郑云飞，西南大学电子信息工程学院讲师。2021年9月博士毕业于西安交通大学控制科学与工程专业，随后加入西南大学从事鲁棒机器学习与自适应信号处理方面的基础理论与应用研究工作。近年来，主持/参与国家自然科学基金项目5项、省部级科研项目3项、西南大学校级科研项目1项；在IEEE TNNLS、IEEE TSP、IEEE TCAS-II、EAAI、Neural Networks等国际著名SCI期刊上发表论文30余篇；兼职IEEE TNNLS、IEEE TAES、IEEE TCAS-II、ESWA、Pattern Recognition等多个国际刊物的审稿人。

主要科研项目：

1.国家自然科学基金青年基金：基于集成损失函数的鲁棒宽度学习，2024.01-2026.12，主持

2.重庆市自然科学基金面上项目：基于自适应信息论度量准则的鲁棒脑电信号解码研究，2024.07-2027.06，主持

3.重庆博士后研究项目特别资助：基于信息论度量准则的鲁棒宽度学习方法研究，2023.03-2024.09，主持

4.中央高校基本科研业务费科研启动项目：基于轻量化神经网络架构的自适应滤波理论与方法, 2025.05-2028.04，主持

5.国家自然科学基金联合基金项目：云边端一体化服务机器人云脑平台基础理论与关键技术, 2022.01-2025.12, 主研

6.国家自然科学基金面上项目：面向不完备数据的鲁棒自适应滤波器，2025.01-2028.12，主研

7.国家自然科学基金面上项目：多核互相关熵学习理论与方法, 2020.01-2023.12, 主研

8.国家自然科学基金面上项目：基于再生核理论的非线性自适应滤波器, 2017.01- 2020.12, 主研

9.陕西省自然科学基础研究计划重点项目：偏差补偿的稀疏互相关熵自适应滤波及其应用, 2019.01-2021.12, 主研

代表性学术论文：

1.Yunfei Zheng, Badong Chen, Shiyuan Wang, and Weiqun Wang. Broad Learning System Based on Maximum Correntropy Criterion. IEEE Transactions on Neural Networks and Learning Systems, 2021, 32 (7), 3083-3097.

2.Yunfei Zheng, Badong Chen, Shiyuan Wang, Weiqun Wang, and Wei Qin. Mixture Correntropy-Based Kernel Extreme Learning Machines. IEEE Transactions on Neural Networks Learning Systems, 2022, 33 (2), 811-825.

3.Badong Chen,Yunfei Zheng, and Pengju Ren. Error Loss Networks. IEEE Transactions on Neural Networks and Learning Systems, 2024, 35(4): 5256-5268.

4.Yunfei Zheng, Shiyuan Wang, and Badong Chen. Quantized Minimum Error Entropy with Fiducial Points for Robust Regression. Neural Networks, 2023, 168, 405-418.

5.Yunfei Zheng, Shiyuan Wang, and Badong Chen. Robust One-Class Classification with Support Vector Data Description and Mixed Exponential Loss Function. Engineering Applications of Artificial Intelligence, 2023, 122, 106153.

6.Yunfei Zheng, Shiyuan Wang, and Badong Chen. Generalized Multikernel Correntropy Based Broad Learning System for Robust Regression. Information Sciences, 2024, 678: 121026.

7.Yunfei Zheng, Shiyuan Wang, and Badong Chen. Multikernel Correntropy Based Robust Least Squares One-Class Support Vector Machine. Neurocomputing, 2023, 545, 126324.

8.Yunfei Zheng, Shiyuan Wang, and Badong Chen. Identification of Hammerstein Systems with Random Fourier Features and Kernel Risk Sensitive Loss. Neural Processing Letters, 2023, 55, 9041-9063.

9.Yunfei Zheng, Shiyuan Wang, Jiuchao Feng, and Chi K. Tse. A Modified Quantized Kernel Least Mean Square Algorithm for Prediction of Chaotic Time Series. Digital Signal Processing, 2016, 48: 130-136.

10.郑云飞, 陈霸东. 基于最小p-范数的宽度学习系统. 模式识别与人工智能，2019, 32 (1): 51-57.

11.Yunfei Zheng, Xuemei Qin, Zhengkai Xi, and Badong Chen. Mixed-Norm Based Broad Learning System for EEG Classification.  41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Berlin, Germany, 2019.7.23-2019.7.27.

12.Yunfei Zheng, Jiyao Dong, Wentao Ma, and Badong Chen. Kernel Adaptive Hammerstein Filter. 26th European Signal Processing Conference (EUSIPCO), Rome, Italy, 2018.09.03-2018.09.07.

13.Shanli Chen, Yunfei Zheng, Dongyuan Lin, Peng Cai, Yingying Xiao, and Shiyuan Wang. MAML-KalmanNet: A Neural Network-Assisted Kalman Filter Based on Model-Agnostic Meta-Learning. IEEE Transactions on Signal Processing, 2025, 73: 988 - 1003

14.Qiangqiang Zhang, Dongyuan Lin, Yingying Xiao, Yunfei Zheng, and Shiyuan Wang. Error Reused Filtered-X Least Mean Square Algorithm for Active Noise Control. IEEE/ACM Transactions on Audio, Speech, and Language Processing, 2023, 32: 397-412.

15.Yingying Xiao, Qiangqiang Zhang, Yunfei Zheng*, Junhui Qian, and Shiyuan Wang*. Clustering-Sparse Nyström Adaptive Filter-Based Nonlinear Distributed Active Noise Control System. IEEE Transactions on Circuits and Systems II: Express Briefs, 2023, 71(5): 2864-2868.