Research Interests

• Inverse Problems and Computational Imaging

- Image restoration for Natural Images (Denoising, Super-Resolution, etc.)

- Medical Image Reconstructions (CT, Ultrasound, Microscopy)

• Multi-Modal Learning for AI Application

- Enhancing Multi-modal learning with Optimal Transport

- Large Multimodal model for Health Care AI

• Deep Generative AI

- Developing efficient generative model with theoretical understandings

- Accelerating Diffusion models

Education

• Ph. D., Kim Jae Chul Graduate School of AI  (Sep. 2020 - Aug. 2024)

  • Korea Advanced Institute of Science and Technology (KAIST), South Korea

    • • Thesis Title :   "Score Matching Based Self-Supervised Image Denoising and Parameter Estimation"

  • Advisor: Prof. Jong Chul Ye

• M. S., Electrical Engineering (Aug. 2018 - Aug. 2020)

  • Ulsan National Institute of Science and Technology (UNIST), South Korea

  • Thesis Title :   "Unsupervised Training of Denoisers for Low-Dose CT Reconstruction Without Full-Dose Ground Truth"

  • Advisor: Prof.  Se Young Chun, (He is currently in Seoul National University, SNU )

• B. S., Electrical Engineering (Feb. 2012 - Aug. 2018)

  • • • Ulsan National Institute of Science and Technology (UNIST), South Korea, Summa Cum laude

Work Experiences

• Sep. 2024 - Current AI Research Scientist, Samsung Reserach