Woocheol Shin

M.S. Student, Graduate School of Data Science, KAIST

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I am an M.S. student in the Graduate School of Data Science at KAIST, advised by Prof. Jinkyoo Park in the System Intelligence Lab.

I received my B.S. in Computer Science and Engineering from UNIST. I worked with Prof. Junghoon Kim at the Data Mining Lab, focusing on graph-structured problems, particularly algorithm design and problem formulation.

I am broadly interested in building generative policies for sequential decision-making toward human-desired goals in the real world. My current research focuses on steering large generative models, especially diffusion and flow-based models, toward desired outputs using reinforcement learning and reward-guided optimization.

news

Sep 2026 Two papers accepted to NeurIPS 2026!
Jan 2026 Two papers accepted to ICLR 2026!
Oct 2025 Paper accepted to WSDM 2026!
Jun 2025 Paper accepted to Knowledge-Based Systems!
Feb 2025 Started M.S. at the Graduate School of Data Science, KAIST, advised by Prof. Jinkyoo Park.

selected publications

  1. Diffusion Fine-Tuning via Reparameterized Policy Gradient of the Soft Q-Function
    Hyeongyu Kang*, Jaewoo Lee*, Woocheol Shin*, and 2 more authors
    In International Conference on Learning Representations (ICLR), 2026
    *Equal contribution.
  2. Diffusion Alignment as Variational Expectation-Maximization
    Jaewoo Lee, Minsu Kim, Sanghyeok Choi, and 7 more authors
    In International Conference on Learning Representations (ICLR), 2026
  3. Urban Traffic Network Layout Optimization with Guided Discrete Diffusion Models
    Taeyoung Yun, Inhyuck Song, Woocheol Shin, and 4 more authors
    In ACM International Conference on Web Search and Data Mining (WSDM), 2026