学历背景2005.9-2009.7 哈尔滨工业大学 数学系信息与计算科学专业 学士
2009.9-2011.7 哈尔滨工业大学 航天学院控制科学与工程专业 硕士
2011.9-2014.12 哈尔滨工业大学 航天学院控制科学与工程专业 博士
?工作经历2017.1-至今 ?中山大学 地理科学与规划学院 ?副教授/硕导（欢迎对高光谱/高分辨率遥感、湿地遥感、大数据、社交媒体/街景、人工智能/深度学习等方向感兴趣的学生保送与报考研究生）
2015.1-2017.1 ?中山大学地理科学与规划学院讲师
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社会任职IEEE Transactions on Geoscience and Remote Sensing、
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing、
Expert Systems With Applications、
Remote Sensing、
Remote Sensing Letters、
Canadian Journal of Remote Sensing等SCI期刊审稿人
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讲授课程本科生课程：高级程序设计、遥感图像处理、数量地理学、多元统计分析等
?论著专利已经在遥感监测、深度学习、特征提取、模式识别、社交媒体大数据等方面取得了一定的研究成果，发表有关科研论文超过 30 篇，其中 SCI 期刊论文 21 篇（被引 130 次以上）， EI 论文 10 篇，授权发明专利 5 项
近年来与项目相关的代表性SCI论文及专利成果如下：
Li, J., He, Z*., Plaza, J., Li, S., Chen, J., Wu, H., Wang, Y., & Liu, Y. (2017). Social media: new perspectives to improve remote sensing for emergency response. Proceedings of the IEEE, 105(10), 1900-1912.（SCI检索，中科院一区）
He, Z*., & Liu, L. (2016). Robust multitask learning with three-dimensional empirical mode decomposition-based features for hyperspectral classification. ISPRS Journal of Photogrammetry and Remote Sensing, 121, 11-27.（SCI检索，中科院一区）
He, Z*., Liu, H., Wang, Y., & Hu, J. (2017). Generative adversarial networks-based semi-supervised learning for hyperspectral image classification. Remote Sensing, 9(10), 1-27.（SCI检索，中科院二区）
He, Z*., Li, J.*, Liu, K., Liu, L., & Tao, H. (2018) Kernel low-rank multitask learning in variational mode decomposition domain for multi-/hyperspectral classification. IEEE Transactions on Geoscience and Remote Sensing, DOI: 10.1109/TGRS.2018.**. 已录用（SCI检索，中科院二区）
He, Z*., Wang, Y., & Hu, J. (2018). Joint sparse and low-rank multitask learning with Laplacian-like regularization for hyperspectral classification. Remote Sensing. 10(2), 1-22.（SCI检索，中科院二区）
Cao, J., Leng, W., Liu, K*., Liu, L*., He, Z., & Zhu, Y. (2018). Object-based mangrove species classification using Unmanned Aerial Vehicle hyperspectral images and Digital Surface Models. Remote Sensing, 10(1), 1-20.（SCI检索，中科院二区）
He, Z*., Hu, J., & Wang, Y. (2018). Low-rank tensor learning for classification of hyperspectral image with limited labeled samples. Signal Processing, 145, 12-25.（SCI检索，中科院二区）
He, Z*., Li, J., Liu, L., & Shen, Y. (2017). Three-dimensional empirical mode decomposition (TEMD): A fast approach motivated by separable filters. Signal Processing, 131, 307-319.（SCI检索，中科院二区）
Zhu, Y., Liu, K*., Liu, L*., Myint, S. W., Wang, S., Liu, H., & He, Z. (2017). Exploring the potential of WorldView-2 red-edge band-based vegetation indices for estimation of mangrove leaf area index with machine learning algorithms. Remote Sensing, 9(10), 1-20.（SCI检索，中科院二区）
He, Z*., Li, J., Liu, L., Liu, K., & Zhuo, L. (2016). Fast three-dimensional empirical mode decomposition of hyperspectral Images for class-oriented multitask learning. IEEE Transactions on Geoscience and Remote Sensing, 54(11), 6625-6643.（SCI检索，中科院二区）
He, Z*., Liu, L., Zhou, S., & Shen, Y. (2016). Learning group-based sparse and low-rank representation for hyperspectral image classification. Pattern Recognition, 60, 1041-1056.（SCI检索，中科院二区）
He, Z*., Liu, L., Deng, R., & Shen, Y. (2016). Low-rank group inspired dictionary learning for hyperspectral image classification. Signal Processing, 120, 209-221.（SCI检索，中科院二区）
He, Z*., Li, J., & Liu, L. (2016). Tensor block-sparsity based representation for spectral-spatial hyperspectral image classification. Remote Sensing, 8(8), 1-21.（SCI检索，中科院二区）
He, Z*., & Li, J. (2015). Multiple data-dependent kernel for classification of hyperspectral images. Expert Systems with Applications, 42(3), 1118-1135.（SCI检索，中科院二区）
He, Z*., Shen, Y., Li, J., & Wang, Y. (2015). Regularized multivariable grey model for stable grey coefficients estimation. Expert Systems with Applications, 42(4), 1806-1815.（SCI检索，中科院二区）
He, Z*., Wang, Q., Shen, Y., & Sun, M. (2014). Kernel sparse multitask learning for hyperspectral image classification with empirical mode decomposition and morphological wavelet-based features. IEEE Transactions on Geoscience and Remote Sensing, 52(8), 5150-5163.（SCI检索，中科院二区）
He, Z*., Shen, Y., Wang, Q., & Wang, Y. (2014). Optimized ensemble EMD-based spectral features for hyperspectral image classification. IEEE Transactions on Instrumentation and Measurement, 63(5), 1041-1056.（SCI检索，中科院三区）
He, Z*., Wang, Q., Shen, Y., Jin, J., & Wang, Y. (2013). Multivariate gray model-based BEMD for hyperspectral image classification. IEEE Transactions on Instrumentation and Measurement, 62(5), 889-904.（SCI检索，中科院三区）
He, Z., Wang, Q., Shen, Y*., & Wang, Y. (2013). Discrete multivariate gray model based boundary extension for bi-dimensional empirical mode decomposition. Signal Processing, 93(1), 124-138.（SCI检索，中科院二区）
He, Z., Shen, Y*., & Wang, Q. (2012). Boundary extension for Hilbert–Huang transform inspired by gray prediction model. Signal Processing, 92(3), 685-697.（SCI检索，中科院二区）
He, Z., Shen, Y*., Wang, Q., Wang, Y., Feng, N., & Ma, L. (2012). Mitigating end effects of EMD using non-equidistance grey model. Journal of Systems Engineering and Electronics, 23(4), 603-611.（SCI检索，中科院四区）
授权发明专利：沈毅，贺智，张淼，金晶，基于复化Simpson公式改进多变量灰色模型的故障预测方法（专利号：ZL7.2）
授权发明专利：沈毅，贺智，张淼，基于特征扩展和模糊支持向量机的多分组图像分类方法（专利号：ZL3.9）
授权发明专利：沈毅，贺智，金晶，林玉荣，一种采用基于多变量灰色模型的二维经验模态分解提取图像特征的方法（专利号：ZL8.4）
授权发明专利：沈毅，贺智，张淼，基于二维经验模态分解和小波降噪的多分组图像分类方法（专利号：ZL7.3）
授权发明专利：沈毅，贺智，张淼，一种基于二维经验模态分解的多分组图像分类方法（专利号：ZL6.9）
?科研项目1、主持国家自然科学青年基金项目（**）
基于三维经验模态分解与结构化稀疏表示的高光谱影像精细分类研究及其在红树林中的应用???????? (2016,01~2018,12)
2、主持高校基本科研业务费中山大学青年教师培育项目（16lgpy04）
3、高光谱遥感影像的张量块稀疏表示分类方法研究???????? (2016,01~2018,12)
4、主持2016年度遥感青年科技人才创新资助项目????? (2016,1~2016,12)[注：全国仅20人在本年度获此资助]
5、主持中山大学青年教师起步资助项目(37)?? (2015,10~2016,12)
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