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Donghwan Lee

Integrated M.S.& Ph.D Student in SNU AIBL

Medical AI Researcher and an integrated M.S-Ph.D. candidate at Seoul National University.

I hold a dual Bachelor's degree in Biomedical Engineering and Artificial Intelligence in Korea University, and I am passionate about bridging core AI research with medical applications.

About Me

Research Interests

My research focuses on advancing Image and Video Generation using Diffusion Models in the field of core AI, while actively exploring ways to translate these methods into medical imaging applications.


I am particularly interested in applying these technologies to MRI, CT, and X-ray data, with research directions including 3D reconstruction and unsupervised anomaly detection.


My ultimate goal is to develop generalizable AI models that not only push the boundaries of generative modeling but also contribute to practical improvements in medical diagnostics.

Current Focus Areas

Deep Learning
Computer Vision
Generative Models (Diffusion, Flow Matching)
3D/4D Reconstruction
Medical Imaging

Recent News & Updates

June 2025
Paper Accepted at MICCAI 2025
Our paper on "OFF-CLIP: Improving Normal Detection Confidence in Radiology CLIP with Simple Off-Diagonal Term Auto-Adjustment" has been accepted for publication at MICCAI 2025.

View All News →

News & Updates

June 2025
Paper Accepted at MICCAI 2025
Our paper on "OFF-CLIP: Improving Normal Detection Confidence in Radiology CLIP with Simple Off-Diagonal Term Auto-Adjustment" has been accepted for publication at MICCAI 2025.

Curriculum Vitae

Education

Integrated M.S. & Ph.D Student in Biomedical Science

2025.03 - Present
Seoul National University

Advisor: Prof. Kyungsu Kim

B.S. in Biomedical Engineering & Artificial Intelligence

2021.03 - 2025.02
Korea University

GPA: 3.9/4.5

Work Experience

AI Research Engineer, OGQ corp.

2024.11 ~ present
OGQ corp.

Research and develop state-of-the-art(SOTA) generative AI models using diffusion and flow matching methods,

with applications in image/video inpainting, object removal, and object editing/composition.

Experience

Reviewer for AI conference paper

2025.04
ICCV 2025

Assisted Professor Kyungsu Kim in reviewing submissions for the ICCV 2025.

Evaluated the quality, novelty, and significance of a research paper in computer vision.

Contributed to the feedback provided to authors to improve their work.

Project Proposal

2025.04
Seoul National University R&DB Foundation

Core AI Mapping of Real-time EEG Dynamics to MRI-standard quantitative Biomarkers for Intelligent Brain Tumor Monitoring and Prognosis Prediction

- Led the writing of a multidisciplinary research proposal integrating EEG signal analysis with MRI-based tumor segmentation and report generation via LLMs.

Research Intern

2023.12 - 2024.08
Magnetic Resonance Lab, SNU

Under-sampled MRI Reconstruction by cross domain CNNs with Data Consistency

Awards & Honors

2024 Academic Excellence Award

2025.02
Korea University

Research Excellence Award in Undergraduate Research Program

2024.02
Department of Biomedical Sciences, Seoul National University College of Medicine

Publications

Junhyun Park∗, Chanyu Moon∗, Donghwan Lee, Kyungsu Kim†, Minho Hwang†
MICCAI(International Conference On Medical Image Computing And Computer Assited Intervention)
2025

Contact Information

📧
Email
tdr.lee@snu.ac.kr
🔗
GitHub
github.com/tdrlee
📝
Google Scholar
https://scholar.google.com/citations?user=GglaZUQAAAAJ&hl=ko

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