PUBLICATIONS

S. Jeong, W. Ko, A. W. Mulyadi, and H.-I. Suk, "Deep Efficient Continuous Manifold Learning for Time Series Modeling," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 46, no. 1, pp. 171-184, 2024.

J. Phyo, W. Ko, E. Jeon, and H.-I. Suk, "Transitioning-aware Attention-based Deep Neural Network for Sleep Staging," IEEE Transactions on Cybernetics, vol. 53, no. 9, pp. 4500-4510, 2023. (2021-JCR-IF: 19.118, Automation & Control Systems: 1/65)

E. Jeon, W. Ko, J. S. Yoon, and H.-I. Suk, "Mutual Information-driven Subject-invariant and Class-relevant Deep Representation Learning in BCI,'' IEEE Transactions on Neural Networks and Learning Systems, vol. 34, no. 2, pp. 739-749, 2023. (2021-JCR-IF: 14.255, Computer Science-Theory & Methods: 4/110)

W. Ko, W. Jung, E. Jeon, and H.-I. Suk, "A Deep Generative-Discriminative Learning for Multi-modal Representation in Imaging Genetics," IEEE Transactions on Medical Imaging, vol. 41, no. 9, pp. 2348-2359, 2022. (2021-JCR-IF: 11.037, Radiology-Nuclear Medicine & Medical Imaging: 5/136)

W. Ko, E. Jeon, J. S. Yoon, and H.-I. Suk, "Semi-Supervised Generative and Discriminative Adversarial Learning for Motor Imagery-based Brain-Computer Interface,'' Scientific Reports, vol. 12, no. 1, pp. 1-14, 2022. (2021-JCR-IF: 4.997, Multidisciplinary Science: 19/74)

W. Ko, E. Jeon, and H.-I. Suk, "A Novel RL-assisted Deep Learning Framework for Task-informative Signals Selection and Classification for Spontaneous BCIs,'' IEEE Transactions on Industrial Informatics, vol. 18, pp. 1873-1882, 2022. (2021-JCR-IF: 11.648, Computer Science-Interdisciplinary Applications: 4/112)

W. Ko*, E. Jeon*, S. Jeong, J. Phyo, and H.-I. Suk (*: Equal contribution), "A Survey on Deep Learning-based Short/Zero-calibration Approaches for EEG-based Brain-Computer Interfaces," Frontiers in Human Neuroscience, vol. 15, p. 258, 2021. (2021-JCR-IF: 3.473, Psychology: 29/80)

B.-K. Min, H.-S. Kim, W. Ko, M.-H. Ahn, H.-I. Suk, D. Pantazis, R. T. Knight, "Electrophysiological Decoding of Spatial and Color Processing in Human Prefrontal Cortex,'' NeuroImage, vol. 237, p. 118165, 2021. (2021-JCR-IF: 7.400, Neuroimaging: 2/14)

J. Lee*, W. Ko*, E. Kang, and H.-I. Suk (*: Equal contribution), "A Unified Framework for Personalized Regions Selection and Functional Relation Modeling for Early MCI Identification,'' NeuroImage, vol. 236, p. 118048, 2021. (2021-JCR-IF: 7.400, Neuroimaging: 2/14)

W. Ko, E. Jeon, S. Jeong, and H.-I. Suk, "Multi-Scale Neural Network for EEG Representation Learning in BCI,'' IEEE Computational Intelligence Magazine, vol. 16, pp. 31-45, 2021. (2021-JCR-IF: 9.809, Computer Science-Artificial Intelligence: 15/145)

W. Ko and H.-I. Suk, "EEG-Oriented Self-Supervised Learning and Cluster-Aware Adaptation," in Proceedings of 31st ACM International Conference on Information and Knowledge Management (CIKM), ACM, 2022, pp. 4143-4147. (CIKM2022 Acceptance Rate: 27.51%)

J. Phyo, W. Ko, E. Jeon, and H.-I. Suk, "Enhancing Contextual Encoding with Stage-Confusion and Stage-Transition Estimation for EEG-based Sleep Staging,'' in Proceedings of 47th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), IEEE, 2022, pp. 1301-1305. (ICASSP2022 Acceptance rate: 45%)

S. Jeong, W. Ko, A. W. Mulyadi, and H.-I. Suk, "Continuous Riemannian Geometric Learning for Sleep Staging Classification,'' in Proceedings of 10th International Winter Conference on Brain-Computer Interface (BCI), IEEE, 2022, pp. 1-2.

W. Ko, W. Jung, A. W. Mulyadi, E. Jeon, and H.-I. Suk, "ENGINE: Enhancing Neuroimaging and Genetic Information by Neural Embedding,'' in Proceedings of 21st IEEE International Conference on Data Mining (ICDM), IEEE, 2021, pp. 1162-1167. (ICDM2021 Acceptance rate: 20%)

W. Ko, E. Jeon, and H.-I. Suk, "Spectro-Spatio-Temporal EEG Representation Learning for Imagined Speech Recognition,'' in Proceedings of 6th Asian Conference on Pattern Recognition (ACPR)}, IAPR, 2021, pp. 335-346. (ACPR2021 Acceptance rate: 55.1%)

S. Jeong, E. Jeon, W. Ko, and H.-I. Suk, "Fine-grained Temporal Attention Network for EEG-based Seizure Detection,'' in Proceedings of 9th International Winter Conference on Brain-Computer Interface (BCI), IEEE, 2021, pp. 1-4.

W. Ko, K. Oh, E. Jeon, and H.-I. Suk, "VIGNet: A Deep Convolutional Neural Network for EEG-based Driver Vigilance Estimation,'' in Proceedings of 8th International Winter Conference on Brain-Computer Interface (BCI), IEEE, 2020, pp. 1-3.

E. Jeon, W. Ko, and H.-I. Suk, "Domain Adaptation with Source Selection for Motor-Imagery based BCI,''  in Proceedings of 7th International Winter Conference on Brain--Computer Interface (BCI), IEEE, 2019, pp. 1-4.

W. Ko, E. Jeon, J. Lee, and H.-I. Suk, "Semi-Supervised Deep Adversarial Learning for Brain-Computer Interface,''  in Proceedings of 7th International Winter Conference on Brain-Computer Interface (BCI), IEEE, 2019, pp. 1-4.

W. Ko, J. S. Yoon, E. Kang, E. Jun, J.-S. Choi, and H.-I. Suk, "Deep Recurrent Spatio-Temporal Neural Network for Motor Imagery based BCI,''  in Proceedings of 6th International Winter Conference on Brain-Computer Interface (BCI), IEEE, 2018, pp. 1-3.