基本情况

2015年9月毕业于西安交通大学获博士学位，博士期间曾赴日本理化学研究所(RIKEN)脑信号处理实验室访学十余个月；2015年10月进入雨燕体育足球直播平台雨燕直播足球官网工作；2025年4月至2026年4月，赴英国伯明翰大学数学系以访问学者身份开展为期一年的学术访问.

本课题组聚焦于数据科学、深度学习及图像反问题中的数学理论与方法研究，研究兴趣包括：（1）数据科学与深度学习，涉及高维矩阵与张量估计、深度展开网络、隐式神经表示与高斯泼溅、概率扩散模型、流匹配模型等；（2）图像反问题中数学模型与算法，如压缩感知与计算成像、图像相位恢复、视频分离、图像处理中优化算法等.

学术博士招生：应用数学（同时欢迎统计与数据科学、 数值优化、人工智能相关方向硕士生报考）

学术硕士招生：应用数学；专业硕士招生：应用统计.  编程要求：Python、Matlab.

代表性学术论文

• 1. Wenfei Cao, Yang Chen, Qibin Zhao, Jinglai Li, Andrzej Cichocki. Exponential-family tensor completion via nonconvex dual total-variation regularization, accepted by IEEE Trans. Signal Process, July, 2026.

• 2. Wenfei Cao, Xicui Peng, Yang Chen, Jiahui Ji. Low tubal-rank tensor recovery with adversarial sparse noises. J. Comput. Appl. Math. 483: 117373 (2026)

• 3. Jiahui Ji, Wendong Wang, Wenfei Cao. Low tubal-rank Poisson tensor recovery via Anscombe transform approximation. J. Comput. Appl. Math. 486: 117705 (2026)

• 4. Shoucheng Yan, Yang Chen, Wenfei Cao, Huibin Li. Enhancing U-Net with low-rank attention skip block for 3D point cloud segmentation. Neurocomputing 626: 129593 (2025)

• 5. Wenfei Cao, Xia Chen, Shoucheng Yan, Zeyue Zhou, Andrzej Cichocki. 1-Bit tensor completion via max-and-nuclear-norm composite optimization. IEEE Trans. Signal Process. 72: 3487-3501 (2024)

• 6. Yongting Zhao, Wenfei Cao, Yang Chen. Local-and-nonlocal spectral prior regularized tensor recovery for Cauchy noise removal. Signal Process. 213: 109176 (2023)

• 7. Yang Chen, Wenfei Cao, Li Pang, Jiangjun Peng, Xiangyong Cao. Hyperspectral image denoising via texture-preserved total variation regularizer. IEEE Trans. Geosci. Remote. Sens. 61: 1-14 (2023)

• 8. Xiangyong Cao, Yang Chen, Wenfei Cao. Proximal PanNet: A model-based deep network for pansharpening. AAAI 2022: 176-184

• 9. Yang Chen, Wenfei Cao, Li Pang, Xiangyong Cao. Hyperspectral image denoising with weighted nonlocal low-rank model and adaptive total variation regularization. IEEE Trans. Geosci. Remote. Sens. 60: 1-15 (2022)

• 10. Jing Yao, Deyu Meng, Qian Zhao, Wenfei Cao, Zongben Xu. Nonconvex-sparsity and nonlocal-smoothness-based blind hyperspectral unmixing. IEEE Trans. Image Process. 28(6): 2991-3006 (2019)

• 11. Wenfei Cao, Jing Yao, Jian Sun, Guodong Han. A tensor-based nonlocal total variation model for multi-channel image recovery. Signal Process. 153: 321-335 (2018)

• 12. Fenghui Wang, Wenfei Cao, Zongben Xu. Convergence of multi-block Bregman ADMM for nonconvex composite problems. Sci. China Inf. Sci., 61(12): 122101:1-12 (2018)

• 13. Wenfei Cao, Kaidong Wang, Guodong Han, Jing Yao, Andrzej Cichocki. A robust PCA approach with noise structure learning and spatial-spectral low-rank modeling for hyperspectral image restoration. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 11(10): 3863-3879 (2018)

• 14. Wenfei Cao, Yi Chang, Guodong Han, Junbing Li. Destriping remote sensing Image via low-rank approximation and nonlocal total variation. IEEE Geosci. Remote. Sens. Lett., 15(6): 848-852 (2018)

• 15. Dong Zeng, Qi Xie, Wenfei Cao, et al. Low-dose dynamic cerebral perfusion computed tomography reconstruction via kronecker-basis-representation tensor sparsity regularization. IEEE Trans. Medical Imaging, 36(12): 2546-2556 (2017)

• 16. Wenfei Cao, Yao Wang, Jian Sun, et al. Total variation regularized tensor RPCA for background subtraction from compressive measurements. IEEE Trans. Image Process., 25(9): 4075-4090 (2016)

• 17. Wenfei Cao, Yao Wang, Can Yang, et al. Folded-concave penalization approaches to tensor completion. Neurocomputing 152: 261-273 (2015)

• 18. Jian Sun, Wenfei Cao, Zongben Xu, Jean Ponce. Learning a convolutional neural network for non-uniform motion blur removal. IEEE Conference on Computer Vision and Pattern Recognition, 2015: 769-777

• 19. Qian Zhao, Deyu Meng, Xu Kong, Qi Xie, Wenfei Cao, et al. A novel sparsity measure for tensor recovery. IEEE International Conference on Computer Vision, 2015: 271-279

• 20. Wenfei Cao, Jian Sun, Zongben Xu. Fast image deconvolution using closed-form thresholding formulas of Lq regularization. J. Vis. Commun. Image Represent., 24(1): 31-41 (2013)

教育科研项目

• 1．基于先验的深度学习模型与算法设计及在高光谱图像上应用研究，中央高校基本科研业务费（项目编号：GK202103001，2020/01-2022/12），结题，主持.
  

• 2．复杂噪声背景下的张量恢复及其在多谱图像数据上应用，陕西省自然科学基础研究计划项目（项目编号：2018JQ1032，2018/01-2019/12），结题，主持.

• 3．基于辅助信息与张量建模的高光谱压缩感知研究，国家自然科学基金青年项目（项目编号：61603235，2017/01-2019/12），结题，主持.

• 4．基于张量结构建模与深度学习的图像相位恢复：数学理论与方法，国家自然科学基金面上项目（项目编号：12271327，2023/01-2026/12），在研，主持.

讲授课程

• 《高等数学》、《多元统计分析》、《机器学习导论》、《稀疏建模与优化》、《Python程序设计及数据分析》等.