interested in various data mining applications in medicine, such as TCM health management, drug discovery, hospital readmission, and autism spectrum disorder.

Selected Publications

  1. Jia Zhang, Zhiming Luo, Candong Li, Changen Zhou, Shaozi Li*. Manifold regularized discriminative feature selection for multi-label learning. Pattern Recognition, 2019, 95: 136-150. [code]
  2. Jia Zhang, Candong Li, Zhenqiang Sun, Zhiming Luo, Changen Zhou, Shaozi Li*. Towards a unified multi-source-based optimization framework for multi-label learning. Applied Soft Computing, 2019, 76: 425-435.
  3. Jia Zhang, Candong Li, Donglin Cao, Yaojin Lin, Songzhi Su, Liang Dai, Shaozi Li*. Multi-label learning with label-specific features by resolving label correlations. Knowledge-Based Systems, 2018, 159: 148-157.
  4. Jia Zhang, Candong Li, Yaojin Lin, Youwei Shao, Shaozi Li*. Computational drug repositioning using collaborative filtering via multi-source fusion. Expert Systems with Applications, 2017, 84: 281-289.
  5. Jia Zhang, Yaojin Lin*, Menglei Lin, Jinghua Liu. An effective collaborative filtering algorithm based on user preference clustering. Applied Intelligence, 2016, 45 (2): 230-240.
  6. Jinghua. Liu, Yuwen Li, Wei Weng, Jia Zhang, Baihua Chen, Shunxiang Wu. Feature selection for multi-label learning with streaming label. Neurocomputing, 2020, 387: 268-278.
  7. Yidong Lin, Jinjin Li, Anhui Tan, Jia Zhang. Granular matrix-based knowledge reductions of formal fuzzy contexts. International Journal of Machine Learning and Cybernetics, 2020, 11 (3): 643–656.
  8. Zhenqiang Sun, Jia Zhang, Liang Dai, Candong Li, Changen Zhou, Jiliang Xin, Shaozi Li. Mutual information based multi-label feature selection via constrained convex optimization. Neurocomputing, 2019, 329: 447-456.
  9. Liang Dai, Jia Zhang, Candong Li, Changen Zhou, Shaozi Li. Multi‐label feature selection with application to TCM state identification. Concurrency and Computation: Practice and Experience, 2019, 31 (23): e4634.
  10. Jinghua Liu, Yaojin Lin, Menglei Lin, Shunxiang Wu, Jia Zhang. Feature selection based on quality of information. Neurocomputing, 2017, 225: 11-22.
  11. Yaojin Lin, Qinghua Hu, Jia Zhang, Xindong Wu. Multi-label feature selection with streaming labels. Information Sciences, 2016, 372: 256-275.

Professional Activities

Journal Reviewer: Pattern Recognition, IEEE Transactions on Neural Networks and Learning Systems, Information Sciences, Knowledge-Based Systems