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个人简介

分别于1999和2004于南京航空航天大学计算机科学与工程系获学士和博士学位。2004年5月起留校任教,先后任讲师、副教授,并于2008年5月破格晋升为教授。2004年9月至2006年12月在南京大学计算机软件新技术国家重点实验室做在职博士后研究工作。2007年11月至2008年1月和2008年10-12月分别在香港科技大学和澳大利亚Curtin理工大学做短期学术访问。2010-2012年在美国北卡罗莱纳大学教堂山分校从事博士后研究工作。入选科技创新领军人才和青年拔尖人才、国家优秀青年基金资助、国际模式识别协会会士(IAPR Fellow)等。

研究领域

目前主要从事人工智能、机器学习、模式识别、医学图像分析等领域的研究工作。主持国家自然科学基金6项、国家重点研发计划课题1项,另外主持省部级课题和华为等企业合作课题多项。 人工智能,机器学习,模式识别,医学图象分析

近期论文

查看导师最新文章 (温馨提示:请注意重名现象,建议点开原文通过作者单位确认)

Shao W, Peng Y, Zu C, Wang M, and Zhang D. Hypergraph based multi-task feature selection for multimodal classification of Alzheimer's disease. Computerized Medical Imaging and Graphics 80, 101663, 2020 Li W, Liu M, Zhang D. Nyström Subspace Learning for Large-scale SVMs. arXiv preprint arXiv:2002.08937, 2020 Huang J, Zhou L, Wang L and Zhang D. Attention-Diffusion-Bilinear Neural Network for Brain Network Analysis. IEEE Transactions on Medical Imaging, 2020. Hao X, Bao Y, Guo Y, Yu M, Zhang D, Shannon L.R., et al. Multi-modal neuroimaging feature selection with consistent metric constraint for diagnosis of Alzheimer's disease. Medical Image Analysis 60, 101625(3), 2020. Zhu Q, Xu N, Huang S, Qian J and Zhang D. Adaptive feature weighting for robust Lp-norm sparse representation with application to biometric image classification. International Journal of Machine Learning and Cybernetics, 11 (2), 463-474, 2020. Zhu Q, Xu X, Yuan N, Zhang Z, Guan D, Huang SJ, and Zhang D. Latent Correlation Embedded Discriminative Multi-Modal Data Fusion. Signal Processing, 107466(1), 2020. Ma K, Yu J, Shao W, Xu X, Zhang Z, and Zhang D. Functional Overlaps Exist in Neurological and Psychiatric Disorders: A Proof from Brain Network Analysis. Neuroscience, 425, 39-48, 2020 Yousefnezhad M, Selvitella A, Han L, and Zhang D. Supervised Hyperalignment for multi-subject fMRI data alignment.arXiv preprint arXiv:2001.02894, 2020 Liang Sun, Wei Shao, Daoqiang Zhang, Mingxia Liu. Anatomical Attention Guided Deep Networks for ROI Segmentation of Brain MR Images. IEEE Transactions on Medical Imaging, 2019. Jiashuang Huang, Qi Zhu, Mingliang Wang, Luping Zhou, Zhiqiang Zhang, Daoqiang Zhang. Coherent Pattern in Multi-layer Brain Networks: Application to Epilepsy Identification. IEEE Journal of Biomedical and Health Informatics, 2019. Mingliang Wang, Chunfeng Lian, Dongren Yao, Daoqiang Zhang, Mingxia Liu, Dinggang Shen. Spatial-Temporal Dependency Modeling and Network Hub Detection for Functional MRI Analysis via Convolutional-Recurrent Network. IEEE Transactions on Biomedical Engineering, 2019. Liang Sun, Wei Shao, Mingliang Wang, Daoqiang Zhang, Mingxia Liu. High-order Feature Learning for Multi-atlas based Label Fusion: Application to Brain Segmentation with MRI. IEEE Transactions on Image Processing, 2019. Meiling Wang, Wei Shao, Xiaoke Hao, Li Shen, Daoqiang Zhang. Identify Consistent Cross-Modality Imaging Genetic Patterns via Discriminant Sparse Canonical Correlation Analysis. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2019. Liang Sun, Daoqiang Zhang, Chunfeng Lian, Li Wang, Zhengwang Wu, Wei Shao, Weili Lin, Dinggang Shen, Gang Li, UNC/UMN Baby Connectome Project Consortium. Topological correction of infant white matter surfaces using anatomically constrained convolutional neural network. NeuroImage, 2019, 198: 114-124. Qi Zhu, Ning Yuan, Jiashuang Huang, Xiaoke Hao, Daoqiang Zhang. Multi-modal AD classification via self-paced latent correlation analysis. Neurocomputing, 2019, 355: 143-154. Chen Zu, Yue Gao, Brent Munsell, Minjeong Kim, Ziwen Peng, Jessica R Cohen, Daoqiang Zhang, Guorong Wu. Identifying disease-related subnetwork connectome biomarkers by sparse hypergraph learning. Brain imaging and behavior, 2019, 13(4): 879-892. Mingliang Wang, Daoqiang Zhang, Jiashuang Huang, Pew-Thian Yap, Dinggang Shen, Mingxia Liu. Identifying autism spectrum disorder with multi-site fMRI via low-rank domain adaptation. IEEE Transactions on Medical Imaging, 2019. Wei Shao, Zhi Han, Jun Cheng, Liang Cheng, Tongxin Wang, Liang Sun, Zixiao Lu, Jie Zhang, Daoqiang Zhang, Kun Huang. Integrative analysis of pathological images and multi-dimensional genomic data for early-stage cancer prognosis. IEEE transactions on medical imaging, 2019, 39(1): 99-110. Liang Sun, Li Zhang, Daoqiang Zhang. Multi-Atlas Based Methods in Brain MR Image Segmentation. Chinese Medical Sciences Journal 34.2 (2019): 110-119. Meiling Wang, Xiaoke Hao, Jiashuang Huang, Wei Shao, Daoqiang Zhang. Discovering network phenotype between genetic risk factors and disease status via diagnosis-aligned multi-modality regression method in Alzheimer's disease. Bioinformatics, 2019, 35(11): 1948-1957. Liang Sun, Chen Zu, Wei Shao, Junye Guang, Daoqiang Zhang, Mingxia Liu. Reliability-based robust multi-atlas label fusion for brain MRI segmentation. Artificial intelligence in medicine, 2019, 96: 12-24. Mingliang Wang, Xiaoke Hao, Jiashuang Huang, Kangcheng Wang, Li Shen, Xijia Xu, Daoqiang Zhang, Mingxia Liu. Hierarchical Structured Sparse Learning for Schizophrenia Identification. Neuroinformatics, 2019: 1-15. Muhammad Yousefnezhad, Daoqiang Zhang. Multi-Objective Cognitive Model: a Supervised Approach for Multi-subject fMRI Analysis. Neuroinformatics, 2019, 17(2): 197-210. Mingliang Wang, Daoqiang Zhang, Dinggang Shen, Mingxia Liu. Multi-task exclusive relationship learning for Alzheimer's disease progression prediction with longitudinal data. Medical image analysis, 2019, 53: 111-122. Bo Cheng, Mingxia Liu, Daoqiang Zhang, Dinggang Shen, Alzheimer's Disease Neuroimaging Initiative. Robust multi-label transfer feature learning for early diagnosis of Alzheimer's disease. Brain imaging and behavior, 2019, 13(1): 138-153. Wei Shao, Sheng-Jun Huang, MingXia Liu, Daoqiang Zhang. Querying Representative and Informative Super-pixels for Filament Segmentation in Bioimages. IEEE/ACM transactions on computational biology and bioinformatics, 2019.

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