Team members have published papers in top conferences and journals such as Scientific Reports, International Journal of Computer Vision (IJCV), ICCV 2025 Workshop, ICCV 2025, Engineering Applications of Artificial Intelligence, CVPR 2025, ICLR 2025, and Expert Systems with Applications. Additionally, team member Jungmyung Wi won second place in the 2025 Samsung Collegiate Programming Challenge.
Research Experience
Leading the Universal Transfer Learning (UTL) Lab at Korea University, focusing on research in transfer learning.
Background
Research interests include but are not limited to domain transfer, task transfer, pre-training for transfer learning, foundation model adaptation, efficient adaptation, multimodal representation learning, transferable representation learning, un/self-supervised learning, learning from synthetic data, and learning compositionality. Aiming to develop highly effective transfer learning algorithms that can seamlessly transcend the boundaries of disparate domains and modalities.
Miscellany
Looking for passionate new MS, MS/PhD, PhD students or Postdocs to join the team.