Network science is a field of study that aims to reveal structural patterns in real-world interaction networks, such as social networks, bibliographic networks, power grids, and others. The Network Science Lab (NS Lab; 네트워크과학연구실), part of the Dept. of AI at CUK, conducts extensive research on a wide range of theories, methodologies, and applications related to collection, representation, and analysis of networked data.
Members of the Network Science Lab at the Catholic University of Korea submitted one paper on mitigating the degree bias problem in the message passing mechanism to the IEEE TNSE (Transactions on Network Science and Engineering) and was accepted.
Van Thuy Hoang, a doctoral student at the Network Science Lab @ CUK, received the Best Award (최우수상) at the 22nd Graduate School Academic Awards (제22회 대학원 학술상) Ceremony for his outstanding research in graph learning, highlighting the lab's leadership in graph ML.
Members of the Network Science Lab at the Catholic University of Korea presented a paper on pre-training molecular graph neural networks at the 39th AAAI Conference on Artificial Intelligence (AAAI 2025).
The Network Science Lab at the Catholic University of Korea releases Halal or Not (HaCKG), a novel attributed knowledge graph completion model for predicting cultural appropriateness of everyday products (mainly, halal and haram of cosmetics).
The Network Science Lab at the Catholic University of Korea releases S-CGIB, a novel pre-trained graph neural network model for molecular structure learning.