About Me
Hi! I am a Ph.D. candidate working at the intersection of optical imaging and generative AI. I develop diffusion/flow-based methods for solving inverse problems in imaging (advisor: Prof. Se Young Chun, Intelligent Computational Imaging Lab). Previously, I worked on advanced imaging systems with nanophotonic/metasurface technologies (advisors: Prof. Byoungho Lee, Prof. Yoonchan Jeong, Optical Engineering and Quantum Electronics Lab).
đź’ˇ My research interest is bridging the gap between optical system design and learned signal reconstruction, developing next-generation intelligent imaging systems that integrate physics and machine intelligence.
Interests
- Computational Imaging
- Inverse Problems
- Generative Models
- Metasurfaces & Nano-Optics
Education
- Ph.D. in Electrical and Computer EngineeringSeoul National University · 2021 – present
- B.S. in Electrical and Computer EngineeringSeoul National University · 2016 – 2021
News
Oct 03, 2026
Our paper “FLINT: Coupling Proximal Initialization and Bounded Stochasticity for Flow-Matching Inverse Problems” accepted to NeurIPS 2026.
Aug 08, 2026
Our paper “Metric 3D Height Reconstruction from 2D SEM Images via Confidence-Weighted Fusion of Stereo and Four-Channel Photometric Cues” accepted to ISOCC 2026.
May 26, 2026
An updated version of our paper “Self-Cascaded Diffusion Models for Arbitrary-Scale Image Super-Resolution” is now available on arXiv. The code will be released soon.
May 01, 2026
Our paper “Triadic Dynamics Aware Diffusion Posterior Sampling for Inverse Problems: Optimizing Guidance and Stochasticity Schedules” accepted to ICML 2026.
Jun 09, 2025
Our paper “Self-Cascaded Diffusion Models for Arbitrary-Scale Image Super-Resolution” preprint released on arXiv.
May 12, 2025
Our paper AIM 2024 Challenge on UHD Blind Photo Quality Assessment accepted to ECCV 2024 Workshops.