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兰州大学信息科学与工程学院导师教师师资介绍简介-张晓炜

本站小编 Free考研考试/2021-07-16

张晓炜
政治面貌中共党员
职称教授、硕士生导师
职务计算机应用技术研究所所长
所在系所计算机应用技术研究所
邮箱zhangxw@lzu.edu.cn
办公地址飞云楼502

学习经历
  1999.09-2003.06 兰州大学信息科学与工程学院,计算机科学与技术,工学学士
  2003.09-2006.06 兰州大学信息科学与工程学院,计算机应用技术,工学硕士
  2010.09-2016.06 兰州大学信息科学与工程学院,计算机应用技术,工学博士

工作经历
  2006.07-2015.04,兰州大学信息科学与工程学院,讲师
  2015.05-2020.12 兰州大学信息科学与工程学院 副教授
  2021.01- 至今 兰州大学信息科学与工程学院 教授

教学情况
  主讲本科生课程:计算机导论、信息安全原理与技术

指导研究生情况
  2017年开始招收计算机方向硕士研究生

研究方向
  情感智能、机器学习、多模数据融合建模

招生专业
  计算机科学方向(学硕/专硕)

项目成果
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**)
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2019YFA**; 2017YFE**)
国家自然科学基金委员会面上项目1项(项目号**)


发表论文及专著
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)


对外合作


荣誉获奖


社会工作


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