个人简介

陈昆，武汉理工大学信息工程学院副教授，博士生导师，近年一直从事信号处理、人工智能、脑机接口等方面的工作。新西兰奥克兰大学联合培养博士，英国卡迪夫大学博士后。主持湖北省自然科学基金青年基金项目、湖北省自然科学基金联合基金项目等，参与了国家自然科学基金、国家重点研发项目、工信部两机专项等项目。近年来在Neural Networks、Artificial Intelligence in Medicine、Expert Systems with Applications、Journal of Neural Engineering、Biomedical Signal Processing and Control等国际期刊上发表重要学术论文30余篇，授权发明专利11项，获教育部中国高校科研成果奖科技进步奖二等奖1项。

联系方式：kunchen@whut.edu.cn

教育和工作经历

2019-09 至 今, 武汉理工大学, 信息工程学院, 副教授

2018-07 至 2019-04, 英国卡迪夫大学，博士后

2016-11 至 2019-09, 武汉理工大学, 信息工程学院, 讲师

2014-10 至 2016-10, 武汉理工大学，博士后

2010-09 至 2015-01, 武汉理工大学, 信息与通信工程, 博士

2012-09 至 2013-09, 新西兰奥克兰大学, 机械工程，博士联培

2008-09 至 2011-06, 武汉理工大学, 通信与信息系统, 硕士

2004-09 至 2008-06, 武汉理工大学, 电子信息工程, 学士

主要研究方向

信号处理、人工智能、脑机接口

主持或参与的科研项目

[1]科技部重点研发项目，基于离岸导助航设施的沿海航道通航环境长效实时监测技术研究

[2]湖北省自然科学基金联合基金项目，老年人运动平衡的下肢关节力矩调制机制研究

[3]科技部重点研发项目，基于通导融合的星基海上目标实时定位与信息收发技术

[4]湖北省科技厅对外科技合作类项目, 多关节柔性上肢外骨骼康复机器人关键技术研究

[5]工业和信息化部“两机”专项子课题，耐高温光纤传感***

[6]湖北省自然科学基金青年基金项目，基于运动意图解码和情绪反馈的智能脑机交互研究

代表性学术成果

[1]Kun Chen, Zihao Yang, Mincheng Cai, Quan Liu, Qingsong Ai, Li Ma*. A novel biologically plausible spiking convolutional capsule network with optimized batch normalization for EEG-based emotion recognition. Expert Systems with Applications, 2025, 288 (2025), 128183.

[2]Kun Chen, Wenhao Ruan, Quan Liu, Qingsong Ai, Li Ma*. A Novel Deep Learning Model Combining 3DCNN-CapsNet and Hierarchical Attention Mechanism for EEG Emotion Recognition. Neural Networks, 2025, 186 (2025), 107267.

[3]Qingsong Ai, Chenghuan Wang, Kun Chen*, Li Ma. Multi-Source Domain Separation Adversarial Domain Adaptation for EEG Emotion Recognition. Biomedical Signal Processing and Control, 2025, 109, 108016.

[4]Kun Chen, Shulong Chai, Mincheng Cai, Quan Liu, Qingsong Ai, Chiming Zhou, Li Ma*. A novel 3D feature fusion network for EEG emotion recognition. Biomedical Signal Processing and Control, 2025, 102, 107347.

[5]Qingsong Ai, Yuang Liu, Quan Liu, Li Ma, Kun Chen*. Holographic convolutional attention neural network for motor imagery decoding based on EEG temporal-spatial frequency features. Biomedical Signal Processing and Control, 2025, 104, 107526.

[6]Kun Chen, Shulong Chai, Tianli Xie, Quan Liu, Li Ma*. EEG Spatial Inter-Channel Connectivity Analysis: A GCN-Based Dual Stream Approach to distinguish mental fatigue status. Artificial Intelligence In Medicine, 2024, 157, 102996.

[7]Kun Chen, Huchuan Jing, Quan Liu, Qingsong Ai, Li Ma*.A Novel Caps-EEGNet Combined with Channel Selection for EEG-based Emotion Recognition. Biomedical Signal Processing and Control. 2023, 86, 105312.

[8]Kun Chen, Zhiyong Liu, Quan Liu, Qingsong Ai, Li Ma*. EEG-based mental fatigue detection using linear prediction cepstral coefficients and Riemann spatial covariance matrix. Journal of Neural Engineering. 2022, 19(6), 066021.

[9]Kun Chen, Tianli Xie, Li Ma*, Andrew E. Hudson, Qingsong Ai, Quan Liu. A Two-Stream Graph Convolutional Network Based on Brain Connectivity for Anesthetized States Analysis. IEEE Transactions on Neural Systems and Rehabilitation Engineering. 2022, 30, 2077-2087.

[10]Quan Liu, Wenhao Zheng, Kun Chen*, Li Ma, Qingsong Ai. Online Detection of Class-Imbalanced Error-Related Potentials Evoked by Motor Imagery. Journal of Neural Engineering. 2021, 18(4), 046032.

[11]Qingsong Ai, Anqi Chen, Kun Chen*, Quan Liu, Tichao Zhou, Sijin Xin*, Ze Ji. Feature Extraction of Four-Class Motor Imagery EEG Signals Based on Functional Brain Network. Journal of Neural Engineering. 2019, 12(6), 026032.