张辉，博士，教授。本硕博均毕业于东南大学。2011-2013年于加拿大温莎大学师从工程院院士Jonathan Wu教授。已发表SCI论文30余篇，其中包括国际权威杂志IEEE TIP，IEEE TNNLS，IEEE TGRS等10余篇，ESI高被引论文两篇。据Google Scholar的不完全统计，所发论文的引用率已达1000余次。主持国家自然基金两项，参与四项。发明专利三项。
Ø 教学及研究方向（主讲课程）
人工智能，计算机视觉，图像处理，开设课程有《人工智能》。
Ø 主持科研项目
1.2016-2019 国家自然科学基金面上项目：基于改进有限混合模型的图像/视频分割算法研究。
2.2012-2014 国家自然科学基金青年项目：对图像模糊和几何变换不变的不变矩研究。
Ø 发表论文
1. Qiang Huang, Yinglei Yu, Tian Wen, Jianwei Zhang, Zhangjing Yang, Fanlong Zhang, Hui Zhang*. Segmentation of Brain MR Image Using Modified Student’s t-Mixture Model, Journal of Medical Imaging and Health Informatics, 2021.
2. Zhangjing Yang#, Hui Zhang#, Danhua Xu, Fanlong Zhang*, Guowei Yang. Double truncated nuclear norm-based matrix decomposition with application to background modeling, Journal of Ambient Intelligence and Humanized Computing, 2018.
3. Yuhui Zheng, Byeungwoo Jeon, Le Sun, Jianwei Zhang and Hui Zhang*, Student’s t-Hidden Markov Model for Unsupervised Learning Using Localized Feature Selection, IEEE Transactions on Circuits and Systems for Video Technology, vol. 28, no. 10, pp. 2586-2598, 2018.
4. Lingcheng Kong, Hui Zhang*, Yuhui Zheng, Yunjie Chen, Jiezhong Zhu and Q. M. Jonathan Wu, Image Segmentation using a Hierarchical Student’s-T Mixture Model, IET Image Processing, vol. 11, no. 11, pp. 1094-1102, 2017.
5. Yuhui Zheng, Xiaozhou Zhou, Byeungwoo Jeon, Jian Shen and Hui Zhang, Multi-scale Patch Prior Learning for Image Denoising Using Student's-t Mixture Model. Journal of Internet Technology, vol. 18, no. 7, pp. 1553-1560, 2017.
6. Yunjie Chen, Hui Zhang, Yuhui Zheng, Byeungwoo Jeon and Q. M. Jonathan Wu, An improved anisotropic hierarchical fuzzy c-means method based on multivariate student t-distribution for brain MRI segmentation, Pattern Recognition, vol. 60, no. 12, pp. 778-792, 2016.
7. Xianye Ben, Peng Zhang, Weixiao Meng, Rui Yan, Mingqiang Yang, Wenhe Liu, Hui Zhang, On the distance metric learning between cross-domain gaits. Neurocomputing, vol. 208, no. 10, pp. 153-164, 2016.
8. Yunjie Chen, Jian Li, Hui Zhang*, Yuhui Zheng, Byeungwoo Jeon and Q. M. Jonathan Wu, Non-local-based spatially constrained hierarchical fuzzy C-means method for brain magnetic resonance imaging segmentation, IET Image Processing, vol. 8, no. 10, pp. 571-581, 2016.
9. Jianwei Zhang, Qiqiong Yu, Yuhui Zheng, Hui Zhang, Jonathan Wu. Regularization parameter selection for TV image denoising using spatially adaptive local spectral response. Journal of Internet Technology. vol. 17 no. 6, pp. 1117-1124, 2016.
10. Thanh Minh Nguyen, Q. M. Jonathan Wu and Hui Zhang, Asymmetric Mixture Model with Simultaneous Feature Selection and Model Detection, IEEE Transaction on Neural Networks and Learning Systems, vol. 26, no. 2, pp. 400-408, 2015.
11. Hui Zhang, Tian Wen, Yuhui Zheng, Danhua Xu, Dingcheng Wang, Thanh Minh Nguyen and Q. M. Jonathan Wu, Two Fast and Robust Modified Gaussian Mixture Models Incorporating Local Information for Image Segmentation, Journal of Signal Processing Systems, vol. 81, no. 1, pp. 45-58, 2015.
12. Yuhui Zheng, Byeungwoo Jeon, Danhua Xu, Q. M. Jonathan Wu and Hui Zhang*, Image Segmentation by Generalized Hierarchical Fuzzy C-Means Algorithm, Journal of Intelligent and Fuzzy Systems, vol. 28, no. 2, pp. 961-973, 2015.
13. Hui Zhang, Q. M. Jonathan Wu, Thanh Minh Nguyen and Xingmin Sun, Synthetic Aperture Radar Image Segmentation by Modified Student’s t-Mixture Model, IEEE Transaction on Geoscience and Remote Sensing, vol. 52, no. 7, pp. 4391-4403, 2014.
14. Thanh Minh Nguyen, Q. M. Jonathan Wu and Hui Zhang, Bounded Generalized Gaussian Mixture Model, Pattern Recognition, vol. 47, no. 9, pp. 3132-3142, 2014.
15. Hui Zhang, Q. M. Jonathan Wu, Yuhui Zheng, Thanh Minh Nguyen and Dingcheng Wang, Effective Fuzzy Clustering Algorithm with Bayesian Model and Mean Template for Image Segmentation, IET Image Processing, vol. 8, no. 10, pp. 571-581, 2014.
16. Hui Zhang, Q. M. Jonathan Wu and Thanh Minh Nguyen, Image Segmentation by Dirichlet Process Mixture Model with Generalized Mean, IET Image Processing, vol. 8, no. 2, pp. 103-111, 2014.
17. Xiubin Dai, Hui Zhang, Tianliang Liu, Huazhong Shu and Limin Luo, Legendre moment invariants to blur and affine transformation and their use in image recognition, Pattern Analysis & Applications, vol. 17, no. 2, pp. 311-326, 2014.
18. Thanh Minh Nguyen, Q. M. Jonathan Wu, Dibyendu Mukherjee and Hui Zhang, A Bayesian Bounded Asymmetric Mixture Model with Segmentation Application, IEEE Journal of Biomedical and Health Informatics, vol. 18, no. 1, pp. 109-119, 2014.
19. Hui Zhang, Q. M. Jonathan Wu and Thanh Minh Nguyen, Incorporating Mean Template into Finite Mixture Model for Image Segmentation, IEEE Transaction on Neural Networks and Learning Systems, vol. 24, no. 2, pp. 328-335, 2013.
20. Hui Zhang, Q. M. Jonathan Wu and Thanh Minh Nguyen, A Robust Fuzzy Algorithm based on Student's t-distribution and Mean Template for Image Segmentation Application, IEEE Signal Processing Letters, vol. 20, no. 2, pp. 117-120, 2013.
21. Thanh Minh Nguyen, Q. M. Jonathan Wu, Dibyendu Mukherjee and Hui Zhang, A Finite Mixture Model for Detail-Preserving Image Segmentation, Signal Processing, vol. 93, no. 11, pp. 3171-3181, 2013.
22. Hui Zhang, Q. M. Jonathan Wu and Thanh Minh Nguyen, Image Segmentation by a New Weighted Student’s t-Mixture Model, IET Image Processing, vol. 7, no. 3, pp. 240-251, 2013.
23. Hui Zhang, Q. M. Jonathan Wu and Thanh Minh Nguyen, Modified Student’s t-Hidden Markov Model for Pattern Recognition and Classification, IET Signal Processing, vol. 7, no. 3, pp. 219-227, 2013.
24. Hui Zhang, Q. M. Jonathan Wu and Thanh Minh Nguyen, Variational Bayes and Localized Feature Selection for Student’s t-Mixture Models, International Journal of Pattern Recognition and Artificial Intelligence, vol. 27, no. 6, pp. 1-18, 2013.
25. Beijing Chen, Huazhong Shu, Hui Zhang, Gang Chen, Christine Toumoulin, Jean Louis Dillenseger, Limin Luo, Quaternion Zernike Moments and Their RST Invariants of Color Images, Signal Processing, vol. 92, no. 2, pp. 308-318, 2012.
26. Hui Zhang, Huazhong Shu, Gouenou Coatrieux, Jie Zhu, Q. M. Jonathan Wu, Yue Zhang, Hongqing Zhu and Limin Luo, Affine Legendre Moment Invariants for Image Watermarking Robust to Geometric Distortions, IEEE Transaction on Image Processing, vol. 20, no. 8, pp. 2189-2199, 2011.
27. Beijing Cheng, Huazhong Shu, Hui Zhang, Gouenou Coatrieux, Limin Luo and Jean Louis Coatrieux, Combined Invariants to Geometric Transformation and to Blur Using Orthogonal Zernike Moments, IEEE Transaction on Image Processing, vol. 20, no. 2, pp. 345-360, 2011.
28. Hongqing Zhu, Min Liu, Yu Li, Huazhong Shu and Hui Zhang, Image description with nonseparable two-dimensional Charlier and Meixner moments, International Journal of Pattern Recognition and Artificial Intelligence, vol. 55, no. 1, pp 37-55, 2011.
29. Hui Zhang, Huazhong Shu, Guoniu Han, Gouenou Coatrieux, Limin Luo and Jean Louis Coatrieux, Blurred Image Recognition by Legendre Moment Invariants, IEEE Transaction on Image Processing, vol. 19, no. 3, pp. 596-611, 2010.
30. Huazhong Shu, Hui Zhang, Beijing Cheng, Pascal Haigron and Limin Luo, Fast Computation of Tchebichef Moments for Binary and Gray-scale Images, IEEE Transaction on Image Processing, vol. 19, no. 12, pp. 3171-3180, 2010.
31. Hui Zhang, Huazhong Shu, Pascal Haigron, Baosong Li and Limin Luo, Construction of a complete set of orthogonal Fourier–Mellin moment invariants for pattern recognition applications, Image and vision computing, vol. 28, no. 1, pp. 38-44, 2010.
32. Hongqing Zhu, Min Liu, Huazhong Shu, Hui Zhang and Limin Luo, General Form for Obtaining Discrete Orthogonal Moments, IET Image Processing, vol. 4, no. 5, pp. 335-352, 2010.
33. Hongqing Zhu, Min Liu, Huazhong Shu, Jing Zhang, Hui Zhang, Representation of videokeratoscopic height data using a set of discrete Tchebichef orthogonal polynomials, International Journal of Signal Processing, Image Processing and Pattern Recognition, vol. 3, no. 3, pp. 13-28, 2010.
Ø 授权发明专利与转让情况
1. 授权发明专利3件（第1发明人，已转让）。
Ø 获人才工程及荣誉称号
1. “创业浦口”人才计划（2020）。
2. “创业南京”英才计划（高层次创业人才引进计划，2020）。
Ø 联系方式
邮箱：67710705@qq.com