个人简介

张佳,博士研究生,现就读于厦门大学信息学院人工智能系,师从李绍滋教授。电子邮件:zhangjia_gl@163.com j.zhang@stu.xmu.edu.cn

研究兴趣:机器学习,数据挖掘,人工智能。目前主要关注:弱监督多标记学习,多视图学习,特征选择,医疗人工智能(中医健康管理,药物重定位,再住院预测,神经发育障碍)。

学术经历

2016.09-2020.06:厦门大学—智能科学与技术专业,工学博士。导师:李绍滋教授

2019.05-2019.07:香港城市大学—访问学者。导师:Kay Chen Tan 教授

2013.09-2016.06:闽南师范大学—计算机应用技术专业,工学硕士。导师:林梦雷教授,林耀进教授

项目经历:目前/曾参与国家重点研发计划子课题,国家自然科学基金联合重点项目,国家自然科学基金面上项目,福建省 2011 中医健康管理协同创新中心项目等。

主要成果

在国内外发表科研论文20余篇,其中SCI收录10余篇,EI收录4篇,Google Scholar 他引超过200次,单篇最高他引60次。主要学术成果如下:

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. [code]

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.

主要荣誉

2020年获厦门大学优秀毕业生(博士)

2019年获中华医药博士生创新创业大赛片仔癀特别奖,中国澳门(排名第二)

网站链接

General Information:中国教育和科研计算机网厦门大学图书馆厦门大学信息学院

国际出版物检索:DBLP, 国内出版物检索:软件学报计算机学报中国科学:信息科学计算机研究与发展

CCF推荐期刊/会议列表 【链接

Biography

Jia Zhang is currently working towards the Ph.D. degree from the Artificial Intelligence Department, Xiamen University, Xiamen, China. He received the M.S. degree from the School of Computer Science, Minnan Normal University, Zhangzhou, China, in 2016. He is boardly interested in machine learning, data mining, and artificial intelligence. Now he is working on weak label learning, multi-view learning, feature selection, and some data mining applications in medicine, such as TCM health management, drug discovery, hospital readmission, and autism spectrum disorder. He has published over 20 academic papers in some prestigious journals and conferences, such as Pattern Recognition, Knowledge-Based Systems, Information Sciences, Expert Systems with Applications, and IJCAI. His papers have been cited more than 200 times (Google scholar).

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