脑与认知神经科学研究中心教师，计算机应用技术工学博士。
chengcheng@lnnu.edu.cn
研究兴趣：
脑电信号分析、情感识别与抑郁检测、多模态、神经网络、脑机接口。
教育经历：
2021.9-2024.12，大连理工大学，计算机科学与技术学院，博士。
学术兼职：
担任中文信息学会情感计算专委会委员，《IEEE Transactions on Neural Networks and Learning Systems》，《IEEE Transactions on Multimedia》，《Neural Networks》，《IEEE Journal of Biomedical and Health Informatics》，《IEEE Transactions on Affective Computing》等期刊审稿人。
主要荣誉与奖励：
2021年3月，辽宁省优秀毕业生；
2022年10月，大连理工大学优秀研究生；
2024年12月，大连理工大学优秀研究生；
2024年12月，博士研究生国家奖学金;
2025年4月，大连市高层次人才。
主持项目：
[1] 国家自然科学基金-青年基金C类项目，在研，主持。
[2] 辽宁省科技厅一般项目，在研，主持。
[3] 辽宁师范大学博士启动科研项目，在研，主持。
[4] 辽宁省博士启动项目，在研，主持。
[5] 辽宁师范大学高端培育项目，在研，主持。
招生信息：
热忱欢迎具有心理学、计算机科学、数学、信号处理等专业背景，对脑电信号分析、认知神经科学等领域感兴趣的青年学子加入我们团队，进行创新实验或攻读学位，共同探索前沿研究！
部分代表作论文：
[1] Lian, T, Tang, M, Zhao, R, Zhang, Y, Zhang, J, Cheng, C, Han, J, Distinct brain network organization in asynchronous and synchronous motor observation and motor imagery: evidence from EEG functional connectivity, phase-amplitude coupling, and decoding, NeuroImage, 2026, 341, 122287.(JCR Q1), DOI: 10.1016/j.neuroimage.2026.122287
[2] Cheng, C, Cheng, Y, Wang, Z, Zhang, Y, Jia, Z, Multi-view cross-modal contrastive representation learning with domain adaptation for multi-modal emotion recognition, Biomedical Signal Processing and Control, 2026, 123, 110501.(JCR Q1), DOI: 10.1016/j.bspc.2026.110501
[3] Cheng, C, Li, H, Zhang, J, Lian, Z, Zhou, X, Jia, Z, Luo, W, EEG Data Augmentation for Depression Detection Using Spatial-Temporal Diffusion Model, IEEE Transactions on Affective Computing, 2026, 1-13.(SCI 1区), DOI: 10.1109/TAFFC.2026.3713110
[4] Cheng, C, Zhang, J, Cheng, Y, Jia, Z, He, W, MS-STGAN: A dual-branch multi-scale spatio-temporal generative adversarial framework for incomplete EEG-based emotion recognition, Neural Networks, 2026, 204, 109203.(JCR Q1), DOI: 10.1016/j.neunet.2026.109203
[5] Feng, L, Huo, Y, Kong, Y, Cheng, C, A dual-branch multiscale model based on Bi-Mamba for EEG emotion recognition, Biomedical Signal Processing and Control, 2026, 117, 109623.(JCR Q1), DOI: 10.1016/j.bspc.2026.109623
[6] Cheng, C, Liu, W, Li, P, Jia, Z, Luo, W, MSDB-Mam: Dual-Branch Mamba Network With Multi-Scale Features for EEG-Based Depression Detection, IEEE Journal of Biomedical and Health Informatics, 2026, 1-12.(SCI 1区), DOI: 10.1109/JBHI.2026.3678034
[7] Cheng, C, Liu, W, Shang, R, Cheng, Y, Jia, Z, Modality-aware fusion with alignment and balancing for robust multimodal emotion recognition, Information Fusion, 2026, 134, 104368.(SCI 1区), DOI: 10.1016/j.inffus.2026.104368
[8] Cheng, C, Shang, R, Wang, Z, Li, H, Jia, Z, MBDA: A modality-balanced framework with data augmentation and alignment for multimodal emotion recognition, Neural Networks, 2026, 201, 108852.(JCR Q1), DOI: 10.1016/j.neunet.2026.108852
[9] Cheng, C, Li, S, Yang, Y, Wu, C, Si, Y, He, W, Emotion processing models in individuals with different levels of social anxiety based on the crowd emotion perception task. NeuroImage, 121880.(JCR Q1), 2026, DOI: 10.1016/j.neuroimage.2026.121880
[10] Cheng, C, Cai, X, Qi, H, Chen, W, Zhang, Y, MSDA-Net: Multi-source Domain Adaptive Network for Multi-modal Emotion Recognition, ACM Transactions on Asian and Low-Resource Language Information Processing, 2026, 25 (1), 1-22.(JCR Q2), DOI: 10.1145/3786588
[11] Cheng, C, Liu, W, Jia, Z, Luo, W, A multi-stage hemisphere asymmetry fusion network inspired by the brain for EEG depression detection. Information Fusion, 124, 2025, 103342. (SCI 1区), DOI: 10.1016/j.inffus.2025.103342
[12] Zhang, Y, Chen, W, Cai, X, Cheng, C*, SASD-MCL: Semi-supervised alignment self-distillation with mixed contrastive learning for cross-subject EEG emotion recognition. Neural Networks,190, (2025), 107614. (JCR Q1), DOI: 10.1016/j.neunet.2025.107614
[13] Cheng, C, Liu, W, Jia, Z, & He, W, Multi-view Multi-scale Adapter Squeeze Excitation Network with Domain Generalization for Cross-Subject Emotion Recognition. Expert Systems with Applications, 2025, 129222. (SCI 1区), DOI: 10.1016/j.eswa.2025.129222
[14] Zhang Y, Liu Y, Li HK, Cheng C*, Z Jia, MPFBL: Modal pairing-based cross-fusion bootstrap learning for multimodal emotion recognition, 2025, Neurocomputing, 131577. (JCR Q1)， DOI: 10.1016/j.neucom.2025.131577
[15] Cheng C, Liu W, Wang X, Feng L, Jia Z, DISD-Net: A dynamic interactive network with self-distillation for cross-subject multi-modal emotion recognition, IEEE Transactions on Multimedia, 2025. (SCI 1区), DOI:10.1109/TMM.2025.3535344
[16] Y Zhang, J Qu, Q Zhang, Cheng C*, EEG-based emotion recognition based on 4D feature representations and multiple attention mechanisms, 2025, Biomedical Signal Processing and Control, 2025, 103, 107432. (JCR Q1), DOI:https://doi.org/10.1016/j.bspc.2024.107432
[17] Cheng C, Liu W, Feng L, Jia Z, Emotion recognition using hierarchical spatial–temporal learning transformer from regional to global brain, Neural Networks, 2024, 179, 106624. (SCI 1区), DOI:https://doi.org/10.1016/j.neunet.2024.106624
[18] Cheng C, Liu W, Fan Z, Feng L, Jia Z, A novel transformer autoencoder for multi-modal emotion recognition with incomplete data, Neural Networks, 2024, 172, 106111. (JCR Q1), DOI:https://doi.org/10.1016/j.neunet.2024.106111
[19] Cheng C, Liu W, Feng L, Jia Z, Dense graph convolutional with joint cross-attention network for multimodal emotion recognition, IEEE Transactions on Computational Social Systems, 2024. (JCR Q1), DOI:10.1109/TCSS.2024.3412074
[20] Cheng C, Liu W, Zhang Y, Feng L, Jia Z, A cross-modal adaptive masked autoencoder for decoding emotions with multimodal data, IEEE Transactions on Computational Social Systems, 2024. (JCR Q1), DOI:10.1109/TCSS.2024.3415613
[21] Cheng C, Yu Z, Zhang Y, Feng L, Hybrid network using dynamic graph convolution and temporal self-attention for EEG-based emotion recognition, IEEE Transactions on Neural Networks and Learning System, 2023, 1-11. (SCI 1区), DOI:10.1109/TNNLS.2023.3319315
[22] Wang X, Cheng C, Liu S, Song R, Wang X, Feng L, SS-INR: Spatial-spectral implicit neural representation network for hyperspectral and multispectral image fusion, IEEE Transactions on Geoscience and Remote Sensing, 2023, 61, 1-14. (SCI: 1区), DOI:10.1109/TGRS.2023.3317413
[23] Feng L, Cheng C*, Zhao M, Deng H, Zhang Y, EEG-based emotion recognition using spatial-temporal graph convolutional LSTM with attention mechanism, IEEE Journal of Biomedical and Health Informatics, 2022, 26 (11), 5406-5417. (SCI 1区), DOI:10.1109/JBHI.2022.3198688
[24] Cheng C, Zhang Y, Liu L, Liu W, Feng L, Multi-domain encoding of spatiotemporal dynamics in EEG for emotion recognition, IEEE Journal of Biomedical and Health Informatics, 2022, 27 (3), 1342-1353. (SCI 1区), DOI:10.1109/JBHI.2022.3232497
[25] Zhang Y, Cheng C, Wang S, Xia T, Emotion recognition using heterogeneous convolutional neural networks combined with multimodal factorized bilinear pooling, Biomedical Signal Processing and Control, 2022, 77, 103877. (JCR Q1), DOI:https://doi.org/10.1016/j.bspc.2022.103877
[26] Zhang Y, Cheng C, Zhang Y, Multimodal emotion recognition based on manifold learning and convolution neural network, Multimedia Tools and Applications, 2022, 81 (23), 33253-33268. (SCI: 4区), DOI:https://doi.org/10.1007/s11042-022-13149-8
[27] Zhang Y, Cheng C, Zhang Y, Multimodal emotion recognition using a hierarchical fusion convolutional neural network, IEEE Access, 2021, 9, 7943-7951. (SCI: 3区), DOI:10.1109/ACCESS.2021.3049516
会议论文：
[1] Zhang Y, Liu Y, Cheng C*, PSACF: Parallel-serial attention-based cross-fusion for multimodal emotion recognition, 2024 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2024, 4014-4017, DOI:10.1109/BIBM62325.2024.10822849
[2] Zhang Y, Chen W, Cheng C*, Multi-modal network based on spatio-temporal and attention for emotion recognition, 2023 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2023, 2364-2367, DOI:10.1109/BIBM58861.2023.10385831
[3] Zhang Y, Cai X, Chen W, Cheng C, Wang J, MSDA-ACLDR: Multi-source Domain Adaptation Augmented Contrastive Learning with Dual-stream Representations for Emotion Recognition, 2024 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2024, 4010-4013, DOI:10.1109/BIBM62325.2024.10821760
[4] Yu Z, Cheng C, Wen W, Guo W, Feng L, Action reinforcement and indication module for single-frame temporal action localization, 2023 International Joint Conference on Neural Networks (IJCNN), 2023, DOI: 10.1109/IJCNN54540.2023.10191287
[5] Zhang Y, Cheng C, Chen T, Multi-channel physiological signal emotion recognition based on relieff feature selection, 2019 IEEE 25th International Conference on Parallel and Distributed Systems (ICPADS), 2019, 725-730, DOI:10.1109/ICPADS47876.2019.00107
更多信息：
谷歌学术: https://scholar.google.com.hk/citations?hl=zh-CN&user=b21brckAAAAJ
ResearchGate: https://www.researchgate.net/profile/Cheng-Cheng-151/research
