m7237com太阳游乐城

　　1999.09-2003.06 m7237com太阳游乐城，计算机科学与技术，工学学士
　　2003.09-2006.06 m7237com太阳游乐城，计算机应用技术，工学硕士
　　2010.09-2016.06 m7237com太阳游乐城，计算机应用技术，工学博士

　　2006.07-2015.04，m7237com太阳游乐城，讲师
　　2015.05-2020.12 m7237com太阳游乐城 副教授
　　2021.01- 至今 m7237com太阳游乐城 教授

　　主讲本科生课程：计算机导论、信息安全原理与技术

　　2017年开始招收计算机方向硕士研究生

　　情感智能、机器学习、多模数据融合建模

　　计算机科学方向（学硕/专硕）

主持参与完成的项目：

科技部“973”计划项目1项(项目号2014CB744600)

国家自然科学基金委员会青年基金项目1项(项目号61402211)

甘肃省省青年科技基金计划项目1项(项目号1208RJYA015)

目前在研项目：

科技部重点研发计划项目2项(项目号2019YFA0706200; 2017YFE0111900)

国家自然科学基金委员会面上项目1项（项目号62072219）

发表SCI/EI论文20余篇，近5年主要的SCI/EI论文如下：

[1] Zhang X, Liu J, Shen J, et al. Emotion Recognition From Multimodal Physiological Signals Using a Regularized Deep Fusion of Kernel Machine[J]. IEEE Transactions on Cybernetics, 2020.(IF=10.387，SCI一区)

[2] Zhang X, Lu D, Pan J, et al. Fatigue Detection with Covariance Manifolds of Electroencephalography in Transportation Industry[J]. IEEE Transactions on Industrial Informatics, 2020.(IF=9.112，SCI一区)

[3] Shen J, Zhang X, Huang X, et al. An Optimal Channel Selection for EEG-based Depression Detection via Kernel-Target Alignment[J]. IEEE Journal of Biomedical and Health Informatics, 2020.(IF=4.217，SCI二区)

[4] Zhang X, Pan J, Shen J, et al. Fusing of Electroencephalogram and Eye Movement with Group Sparse Canonical Correlation Analysis for Anxiety Detection[J]. IEEE Transactions on Affective Computing, 2020. (IF=6.288，SCI二区)

[5] Zhang X, Shen J, ud Din Z, et al. Multimodal Depression Detection: Fusion of Electroencephalography and Paralinguistic Behaviors Using a Novel Strategy for Classifier Ensemble[J]. IEEE journal of biomedical and health informatics, 2019, 23(6): 2265-2275.(IF=4.217，SCI二区)

[6] Zhang X, Lu D, Shen J, et al. Spatial-temporal Joint optimization Network on Covariance Manifolds of Electroencephalography for Fatigue Detection[C]//2020 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). IEEE, 2020: 893-900.(CCF B类)

[7] Guo Z, Fu E, Pan J, et al. Anxiety Detection with Nonlinear Group Correlation Fusion of Electroencephalogram and Eye Movement[C]//2020 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). IEEE, 2020: 2596-2602. (CCF B类)

[8] Zhang X, Li J, Hou K, et al. EEG-based depression detection using convolutional neural network with demographic attention mechanism[C]//2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC). IEEE, 2020: 128-133.

[9] Shen J, Zhang X, Hu B, et al. An Improved Empirical Mode Decomposition of Electroencephalogram Signals for Depression Detection[J]. IEEE Transactions on Affective Computing, 2019. (IF=6.288，SCI二区)

[10] Zhang X, Liang W, Ding T, et al. Individual Similarity Guided Transfer Modeling for EEG-based Emotion Recognition[C]//2019 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). IEEE, 2019: 1156-1161.(CCF B类)

[11] Zhang X, Wang Y, Zhao S, et al. Emotion recognition based on electroencephalogram using a multiple instance learning framework[C]//International Conference on Intelligent Computing. Springer, Cham, 2018: 570-578.

[12] Zhang X, Yao Y, Wang M, et al. Normalized mutual information feature selection for electroencephalogram data based on grassberger entropy estimator[C]//2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). IEEE, 2017: 648-652.(CCF B类)

[13] Zhao S, Zhao Q, Zhang X, et al. Wearable EEG-based real-time system for depression monitoring[C]//International Conference on Brain Informatics. Springer, Cham, 2017: 190-201.

[14] Zhang X, Hu B, Ma X, et al. Resting-State Whole-Brain Functional Connectivity Networks for MCI Classification Using L2-Regularized Logistic Regression[J]. IEEE Transactions on Nanobioscience, 2015, 14(2): 237-247. 237-247. (IF=1.927，SCI三区)