News
| Mar 18, 2026 | Our project, “Development of a Multi-Institutional Endoscopic Digital Twin and Surgical Simulation World Model Platform Based on 4DGS and Federated Learning,” has been selected for funding by the National Research Foundation of Korea (NRF). |
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| Aug 01, 2025 | Our project, “Intelligent Mobile Vision: Efficient Federated MoE with Device-Specific Expert Models and Semi-Supervised Learning,” has been selected for funding by the National Research Foundation of Korea (NRF). |
| Jun 25, 2025 | Our paper “FedWSQ: Efficient Federated Learning with Weight Standardization and Distribution-Aware Non-Uniform Quantization” has been accepted to ICCV 2025. |
Research Interests
🌐 Federated learning
We explore federated learning frameworks for privacy-preserving and distributed deep learning across multiple clients.
🤳 Image restoration
We study image restoration techniques, including deblurring and denoising for high-quality visual reconstruction.
📷 Object detection
We study object detection methods for real-world scenarios and focus on lightweight architectures and efficient techniques for edge-device deployment.
