Complete Publication List

Google Scholar Profile

Brain-Computer Interface:

1. D. Wu*, "Revisiting Euclidean Alignment for Transfer Learning in EEG-Based Brain-Computer Interfaces," Journal of Neural Engineering, 22:031005, 2025.

2. 伍冬睿, “精准、安全、隐私保护的脑机接口”, 中国人工智能学会通讯, 15(3):29-35, 2025.

3. L. Meng, X. Jiang, X. Chen, W. Liu, H. Luo and D. Wu*, "Adversarial Filtering Based Evasion and Backdoor Attacks to EEG-Based Brain-Computer Interfaces," Information Fusion, 107:102316, 2024. (Python)

4. R. Bian, H. Wu, B. Liu and D. Wu*, "Small Data Least-Squares Transformation (sd-LST) for Fast Calibration of SSVEP-based BCIs," IEEE Trans. on Neural Systems and Rehabilitation Engineering, 31:446-455, 2023. (Python)

5. D. Wu, J. Xu, W. Fang, Y. Zhang, L. Yang, X. Xu*, H. Luo* and X. Yu*, "Adversarial Attacks and Defenses in Physiological Computing: A Systematic Review," National Science Open, 1:20220023, 2022.

6. D. Wu*, X. Jiang, R. Peng, "Transfer Learning for Motor Imagery Based Brain-Computer Interfaces: A Tutorial," Neural Networks, 153:235-253, 2022. (Matlab)

7. X. Zhang, D. Wu*, L. Ding*, H. Luo, C-T Lin, T-P Jung and R. Chavarriaga, "Tiny noise, big mistakes: Adversarial perturbations induce errors in Brain-Computer Interface spellers," National Science Review, 8(4), 2021. (Python; TechXplore; TechXplore2)

8. W. Zhang and D. Wu*, "Manifold Embedded Knowledge Transfer for Brain-Computer Interfaces," IEEE Trans. on Neural Systems and Rehabilitation Engineering, 28(5):1117-1127, 2020. (Python; 世界机器人大会)

9. H. He and D. Wu*, "Transfer Learning for Brain-Computer Interfaces: A Euclidean Space Data Alignment Approach," IEEE Trans. on Biomedical Engineering, 67(2):399-410, 2020. (ESI Highly Cited Paper; Matlab; IEEE Brain; Best Paper Award)

10. X. Zhang and D. Wu*, "On the Vulnerability of CNN Classifiers in EEG-Based BCIs," IEEE Trans. on Neural Systems and Rehabilitation Engineering, 27(5):814-825, 2019. (Python)

Affective Computing:

1. D. Wu, B-L Lu, B. Hu* and Z. Zeng*, "Affective Brain-Computer Interfaces (aBCIs): A Tutorial," Proceedings of the IEEE, 111(10):1314-1332, 2023.

2. Y. Xu, X. Jiang and D. Wu*, "Cross-Task Inconsistency Based Active Learning (CTIAL) for Emotion Recognition," IEEE Trans. on Affective Computing, 2024, in press. (Python)

3. Y. Xu, Y. Cui, X. Jiang, Y. Yin, J. Ding, L. Li and D. Wu*, "Inconsistency-Based Multi-Task Cooperative Learning for Dimensional Emotion Recognition," IEEE Trans. on Affective Computing, 13(4):2017-2027, 2022. (Python)

4. D. Wu* and J. Huang, "Affect Estimation in 3D Space Using Multi-Task Active Learning for Regression," IEEE Trans. on Affective Computing, 13(1):16-27, 2022.

5. S. Li, Y. Xu, H. Wu, D. Wu*, Y. Yin, J. Cao and J. Ding, "Facial Expression Recognition in-the-wild with Deep Pre-trained Models," European Conference on Computer Vision (ECCV) ABAW Workshop, Tel Aviv, Israel, October 2022.  (Python)

6. 权学良, 曾志刚, 蒋建华, 张亚倩, 吕宝粮, 伍冬睿*, 基于生理信号的情感计算研究综述. 自动化学报, 47(8):1769−1784, 2021.

7. D. Wu, C. Courtney, B. Lance, S. Narayanan, M. Dawson, K. Oie, and T.D. Parsons, “Optimal Arousal Identification and Classification for Affective Computing: Virtual Reality Stroop Task,” IEEE Trans. on Affective Computing, 1(2):109-118, 2010. (Top Accessed Article; IEEE Trans. on Affective Computing Most Influential Paper Award Finalist)

Machine Learning:

1. L. Deng, R. Xu, Y. Wang, X. Du, X. Ma, X. Zheng and D. Wu*, "LMID: A Comprehensive multimodal Dataset for Failure Prediction in Cloud Computing Systems," ACM KDD, Jeju, South Korea, August 2026.

2. L. Deng, Y. Wang, H. Wang, X. Ma, X. Du, X. Zheng and D. Wu*, "Time-Aware Attention-Based Transformer (TAAT) for Cloud Computing System Failure Prediction," ACM KDD, Barcelona, Spain, August 2024.

3. C. Zhao, D. Wu*, J. Huang, Y. Yuan, H-T Zhang, R. Peng and Z. Shi, "BoostTree and BoostForest for Ensemble Learning," IEEE Trans. on Pattern Analysis and Machine Intelligence, 45(7):8110-8126, 2023. (Python)

4. W. Zhang, L. Deng, L. Zhang and D. Wu*, "A Survey on Negative Transfer," IEEE/CAA Journal of Automatica Sinica, 10(2):305-329, 2023. (Python; Norbert Wiener Review Award)

5. X. Zhang, H. Xiong and D. Wu, "Rethink the Connections among Generalization, Memorization, and the Spectral Bias of DNNs," Int'l Joint Conf. on Artificial Intelligence (IJCAI), Montreal, Canada, August 2021.

6. X. Zhang and D. Wu*, "Empirical Studies on the Properties of Linear Regions in Deep Neural Networks," Int'l. Conf. on Learning Representations (ICLR), Addis Ababa, Ethiopia, April 2020.

7. D. Wu*, Y. Yuan, J. Huang and Y. Tan*, "Optimize TSK Fuzzy Systems for Regression Problems: Mini-Batch Gradient Descent with Regularization, DropRule and AdaBound (MBGD-RDA)," IEEE Trans. on Fuzzy Systems, 28(5):1003-1015, 2020. (Matlab)

8. D. Wu* and J.M. Mendel, "Patch Learning," IEEE Trans. on Fuzzy Systems, 28(9):1996-2008, 2020. (Matlab; IEEE CIS Publication Spotlight)

9. D. Wu, C-T Lin, J. Huang* and Z. Zeng*, "On the Functional Equivalence of TSK Fuzzy Systems to Neural Networks, Mixture of Experts, CART, and Stacking Ensemble Regression," IEEE Trans. on Fuzzy Systems, 28(10):2570-2580, 2020.

10. D. Wu*, C-T Lin and J. Huang*, "Active Learning for Regression Using Greedy Sampling," Information Sciences, 474:90-105, 2019. (Matlab)

11. D. Wu, "Pool-based sequential active learning for regression," IEEE Trans. on Neural Networks and Learning Systems, 30(5): 1348-1359, 2019. (Matlab)

Smart Healthcare:

1. Z. Wang, S. Li and D. Wu*, "Canine EEG Helps Human: Cross-Species and Cross-Modality Epileptic Seizure Detection via Multi-Space Alignment," National Science Review, 12:nwaf086, 2025. (Python)

2. J. An, R. Peng, Z. Du, H. Liu, F. Hu, K. Su* and D. Wu*, "Sparse Knowledge Sharing (SKS) for Privacy-Preserving Domain Incremental Seizure Detection," Journal of Neural Engineering, 22(2):026003, 2025. (Python)

3. R. Peng, Z. Du, C. Zhao, J. Luo, W. Liu, X. Chen* and D. Wu*, "Multi-Branch Mutual-Distillation Transformer for EEG-Based Seizure Subtype Classification," IEEE Trans. on Neural Systems and Rehabilitation Engineering, 32:831-839, 2024. (Python)

4. Z. Du, R. Peng, W. Liu, W. Li* and D. Wu*, "Mixture of Experts for EEG-Based Seizure Subtype Classification," IEEE Trans. on Neural Systems and Rehabilitation Engineering, 31:4781-4789, 2023. (Python)

5. Z. Wang, W. Zhang, S. Li, X. Chen and D. Wu*, "Unsupervised Domain Adaptation for Cross-Patient Seizure Classification," Journal of Neural Engineering, 20(6):066002, 2023. (Python)

6. R. Peng, C. Zhao, J. Jiang, G. Kuang, Y. Cui, Y. Xu, H. Du, J. Shao*, and D. Wu*, "TIE-EEGNet: Temporal Information Enhanced EEGNet for Seizure Subtype Classification," IEEE Trans. on Neural Systems and Rehabilitation Engineering, 30:2567-2576, 2022. (Python)

7. 彭睿旻, 江军, 匡光涛, 杜浩, 伍冬睿*, 邵剑波. 基于EEG的癫痫自动检测: 综述与展望. 自动化学报, 48(2):335-350, 2022.