面向儿童孤独症谱系障碍（ASD）及其伴随认知异常的评估与干预需求，无创脑机接口技术的发展面临三大核心挑战：脑电数据稀缺、个体差异显著、神经机制不明确。针对这些问题，致力于四个层面的方法学创新。

1)    在数据层面，通过生成高质量脑电数据，有效缓解了临床罕见样本数据匮乏的瓶颈。生成的脑电信号在时域、频域和空域特征上与真实数据保持高度一致，保留了与认知功能密切相关的神经振荡模式，为脑电信号解码提供了可靠的数据基础；

2)    在特征解析层面，开发的时空动态特征分析方法能够同步捕捉脑电信号的多维特性。这些方法成功识别了与感觉信息处理、执行功能等认知过程相关的神经活动模式，建立了脑电特征与行为表现的量化映射关系，为认知评估提供了客观指标；

3)    针对个体差异问题，构建的适应性质化分析框架能够有效处理ASD患儿的异质性表现。该框架通过多维度神经表征分析，揭示了不同认知领域（执行功能、感觉处理等）的特异性神经标记，为理解ASD认知异常的异质性提供了新视角；

4)    在临床应用层面，通过将脑电解析与计算模型相结合，完成了对个体认知特征的精准量化，为制定个性化干预方案提供了科学依据。

为无创脑机接口技术在ASD认知障碍评估与干预中的实际应用提供了方法学支持，助力医工结合技术从实验室向认知障碍临床场景的转化。

2020年以来在IEEE TKDE/TMI/TCYB/TNSRE/TCBB/TAI/JHBI、ACM CSUR等发表第一或通讯作者SCI论文四十余篇，入选JHBI亮点论文(2023(3))。期间代表性SCI期刊论文如下：

1)    ZUO, Y., WANG, Y., CHEN, D., ZOMAYA, A. Y., WANG, F., GAO, T., & CHEN, J. High-Fidelity EEG Generation: Generative Adversarial Network Highlighting Time-Frequency-Spatial Features Regulated by Global Dynamics Supervision. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2025, 33, 4432-4443.

2)    WANG, Y., ZUO, Y., CHEN, D., et al. Counterfactual Causal Inference of Biomedical Signals: Unveiling Causal EEG Patterns for ASD Evaluation, IEEE Transactions on Artificial Intelligence, 2025, DOI: 10.1109/TAI.2025.3610394.

3)    GAO, T., CHEN, D., ZHOU, M., WANG, Y., ZUO, Y., TU, W., LI, X., & CHEN, J. Self-training EEG discrimination model with weakly supervised sample construction: An age-based perspective on ASD evaluation. Neural Networks, 2025, 187, 107337.

4)    WANG, Y., ZUO, Y., CHEN, D., TU, W., ZOMAYA, A. Y., & LI, X. From hippocampal neurons to broad spiking neural networks. Neurocomputing, 2025, 647, 130547.

5)    TANG, Y., HUANG, W., CHEN, C., & CHEN, D. CT-DCENet: Deep EEG denoising via CNN-Transformer-based dual-stage collaborative ensemble learning. IEEE Journal of Biomedical and Health Informatics, 2025, 29(6), 4095-4108.

6)    WANG, F., CHEN, D., WENG, S., GAO, T., ZUO, Y., & ZHENG, Y. (2025). EEG temporal-spatial feature learning for automated selection of stimulus parameters in electroconvulsive therapy. IEEE Journal of Biomedical and Health Informatics, 29(2), 4095-4108

7)    WEI S, TANG Y B, GAO T F, CHEN D. Scale-variant structural feature construction of EEG stream via component-increased Dynamic Tensor Decomposition. Knowledge-Based Systems, 2024, 294: 111747.

8)    MING Z K, CHEN D, GAO T F, et al. V2IED: Dual-view learning framework for detecting events of interictal epileptiform discharges. Neural Networks, 2024, 172: 106136.

9)    KE H, CHEN D, YAO Q, TANG Y, et al. Deep Factor Learning for Accurate Brain Neuroimaging Data Analysis on Discrimination for Structural MRI and Functional MRI. IEEE/ACM Trans Comput Biol Bioinform. 2024 Jul-Aug;21(4):582-595.

10) TANG Y B, CHEN D, WU J, et al. Functional connectivity learning via Siamese-based SPD matrix representation of brain imaging data. Neural Networks, 2023, 163: 272-285.

11) TANG Y B, CHEN D, LIU H H, et al. Deep EEG Super-resolution via Correlating Brain Structural and Functional Connectivities. IEEE Transactions on Cybernetics, 2023, 53(7): 4410-4422.

12) GAO T F, CHEN D, TANG Y B, et al. EEG Reconstruction with a Dual-Scale CNN-LSTM Model for Deep Artifact Removal. IEEE Journal of Biomedical and Health Informatics, 2023, 27(3): 1283-1294.

13) TANG Y B, CHEN D, ZUO Y P, et al. Enhanced Bayesian Factorization with Variant Scale Partitioning for Multivariate Time Series Analysis. IEEE Transactions on Knowledge and Data Engineering, 2023, 35(4): 3832-3845.

14) CAI C, KANG H C, HASHEMI A, CHEN D. Bayesian Algorithms for Joint Estimation of Brain Activity and Noise in Electromagnetic Imaging. IEEE Transactions on Medical Imaging, 2023, 42(3): 762-773.

15) TANG Y B, CHEN D, LI X L. Dimensionality Reduction Methods for Brain Imaging Data Analysis. ACM Computing Surveys, 2022, 54(4): 87:1-87:36.

16) YIN D Z, CHEN D, TANG Y B, et al. Adaptive feature selection with shapley and hypothetical testing: Case study of EEG feature engineering. Information Sciences, 2022, 586: 374-390.

17) GAO T F, CHEN D, TANG Y B, et al. Adaptive density peaks clustering: Towards exploratory EEG analysis. Knowledge-Based Systems, 2022, 240: 108123.

18) CHEN D, TANG Y B, ZHANG H, et al. Incremental Factorization of Big Time Series Data with Blind Factor Approximation. IEEE Transactions on Knowledge and Data Engineering, 2021, 33(2): 569-584.

19) CAI C, DIWAKAR M, CHEN D, et al. Robust Empirical Bayesian Reconstruction of Distributed Sources for Electromagnetic Brain Imaging. IEEE Transactions on Medical Imaging, 2020, 39(3): 567-577.

20) KE H J, CHEN D, SHI B Y, et al. Improving Brain E-Health Services via High-Performance EEG Classification With Grouping Bayesian Optimization. IEEE Transactions on Services Computing, 2020, 13(4): 696-708.