We are Universal Transfer Learning (UTL) lab at Korea University with Prof. Donghyun Kim. Our research pursuits are situated under the expansive umbrella of transfer learning, with a particular emphasis on investigating the transferability, generalization, and adaptability of robust artificial intelligence (AI) models across a wide array of AI domains and disciplines.
Our overarching objective is to pioneer the creation of highly effective transfer learning algorithms that can seamlessly transcend the boundaries of disparate domains and modalities found within a multitude of fields. These algorithms will be specifically tailored to cater to a wide spectrum of real-world applications, thus driving innovation and advancements in various industries and sectors.
Our main research interests include but not limited to the following:
We are looking for passionate new MS, MS/PhD, PhD students or Postdocs to join the team (more info) !
June 2026
A paper has been accepted to Engineering Applications of Artificial Intelligence (EAAI). (JCR IF Top 3%)
June 2026
Yongwoo Kim has been awarded the AI SeoulTech Graduate School Scholarship.
June 2026
Three papers have been accepted to European Conference on Computer Vision (ECCV).
June 2026
A collaboration work with Miscrosoft Research and University of Wisconsin-Madison has been accepted to International Conference on Intelligent Robots & Systems (IROS).
May 2026
A collaboration work with Miscrosoft Research has been accepted to International Conference on Machine Learning (ICML).
Jan. 2026
A paper has been accepted to Engineering Applications of Artificial Intelligence (EAAI). (JCR IF Top 3%)
Jan. 2026
A paper has been accepted to European Chapter of the Association for Computational Linguistics (EACL).
Dec. 2025
Donghyun Kim has been awarded the Outstanding Advisor Award in the WISET Graduate Women Engineers Research Team Program.
Dec. 2025
A paper has been accepted to International Journal of Computer Vision (IJCV). (JCR IF Top 3%)
