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[11] .Jie Luo, Weigang Cui, Xiao Li, Xiaofeng Liao, Yang Li*,"A Dual-Branch Spatio-Temporal-Spectral Transformer Feature Fusion Network for EEG-based Visual Recognition", IEEE Transactions on Industrial Informatics, 2023, Accepted.(SCI, 影响因子：12.3, JCR: Q1) [Code: https://github.com/ljbuaa/VisualDecoding]
[12] .Minyi Sun, Weigang Cui, Yue Zhang, Shuyue Yu, Xiaofeng Liao, Bin Hu, and Yang Li*. "Attention-Rectified and Texture-Enhanced Cross-Attention Transformer Feature Fusion Network for Facial Expression Recognition", IEEE Transactions on Industrial Informatics, vol. 19, no. 12, pp. 11823 - 11832, 2023. (SCI, 影响因子：12.3, JCR: Q1) [Code: https://github.com/smy17/AR-TE-CATFFNet]
[13] .Minyi Sun, Weigang Cui, Shuyue Yu, Hongbin Han, Bin Hu, Yang Li*."A Dual-Branch Dynamic Graph Convolution based Adaptive Transformer Feature Fusion Network for EEG Emotion Recognition", IEEE Transactions on Affective Computing, vol. 13, no. 4, pp: 2218-2228, 2022. (SCI, 影响因子：11.2, JCR: Q1) [Code: https://github.com/smy17/DANet]
[14] .Yang Li, Yue Zhang*, Jingyu Liu, Kang Wang, Gensheng Zhang*, Kai Zhang, Xiaofeng Liao, Guang Yang. "Global Transformer and Dual Local Attention Network via Deep-Shallow Hierarchical Feature Fusion for Retinal Vessel Segmentation", IEEE Transactions on Cybernetics, vol. 53, no. 9, pp. 5826-5839, 2023. (SCI, 影响因子：11.8, JCR: Q1) [Code: https://github.com/YangLibuaa/GT-DLA-dsHFF]
[15] .Yang Li, Jingyu Liu, Yiqiao Jiang, Yu Liu and Baiying Lei, "Virtual Adversarial Training based Deep Feature Aggregation Network from Dynamic Effective Connectivity for MCI Identification ", IEEE Transactions on Medical Imaging, vol. 41, no. 1, pp: 237-251, 2022. (SCI, 影响因子：10.6, JCR: Q1), [Code: https://github.com/YangLibuaa/gkf-vat-cwGAT]
[16] .Yang Li, Yu Liu, Yuzhu Guo, Xiaofeng Liao, Bin Hu and Tao Yu, "Spatio-Temporal-Spectral Hierarchical Graph Convolutional Network with Semi-Supervised Active Learning for Patient-Specific Seizure Prediction":IEEE Transactions on Cybernetics, vol. 52, no.11, pp. 12189-12204, 2022. (SCI, 影响因子：11.8, JCR: Q1) [Code: https://github.com/YangLibuaa/STS-HGCN-AL]
[17] .Yang Li, Yue Zhang*, Weigang Cui, Baiying Lei, Xihe Kuang, and Teng Zhang, "Dual Encoder-based Dynamic-Channel Graph Convolutional Network with Edge Enhancement for Retinal Vessel Segmentation", IEEE Transactions on Medical Imaging, vol. 41, no. 8, pp.1975-1989, 2022. (SCI, 影响因子：10.6, JCR: Q1), [Code: https://github.com/YangLibuaa/DE-DCGCN-EE].[期刊]
[18] .Weigang Cui（PhD）, Yinyan Wang, Jianxun Ren, Catherine Hubbard, Xiaoxuan Fu, Shengyu Fang, Danhong Wang, Hao Zhang, Yang Li*, Luming Li*, Tao Jiang*, Hesheng Liu*, Personalized fMRI delineates functional regions preserved within brain tumors, Annals of Neurology, vol. 91, no. 3, pp: 353-366, 2022. (SCI, 影响因子：11.2, JCR: Q1)
[19] .Yang Li, Hao Yang, Baiying Lei, Jingyu Liu, Chong-Yaw Wee. "Novel Effective Connectivity Inference Using Ultra-Group Constrained Orthogonal Forward Regression and Elastic Multilayer Perceptron Classifier for MCI Identification." IEEE Transactions on Medical Imaging, vol. 38, no. 5, pp. 1227-1239, 2019. (SCI, 影响因子：10.6, JCR: Q1)
[20] .Yang Li, Jingyu Liu, Zhenyu Tang, Baiying Lei. "Deep Spatial-Temporal Feature Fusion from Adaptive Dynamic Functional Connectivity for MCI Identification." IEEE Transactions on Medical Imaging, vol. 39, no. 9, pp. 2818-2830, 2020. (SCI, 影响因子：10.6, JCR: Q1), [Code: https://github.com/l675451097/Adaptive-Dynamic-Functional-Connectivity]

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