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張佳，暨南大學信息科學技術學院講師，碩導。于2020年6月獲廈門大學人工智能系博士學位，師從李紹滋教授。博士畢業后，加入暨南大學信息科學技術學院從事教學科研工作。研究方向為機器學習，數據挖掘，智能人機交互。主持國家自然科學基金1項、廣東省面上項目1項，廣州市科技計劃項目1項，并參與了多項國家級/省部級課題研究，包括：國家重點研發計劃子課題，國家自然科學基金聯合基金重點項目，廣東省基礎與應用基礎研究基金重點項目等。在人工智能國際權威期刊：IEEE TCYB、IEEE TNNLS、IEEE TPAMI、PR；腦科學國際權威期刊：IEEE TNSRE、JNE；及國際頂會：IJCAI等發表學術論文50余篇，其中SCI收錄40余篇，ESI高被引論文4篇。據 Google Scholar 統計，論文被引用次數超1400次，第一作者單篇最高引用247次。現為IEEE會員（2023-），CCF專業會員（2020-），CCF人工智能與模式識別專委會委員，CCF協同計算專委會執委；擔任國家自然科學基金評議專家，廣州市科技局入庫專家；擔任TPAMI、TKDE、TCYB、TNNLS、TBD等IEEE匯刊、TKDD、PR、KAIS、INS等國際權威期刊的審稿人，AAAI、IJCNN等國際知名會議的程序委員會委員。

聯系郵箱：jiazhang@jnu.edu.cn

通訊地址: 廣東省廣州市天河區黃埔大道西601號暨南大學（石牌校區）南海樓615室

研究方向是機器學習和數據挖掘。研究側重點是多標記學習、弱標記學習、特征選擇、以及信息融合。本人也對機器學習在人機交互、健康管理、以及生物信息學中的應用感興趣。有志于未來從事相關研究的碩士研究生和保研本科生可與我郵件聯系。

[1] Li, Y., et al. “Consistent and specific multi-view multi-label learning with correlation information.” Information Sciences, 2025, 687: 121395.

[2] Zhang, J., et al. “Toward cross-brain-computer interface: A prototype-supervised adversarial transfer learning approach with multiple sources.” IEEE Transactions on Instrumentation and Measurement, 2024, 73: 1-13.

[3] Zhang, J., et al. “Fast multilabel feature selection via global relevance and redundancy optimization.” IEEE Transactions on Neural Networks and Learning Systems, 2024, 35 (4): 5721-5734.

[4] Du, G., et al. “Semi-supervised imbalanced multi-label classification with label propagation.” Pattern Recognition, 2024, 150: 110358.

[5] Wu, H., et al. “Simplicial complex neural networks.” IEEE Transactions on Pattern Analysis and Machine Intelligence, 2024, 46 (1): 561-575.

[6] Zhang, J., et al. “Group-preserving label-specific feature selection for multi-label learning.” Expert Systems with Applications, 2023, 213: 118861. 

[7] Liu, D., et al. “Multi-source transfer learning for EEG classification based on domain adversarial neural network.” IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2023, 31: 218-228.

[8] Du, G., et al. “Graph-based class-imbalance learning with label enhancement.” IEEE Transactions on Neural Networks and Learning Systems, 2023, 34 (9): 6081-6095.

[9] Zhang, J., et al. “Learning from weakly labeled data based on manifold regularized sparse model.” IEEE Transactions on Cybernetics, 2022, 52 (5): 3841-3854.

[10] Huang, Z.-A., et al. “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.

[11] Zhang, J., et al. “Multi-label feature selection via global relevance and redundancy optimization.” In IJCAI, Yokohama, Japan, 2020, pp. 2512–2518. 

[12] Zhang, J., et al. “Manifold regularized discriminative feature selection for multi-label learning.” Pattern Recognition, 2019, 95: 136-150.

[1] 國家自然科學基金青年科學基金項目: 基于超高維標記與特征數據的多標記分類建模關鍵技術研究 (2022-2024), 62106084, PI

[2] 廣東省自然科學基金面上項目: 融合多模態數據的弱監督多標記分類學習關鍵技術研究 (2022-2024), 2022A1515010468, PI

[1] 人工智能導論（本科課程，暨大通識課），秋季學期，2024

[2] 人工智能原理（本科課程），秋季學期，2021，2022，2023，2024

[3] 軟件系統分析（本科課程），秋季學期，2022，2023，2024

[4] 軟件系統分析實驗（本科課程），秋季學期，2022，2023，2024

[5] 計算機文化（本科課程，英語授課），秋季學期，2021

期刊審稿：

Artificial Intelligence: IEEE Transactions on Pattern Analysis and Machine Intelligence; IEEE Transactions on Cybernetics; IEEE Transactions on Evolutionary Computation; IEEE Transactions on Neural Networks and Learning Systems; IEEE Transactions on Emerging Topics in Computational Intelligence; IEEE Transactions on Artificial Intelligence; Pattern Recognition; Neural Networks…
Data Mining: IEEE Transactions on Knowledge and Data Engineering; ACM Transactions on Knowledge Discovery from Data; Knowledge and Information Systems; IEEE Transactions on Big Data; Information Sciences…
Other Fields: IEEE Transactions on Multimedia; IEEE Transactions on Circuits and Systems for Video Technology; IEEE Journal of Biomedical and Health Informatics; IEEE Transactions on Industrial Informatics…

Program Committee: AAAI；IJCNN...

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 student at the City University of Hong Kong, supervised by Prof. Kay Chen Tan.

My research interests include machine learning and data mining. In particular, I am interested in multi-label learning, weak label learning, feature selection, and information fusion. I am also interested in various machine learning applications in health care, bioinformatics, and brain-computer interactions. I have published over 50 academic papers in some prestigious journals and conferences, such as IEEE Transactions on Cybernetics, IEEE Transactions on Neural Networks and Learning Systems, IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Neural Systems and Rehabilitation Engineering, Pattern Recognition, and IJCAI.