学习分析，人工智能，计算机视觉与机器学习

工作经历：
1.2015-06月至今,华中师范大学人工智能教育学部,副教授
2.2018-01月至2018-12月,美国佛罗里达大学,访问学者
3.2015-03月至2017-12月,华中科技大学,博士后
4.2019-07月至2019-09月,澳门大学,访问学者
5.2015-07月至2015-09月,澳门大学,博士后
6.2012-07月至2015-06月,华中师范大学教育信息技术学院,讲师
 
学术兼职：
第23届全球华人计算机教育应用大会子会议主席（学习分析、评估、人工智能教育应用）
第22届全球华人计算机教育应用大会子会议副主席（学习分析、评估、人工智能教育应用）
中国电子学会现代教育技术分会会员
中国自动化学会会员
中国计算机学会会员
International Journal of Image, Graphics and Signal Processing 杂志编委

湖北省教育信息化研究中心副主任

1.魏艳涛，罗洁琳，胡美佳* ，李文昊， 姚璜，基于计算机视觉的在线学习情感识别研究，计算机科学，2021（已接受）.
2.师亚飞,童名文,王建虎,孙佳,戴红斌,魏艳涛.混合同步学习：演进、价值与未来议题[J].电化教育研究,2021,42(12):100-107.
3.Guangrun Xiao，Yantao Wei*，Huang Yao，Wei Deng，Jiazhen Xu，Donghui Pan，Hierarchical broad learning system for hyperspectral image classification，IET Image Processing， 2021. (通讯作者，SCI)
4.韩金辉，魏艳涛*，彭真明，赵骞，陈耀弘，覃尧，李楠，红外弱小目标检测方法综述，红外与激光工程，2021. （通讯作者，EI）
5.Yantao Wei, Shujian Yu, Luis Sanchez Giraldo, José C. Príncipe,Multiscale Principle of Relevant Information for Hyperspectral Image Classification, Machine Learning, 2021.(SCI)
6.Yantao Wei, Yicong Zhou, Spatial-Aware Network for Hyperspectral Image Classification, Remote Sensing, 2021.(SCI)
7.Xinyu Zhang, Yantao Wei*, Huang Yao, Zhijing Ye, Yicong Zhou, Yue Zhao, Locally Homogeneous Covariance Matrix Representation for Hyperspectral Image Classification, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021. (通讯作者，SCI)
8.Feng Xue, Falong Tan, Zhijing Ye, Jiaqing Chen, Yantao Wei, Spectral-Spatial Classification of Hyperspectral Image Using Improved Functional Principal Component Analysis, IEEE Geoscience and Remote Sensing Letters, 2021.(SCI)
9.Zhijing Ye, Jiaqing Chen, Hong Li, Yantao Wei*, Guangrun Xiao, Jón Atli Benediktsson, Supervised functional data discriminant analysis for hyperspectral image classification, IEEE Transactions on Geoscience and Remote Sensing, Vol.58, No.2, pp. 841-851, 2020. (通讯作者，SCI)
10.徐家臻，邓伟，魏艳涛. 基于人体骨架信息提取的学生课堂行为自动识别, 现代教育技术，Vol.30， No.5，pp. 108-113, 2020. (CSSCI)
11.魏艳涛,雷芬,胡美佳,邓伟,姚璜,王志锋.学生表情识别研究综述[J]. 中国教育信息化, 2020(21):48-55.
12.于潇,魏艳涛*,刘怡.学习投入研究进展及展望述[C]. Proceedings of the 25th Global Chinese Conference on Computers in Education (GCCCE 2020).2021, pp.408-416.
13.Huang Yao, Mengting Yang, Tiantian Chen, Yantao Wei*, Yu Zhang, Depth-based human activity recognition via multi-level fused features and fast broad learning system, International Journal of Distributed Sensor Networks, Vol.16, No.2, 2020. (通讯作者，SCI)
14.Ling Zhong, Yantao Wei*, Huang Yao, Wei Deng, Zhifeng Wang, Mingwen Tong，Review of Deep Learning-Based Personalized Learning Recommendation，Proceedings of the 2020 11th International Conference on E-Education, E-Business, E-Management, and E-Learning，pp. 145-149, 2020.
15.Yantao Wei, Shujian Yu, Jose C Principe, Multiscale Principle of Relevant Information for Hyperspectral Image Classification, arXiv preprint arXiv:1907.06022, 2019.
16.魏艳涛，秦道影，胡佳敏，姚璜*，师亚飞，基于深度学习的学生课堂行为识别，现代教育技术，Vol.29， No.7，pp.87-91, 2019. (CSSCI)
17.陈加，张玉麒，宋鹏，魏艳涛*，王煜. 深度学习在基于单幅图像的物体三维重建中的应用，自动化学报，Vol.45, No.4, pp.657-668, 2019.
18.陈甜甜,姚璜,魏艳涛,左明章,杨梦婷.基于融合特征的人体动作识别[J].计算机工程与设计,2019,40(05):1394-1400.
19.Fen Lei, Yantao Wei*, Jiamin Hu, Huang Yao, Wei Deng, Ying Lu, Student Action Recognition Based on Multiple Features, 2019 International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData), pp.428-432, 2019.
20.Yafei Shi, Yantao Wei*, Donghui Pan, Wei Deng, Huang Yao, Tiantian Chen, Gang Zhao, Mingwen Tong and Qingtang Liu，Student body gesture recognition based on Fisher broad learning system, International Journal of Wavelets, Multiresolution and Information Processing，Vol. 17, No. 1, 1950001,2019.
21.Shujian Yu, Zubin Abraham, Heng Wang, Mohak Shah, Yantao Wei, José C.Príncipe. Concept drift detection and adaptation with hierarchical hypothesis testing, Journal of the Franklin Institute, Vol. 356, No. 5, pp. 3187-3215, 2019.
22.陈甜甜，姚璜，魏艳涛，左明章，杨梦婷，基于融合特征的人体动作识别，计算机工程与设计，pp. 1394-1400，2019.
23.Yafei Shi,Yantao Wei*, Huang Yao, Donghui Pan, Guangrun Xiao, High-Boost-Based Multiscale Local Contrast Measure for Infrared Small Target Detection, IEEE Geoscience and Remote Sensing Letters 15 (1), 33-37, 2018 (通讯作者，SCI)
24.Donghui Pan,Yantao Wei, Houzhang Fang, Wenzhi Yang, A reliability estimation approach via Wiener degradation model with measurement errors, Applied Mathematics and Computation, Vol.320, pp. 131–141, 2018. (SCI)
25.Jinyan Nie, Shaocheng Qu,Yantao Wei,Liming Zhang, Lizhen Deng, An infrared small target detection method based on multiscale local homogeneity measure, Infrared Physics & Technology 90, 186-194, 2018. (SCI)
26.Yantao Wei, Peng Zhang, Huang Yao, Jiazhen Xu and Xinge You, Stacked Kernel Extreme Learning Machine for Hyperspectral Image Classification, International Conference on Pattern Recognition and Artificial Intelligence, 2018.
27.秦道影， 师亚飞，魏艳涛* , 学习分析研究进展, 全球华人计算机教育应用大会, 2018.5.25-2018.5.29.
28.Yantao Wei,Yicong Zhou, Hong Li, Spectral-spatial response for hyperspectral image classification, Remote Sensing, Vol. 9, no. 3, pp.203:1-31, 2017. (SCI)
29.Yafei Shi，Yantao Wei，Ting Wu，Qingtang Liu，Statistical graph classification in intelligent mathematics problem solving system for high school student，2017 12th International Conference on Computer Science and Education (ICCSE), pp.645-650, 2017.（通讯作者，EI）
30.Yantao Wei,Yafei Shi, Huang Yao, Gang Zhao and Qingtang Liu, High School Statistical Graph Classification Using Hierarchical Model for Intelligent Mathematics Problem Solving, The Pacific-Rim Symposium on Image and Video Technology (PSIVT), 2017.（EI）
31.聂进焱，魏艳涛，瞿少成. 一种面向局部神经反应的模板选取算法，计算机工程，Vol.43， No.3, pp. 277-281, 2017.
32.Yantao Wei, Xinge You, Hong Li, Multiscale Patch-based Contrast Measure for Small Infrared Target Detection, Pattern Recognition, Vol. 58, pp. 216–226, 2016.(SCI, ESI 高被引)
33.Yicong Zhou,Yantao Wei*, Learning Hierarchical Spectral-Spatial Features for Hyperspectral Image Classification, IEEE Transactions on Cybernetics, Vol. 46, pp. 1667-1678, 2016. (通讯作者，SCI,中科院1区，TOP期刊)
34.Yantao Wei, Xinge You, He Deng, Small Infrared Target Detection Based on Image Patch Ordering, International Journal of Wavelets, Multiresolution and Information Processing, vol. 14, no. 2, pp. 1-14, 2016. (SCI)
35.Lizhen Deng, Hu Zhu, Chao Tao, andYantao Wei, Infrared Moving Point Target Detection Based on Spatial-temporal Local Contrast Filter, Infrared Physics & Technology vol. 76, pp. 168-173, 2016. (SCI)
36.Yantao Wei*,Yicong Zhou，Stacked Tensor Subspace Learning for hyperspectral image classification. The 2016 International Joint Conference on Neural Networks, pp. 1985-1992, 2016
37.Yantao Wei，Guangrun Xiao，He Deng， Hong Chen, Mingwen Tong，Gang，Zhao, Qingtang Liu，Hyperspectral Image Classification Using FPCA-based Kernel Extreme Learning Machine，Optik - International Journal for Light and Electron Optics，vol. 126, no. 23, pp. 3942–3948, 2015. (SCI)
38.Yuan Yan Tang, Tian Xia,Yantao Wei*, Hong Li, and Luoqing Li, Hierarchical kernel-based rotation and scale invariant similarity, Pattern Recognition, 47(4), pp. 1674–1688, 2014. (通讯作者，SCI)
39.C. L. Philip Chen，Hong Li，Yantao Wei, Tian Xia, and Yuan Yan Tang, A local contrast method for small infrared target detection, IEEE Transactions on Geoscience and Remote Sensing, 52(1), pp. 574 - 581, 2014. (SCI)
40.He Deng,Yantao Wei*,Gang Zhao, Qingtang Liu, Integration of local information-based transition region extraction and thresholding, Infrared Physics & Technology, 66, pp. 103 - 113, 2014. (通讯作者，SCI）
41.Hong Li, Hongfeng Li,Yantao Wei, Yuan Yan Tang, Qiong Wang: Sparse-based neural response for image classification. Neurocomputing 144: 198-207 (2014)
42.Hong Li,Yantao Wei, Luoqing Li, and C. L. Philip Chen, Hierarchical feature extraction with local neural response for image recognition, IEEE Transactions on Cybernetics, 43(2), pp. 412 - 424, 2013.(SCI)
43.He Deng,Yantao Wei, Mingwen Tong, Small Target Detection Based on Weighted Self-information Map, Infrared Physics & Technology, vol.60, pp. 197-206, 2013. (SCI)
44.He Deng,Yantao Wei, and Mingwen Tong. Background suppression of small target image based on fast local reverse entropy operator, IET Computer Vision, Vol. 7, no. 5, pp. 405 - 413, 2013. (SCI)
45.邓鹤，魏艳涛，童名文，瞿少成. 基于改进的局部反熵算子的小目标检测, 通信学报, Vol. 34, pp. 60-69, 2013.
46.Hong Li,Yantao Wei, Luoqing Li, and Yuan Yuan, Similarity learning for object recognition based on derived kernel, Neurocomputing, 83(15), pp. 110-120, 2012. (SCI)

1.基于记忆的不变图像特征学习方法研究，国家自然科学基金青年项目，2016.1-2018.12，主持
2.基于人工智能的在线学习参与度识别研究，教育部人文社科项目，2020.1-2022.12，主持
3.多模态在线学习情感识别与分析，中央高校基本科研业务费青年团队项目，2020.1-2022.12，主持
4.基于I理论的深度学习方法研究，湖北省自然科学基金项目，2018.1-2019.12，主持
5.面向高光谱图像分类的深度学习方法研究，中国博士后科学基金，2015.10-2017.10，主持5.
6.面向空谱特征学习的深度极限学习方法研究，中央高校基本科研业务费项目，2016.1-2017.12，主持
7.面向图像分类的深度学习方法研究，中央高校基本科研业务费项目，2014.1-2015.12，主持
8.超分辨率中的矩阵值算子学习问题，国家自然科学基金委，2015.1-2018.12，主要成员
9.初等数学问题求解关键技术及系统，863计划子课题，2015.1-2017.12，主要成员
 

1.2021年指导学生获Iteach大赛一等奖两项；
2.2021年指导学生获校优秀硕士学位论文；
3.2020年指导学生获校优秀硕士学位论文；
4.2019年指导学生获校优秀硕士学位论文；
5.2016年指导学生获湖北省优秀学士论文；
6.2015年指导学生获湖北省优秀学士论文；
7.2015年指导学生参加全国计算机设计大赛获得三等奖。