Dr. Wonzoo Chung

Computer and Communication Engineering

Korea University, Korea (South)

Email: [email protected]

Qualifications

2002 Ph.D., Electrical Engineering, Cornell University, USA

Publications (Selected)

1. Bin, W., An, S., Chung, W., et al. (2026). Neural network approach for wideband RCS computation with wide incident angles via method of moments. Applied Sciences, 16(5), 2518.
2. Jung, K., Kim, M., Chung, W., et al. (2026). Multimodal network with accuracy-based inverse loss weighting and multimodal ensemble classification for EEG-based sleep stage classification. IEEE Access, 14, 1245–1255.
3. Ko, J. S., Nah, S. P., Park, C. S., et al. (2025). Optimal ground-based anchor placement for reference-insensitive linear least squares multilateration. Journal of Korean Institute of Information Technology, 23(10), 153–161.
4. Kim, H., Kim, M., Chung, W., et al. (2025). Sleep staging using compressed vision transformer with novel two-step attention weighted sum. IEEE Access, 13, 69650–69659.
5. Kim, M., & Chung, W. (2025). Phase retrieval using deep dual alternating direction method of multipliers network with deep sparse prior knowledge. IEEE Transactions on Audio, Speech and Language Processing, 33, 557–569.
6. Kang, S., Shin, H., & Chung, W. (2025). A novel geometric-based bistatic range grouping algorithm for multi-target localization in distributed MIMO radar systems. Expert Systems with Applications, 253, 124269.
7. Shin, J., & Chung, W. (2024). Multiband convolutional Riemannian network with band-wise Riemannian triplet loss for motor imagery classification. IEEE Journal of Biomedical and Health Informatics, 28(12), 7230–7238.
8. Lee, S., & Chung, W. (2024). Globally Conditioned Conditional FLOW (GCC-FLOW) for sea clutter data augmentation. Applied Sciences, 14(15), 6538.
9. Jung, K., & Chung, W. (2024). Temporal convolutional network-based multi-view sleep staging. 2024 12th International Winter Conference on Brain-Computer Interface (BCI), 1–7.
10. Shin, J., & Chung, W. (2024). Channel-optimized local region Riemannian approach for motor imagery classification. 2024 12th International Winter Conference on Brain-Computer Interface (BCI), 1–5.
11. Kim, M., & Chung, W. (2024). Convolutional transformer-in-transformer for automatic sleep stage classification. 2024 12th International Winter Conference on Brain-Computer Interface (BCI), 1–5.
12. Ko, J., & Chung, W. (2024). Enhancement of few-shot image classification using eigenimages. International Journal of Control, Automation and Systems, 21(12), 4088–4097.
13. Shin, J., & Chung, W. (2023). Multi-band CNN with band-dependent kernels and amalgamated cross entropy loss for motor imagery classification. IEEE Journal of Biomedical and Health Informatics, 27(9), 4466–4477.
14. Shin, J., & Chung, W. (2023). Multi-class motor imagery classification using multi-class SVM with multi-band Riemannian tangent space mapping. 2023 11th International Winter Conference on Brain-Computer Interface (BCI), 1–5.
15. Kim, M., Jung, K., & Chung, W. (2023). Automatic sleep stage classification method based on transformer-in-transformer. 2023 11th International Winter Conference on Brain-Computer Interface (BCI), 1–5.
16. Kim, H., Kim, M., & Chung, W. (2023). Sleep-cmkd: Self-attention cnn/transformer cross-model knowledge distillation for automatic sleep staging. 2023 11th International Winter Conference on Brain-Computer Interface (BCI), 1–6.
17. Jung, K., Kim, M., & Chung, W. (2023). Epoch-level and sequence-level multi-head self-attention-based sleep stage classification. 2023 11th International Winter Conference on Brain-Computer Interface (BCI), 1–6.
18. Kim, M., & Chung, W. (2023). A cascade of preconditioned conjugate gradient networks for accelerated magnetic resonance imaging. Computer Methods and Programs in Biomedicine, 225, 107090.
19. Kang, S., Kim, S., Park, C., et al. (2022). Design method for a wideband non-uniformly spaced linear array using the modified reinforcement learning algorithm. Sensors, 22(14), 5456.
20. Shin, J., & Chung, W. (2022). Motor imagery classification based on multi-kernel CNN with the amalgamated cross entropy loss. 2022 10th International Winter Conference on Brain-Computer Interface (BCI), 1–4.
21. Shin, J., & Chung, W. (2022). Motor imagery classification based on local log riemannian distance matrices selected by confusion area score. Asian Conference on Pattern Recognition, 159–169.
22. Kang, S., Kim, T., & Chung, W. (2021). Multi-target localization based on unidentified multiple RSS/AOA measurements in wireless sensor networks. Sensors, 21(13), 4455.