We study the geometric structure of datasets and models, and how they influence machine learning algorithms.
Associate Professor at POSTECH, leading research in machine learning with focus on geometric deep learning.
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Explore our research areas and discover what drives our scientific inquiry
Understanding and improving GNNs through geometric perspectives, addressing over-smoothing, and developing novel architectures.
Leveraging hyperbolic and Riemannian geometry for better representation learning of hierarchical and structured data.
Developing methods for machine unlearning, privacy-preserving ML, and robust evaluation of AI systems.
Applying machine learning to scientific discovery, including drug design, molecular modeling, and computational biology.
Research on LLM personalization, retrieval-augmented generation, and geometric reasoning in vision-language models.
Advancing graph generation, diffusion models, and generative approaches for structured data.
Join our lab and gain hands-on experience in cutting-edge machine learning research
Participate in research through POSTECH's undergraduate research program. Work directly with PhD students on ongoing projects.
Get paired with a PhD student mentor who will guide you through the research process and help you develop your skills.
Explore topics in GNNs, geometric deep learning, trustworthy AI, and more. Find projects matching your interests.
Our undergrad alumni have gone on to top PhD programs and industry positions. Build your foundation for a research career.
Our research published in top venues including NeurIPS, ICML, ICLR, CVPR, and more
Meet the researchers driving innovation in our lab
Get in touch or schedule a meeting
Room 4413, RIST Building IV
POSTECH, Pohang, Korea