An, S., Kang, M., Kim, S., Chikontwe, P., Shen, L., & Park, S. H. (2025). Subject-Adaptive Meta-Learning for Personalized BCI: A Fusion of Resting-State EEG Signal and Task-Specific Information. Information Fusion.

Kang, M., Chikontwe, P., Kim, S., Jin, K. H., Adeli, E., Pohl, K. M., & Park, S. H. (2025). Efficient One-shot Federated Learning on Medical Data using Knowledge Distillation with Image Synthesis and Client Model Adaptation. Medical Image Analysis (MedIA).

An, S., Kim, S., Chikontwe, P., Jung, J., Jeon, H., Kim, J., & Park, S. H. (2024). Few-Shot Anomaly Detection Using Positive Unlabeled Learning with Cycle Consistency and Co-Occurrence Features. Expert Systems With Applications (ESWA) (IF 7.5, JCR 6.4%).

Kang, M., Kim, S., Jin, K. H., Adeli, E., Pohl, K. M., & Park, S. H. (2024). FedNN: Federated Learning on Concept Drift Data Using Weight and Adaptive Group Normalizations. Pattern Recognition (IF 8.5, JCR <10%), 149, 110230.

Kim, S.*, Park, H.*, Chikontwe, P., Kang, M., Jin, K. H., Adeli, E., ... Park, S. H. (2024). One-Shot Federated Learning for Multi-Organ Segmentation via Knowledge Distillation with Image Synthesis. IEEE Transactions on Medical Imaging (TMI) (IF 8.9, JCR <5%).

Kim, S.*, Park, H.*, Kang, M., Jin, K. H., Adeli, E., Pohl, K. M., & Park, S. H. (2024). Federated Learning with Knowledge Distillation for Multi-Organ Segmentation with Partially Labeled Datasets. Medical Image Analysis (MedIA) (IF 10.9, JCR <5%).

An, S., Kim, S., Chikontwe, P., & Park, S. H. (2023). Dual Attention Relation Network with Fine-Tuning for Few-Shot EEG Motor Imagery Classification. IEEE Transactions on Neural Networks and Learning Systems (IF 10.4, JCR <5%).

Kim, S., Chikontwe, P., An, S., & Park, S. H. (2023). Uncertainty-Aware Semi-Supervised Few-Shot Segmentation. Pattern Recognition (IF 8.5, JCR <10%), 109292.

Kim, S., Park, Y. W., Park, S. H., Ahn, S. S., Chang, J. H., Kim, S. H., & Lee, S.-K. (2020). Comparison of Diagnostic Performance of Two-Dimensional and Three-Dimensional Fractal Dimension and Lacunarity Analyses for Predicting the Meningioma Grade. Brain Tumor Research and Treatment, 8(1), 36.

Park, Y. W.*, Kim, S.*, Ahn, S. S., Han, K., Kang, S. G., Chang, J. H., ... Park, S. H. (2020). Magnetic Resonance Imaging-Based Three-Dimensional Fractal Dimension and Lacunarity Analyses May Predict the Meningioma Grade. European Radiology (IF 7.034, JCR <20%), 30, 4615–4622.

Jang, E.*, Kang, M.*, Kim, S., & Park, S. H. (2025). Revisiting Masked Image Modeling with Standardized Color Space for Domain Generalized Fundus Photography Classification. In MICCAI. Springer.

Lee, S.*, Kim, S.*, An, S., Lee, S., & Park, S. H. (2025). Logical Anomaly Detection with Text-Based Logic via Component-Aware Contrastive Language-Image Training. In Conference on Knowledge Discovery and Data Mining  (SIGKDD) – accept rate 18.4%.

Namgung, H., Nam, S., Kim, S., & Park, S. H. (2025). MC-NuSeg: Multi-Contour Aware Nuclei Instance Segmentation. In Information Processing in Medical Imaging (IPMI).

An, S., Kang, M., Kim, S., Chikontwe, P., Shen, L., & Park, S. H. (2024). Subject-Adaptive Transfer Learning Using Resting State EEG Signals for Cross-Subject EEG Motor Imagery Classification. In MICCAI. Springer.

Kim, S., An, S., Chikontwe, P., Kang, M., Adeli, E., Pohl, K. M., & Park, S. (2024). Few-Shot Part Segmentation Reveals Compositional Logic for Industrial Anomaly Detection. In AAAI.

Nam, S., Namgung, H., Jeong, J., Luna, M., Kim, S., Chikontwe, P., & Park, S. H. (2024). InstaSAM: Instance-Aware Segment Any Nuclei Model with Point Annotations. In MICCAI. Springer.

Kang, M., Chikontwe, P., Kim, S., Jin, K. H., Adeli, E., Pohl, K. M., & Park, S. H. (2023). One-Shot Federated Learning on Medical Data Using Knowledge Distillation with Image Synthesis and Client Model Adaptation. In MICCAI (pp. 521–531). Springer.

Chikontwe, P., Kim, S., & Park, S. H. (2022). CAD: Co-Adapting Discriminative Features for Improved Few-Shot Classification. In CVPR (pp. 14554–14563).

Park, H., Lee, G. M., Kim, S., Ryu, G. H., Jeong, A., Sagong, M., & Park, S. H. (2022). A Meta-Learning Approach for Medical Image Registration. In ISBI (pp. 1–5). IEEE.

Kim, S., An, S., Chikontwe, P., & Park, S. H. (2021). Bidirectional RNN-Based Few-Shot Learning for 3D Medical Image Segmentation. In AAAI (Vol. 35, pp. 1808–1816).

An, S., Kim, S., Chikontwe, P., & Park, S. H. (2020). Few-Shot Relation Learning with Attention for EEG-Based Motor Imagery Classification. In IROS (pp. 10933–10938).

Kim, S., Luna, M., Chikontwe, P., & Park, S. H. (2020). Two-Step U-Nets for Brain Tumor Segmentation and Random Forest with Radiomics for Survival Time Prediction. In Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries: 5th International Workshop, MICCAI, Part I 5 (pp. 200–209). Springer.