About Me

I am a Ph.D. student at KAIST AI (Kim Jaechul Graduate School of AI), advised by Prof. Jong Chul Ye at the Bioimaging, Signal Processing and Learning Lab (BiSPL). I received my B.S. in Computer Science and Bio and Brain Engineering (double major) from KAIST, graduating Summa Cum Laude.

My research explores diffusion and flow models for visual generation, with a particular focus on measurement-consistent controllable generation and inverse problems.

  • Generative Models
  • Diffusion/Flow Models
  • Controllable Generation
  • Inverse Problems

News

  • Jul. 2026 "InverseCrafter: Efficient Video ReCapture as a Latent Domain Inverse Problem" accepted to ECCV 2026.
  • Apr. 2026 Started research internship at Adobe Research, London.
  • Feb. 2026 "PromptLoop: Plug-and-Play Prompt Refinement via Latent Feedback for Diffusion Model Alignment" accepted to CVPR 2026.
  • Aug. 2025 Started research internship at NAVER Cloud (Generation Research, AI Lab).
  • Jul. 2025 "Reangle-A-Video: 4D Video Generation as Video-to-Video Translation" accepted to ICCV 2025.
  • Sep. 2024 Started Ph.D. at KAIST AI.
  • Jan. 2024 "LLM-CXR", "Don't Play Favorites: Minority Guidance for Diffusion Models", and "Decomposed Diffusion Sampler for Accelerating Large-Scale Inverse Problems" accepted to ICLR 2024.
  • Jul. 2023 "Improving 3D Imaging with Pre-Trained Perpendicular 2D Diffusion Models" accepted to ICCV 2023.
  • Aug. 2022 Started M.S. at KAIST AI.

Industry Experience

Research Intern, Adobe Research, London, United Kingdom

April 2026 – August 2026

Research Intern, NAVER Cloud (Generation Research, AI Lab), Seongnam, Republic of Korea

August 2025 – February 2026

Publications

P: preprint, C: conference · * denotes equal contribution