Young-Han Son

Affiliations: Korea University, Department of Artificial Intelligence.

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Hafelekarspitze, Nordkette Alps🏔️

Innsbruck, Austria

Hello! I’m Young-Han Son, a PhD candidate at the Department of Artificial Intelligence, Korea University.

My research focuses on physics-based modeling for computational lithography, particularly on embedding optical physics, such as diffraction theory, into ML architectures. I am also working on molecular optimization for drug discovery, with interests in optimization and reinforcement learning.

I also co-supervise projects in medical AI.

Outside of research, I’m a coffee lover ☕ — I enjoy AeroPress and hand-drip brewing, and love exploring a variety of coffee beans.

news

Feb 23, 2026 Our paper on optical diffraction-based semiconductor lithography has been accepted to CVPR 2026!
May 01, 2025 Our paper on offline molecular optimization has been accepted to ICML 2025!
Jun 19, 2024 Our paper on multi-objective molecular optimization has been accepted to IJCAI 2024 as a long presentation!
Mar 26, 2024 Our paper on molecular property prediction with multi-representation fusion transformer has been accepted to IEEE JBHI!

selected publications

  1. CVPR
    Optical Diffraction-based Convolution for Semiconductor Lithography
    Young-Han Son, Dong-Hee Shin, Deok-Joong Lee, Hyun Jung Lee, and Tae-Eui Kam
    Proceedings of the Computer Vision and Pattern Recognition Conference, 2026
  2. ICML
    Offline Model-based Optimization for Real-World Molecular Discovery
    Dong-Hee Shin*, Young-Han Son*, Hyung Jung Lee, Deok-Joong Lee, and Tae-Eui Kam
    International Conference on Machine Learning (ICML), 2025
  3. IJCAI Long
    Dynamic Many-Objective Molecular Optimization: Unfolding Complexity with Objective Decomposition and Progressive Optimization
    Dong-Hee Shin*, Young-Han Son*, Deok-Joong Lee, Ji-Wung Han, and Tae-Eui Kam
    International Joint Conference on Artificial Intelligence (IJCAI), 2024
  4. IEEE JBHI
    FTMMR: Fusion transformer for integrating multiple molecular representations
    Young-Han Son*, Dong-Hee Shin*, and Tae-Eui Kam
    IEEE Journal of Biomedical and Health Informatics, 2024
  5. IEEE TSMC
    MARS: multiagent reinforcement learning for spatial—spectral and temporal feature selection in EEG-based BCI
    Dong-Hee Shin*, Young-Han Son*, Jun-Mo Kim, Hee-Jun Ahn, Jun-Ho Seo, Chang-Hoon Ji, Ji-Wung Han, Byung-Jun Lee, Dong-Ok Won, and Tae-Eui Kam
    IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2024