Seunggeun Kim

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Hi, I’m Seunggeun 👋

I’m a third-year Ph.D. student in Electrical & Computer Engineering at The University of Texas at Austin, advised by Prof. Adam Klivans.
My research focuses on generative AI (especially diffusion models) for real-world engineering problems, including work in protein design.

Previously, I received my B.S. in ECE from Seoul National University with highest honors in 2023. As an undergraduate, I worked on ASIC design as a research intern with Prof. Jaeha Kim.

Outside the lab: I enjoy reading and learning new things — and I also love singing and working out!

news

Jul 29, 2026 LatentMDM is in arxiv now.
May 02, 2026 Our paper has been accepted to ICML 2026!
Jun 30, 2025 My first first-author paper is accepted at ICCAD 2025!
Aug 20, 2023 I am starting my Ph.D. at UT Austin!

selected publications

  1. latentmdm_thumbnail.png
    From Interface to Inference: Eliciting Any-Order Inference from Any-Order Models
    Seunggeun Kim*, Jaeyeon Kim*, Taekyun Lee*, Yuyuan Chen*, Yilun Du, and 2 more authors
    arXiv preprint arXiv:2607.26504, 2026
  2. prism.gif
    Fine-Tuning Masked Diffusion for Provable Self-Correction
    Seunggeun Kim*, Jaeyeon Kim*, Taekyun Lee*, David Z Pan, Hyeji Kim, and 2 more authors
    ICML, 2026
  3. ppaas.png
    PPAAS: PVT and Pareto aware Analog Sizing via Goal-conditioned Reinforcement Learning
    Seunggeun Kim, Ziyi Wang, Sungyoung Lee, Youngmin Oh, Hanqing Zhu, and 2 more authors
    ICCAD, 2025