Minjun Kim

I am a Ph.D. candidate in the Department of Electrical and Computer Engineering at Seoul National University, advised by Prof. Jongho Lee.

My research focuses on image reconstruction and domain adaptation/generalization in medical imaging. More recently, I have been exploring foundation models and multimodal large language models (MLLMs) to advance generalizable AI for healthcare applications.

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Minjun Kim

minjoony(at)snu.ac.kr

Education

2026.05 - Present
Visiting Ph.D. Student
Center for Advanced Medical Computing and Analysis
Harvard Medical School and Massachusetts General Hospital, Boston, MA, USA
Advisor: Prof. Quanzheng Li
2021.03 - Present
Ph.D. candidate in Electrical and Computer Engineering
Department of Electrical and Computer Engineering
Seoul National University, Seoul, Korea
Advisor: Prof. Jongho Lee
2015 - 2021.02
B.S. in Computer Engineering
Department of Computer Engineering
Hongik University, Seoul, Korea

Selected Publications

Other publications can be found in my Google Scholar profile.

Representative figure for χ-sepnet

χ-sepnet: Deep neural network for magnetic susceptibility source separation

M. Kim, S. Ji, J. Kim, K. Min, H. Jeong, J. Youn, T. Kim, J. Jang, B. Bilgic, H.-G. Shin, J. Lee

Human Brain Mapping, 2025

Paper Code
Representative figure for Resolution Generalizaiton for QSM

Resolution Generalization of Deep Learning-based Dipole Inversion Networks for QSM

S. Ji, M. Kim, J. Lee, H.-G. Shin

NeuroImage, 2025

Paper Code
Representative figure for Clinical dementia rating classification using integrated vision and language information

Clinical dementia rating classification using integrated vision and language information

J. Yoon, H. Park, M. Kim, H. Jeong, S. Y. Chun, S. Ji, J. Lee

IEEE Access, 2025

Paper Code

Conference Oral Talks

Representative figure for Harmonization for a Black-box Model using Disentanglement-based Generator and Bayesian Optimization

Harmonization for a Black-box Model using Disentanglement-based Generator and Bayesian Optimization

M. Kim, D. J. Mun, H. Jeong, H. Lee, SY. Chun, J. Lee

Annual Meeting of International Society of Magnetic Resonance in Medicine, 2026

Link Video Abstract
Representative figure for BrainMR Specialist: A Foundation Model of Brain MRI for Diverse Downstream Applications

BrainMR Specialist: A Foundation Model of Brain MRI for Diverse Downstream Applications

J. Park, M. Kim, R. Hong, J. Koo, RE. Yoo, SH. Choi, J. Lee

Annual Meeting of International Society of Magnetic Resonance in Medicine, 2026

Link Video Abstract
Representative figure for Bontrast Synthesis Guided by Scan Parameters

Contrast Synthesis Guided by Scan Parameters

J. Koo, M. Kim, T. Kim, R. Hong, J. Kim, H. Jeong, H. Lee, SY. Chun, J. Lee

Annual Meeting of International Society of Magnetic Resonance in Medicine, 2026

Link Video Abstract
Representative figure for Harmonization for a black-box deep learning model

Harmonization for a black-box deep learning model

M. Kim, H. Jeong, H. Seo, W. Jeong, J. Park, SY. Chun, J. Lee

Annual Meeting of International Society of Magnetic Resonance in Medicine, 2025

Link Video Abstract

Honors and Awards

2026
Summa Cum Laude Merit Award (top 5%)
"Harmonization for a Black-box Model using Disentanglement-based Generator and Bayesian Optimization", Annual Meeting of International Society of Magnetic Resonance in Medicine
2026
Summa Cum Laude Merit Award (top 5%)
"BrainMR Specialist: A Foundation Model of Brain MRI for Diverse Downstream Applications", Annual Meeting of International Society of Magnetic Resonance in Medicine
2026
Magna Cum Laude Merit Award (top 15%)
"Contrast Synthesis Guided by Scan Parameters", Annual Meeting of International Society of Magnetic Resonance in Medicine
2025
Annual Meeting Program Committee Selected Abstract (top 1%)
"Harmonization for a black-box deep learning model", Annual Meeting of International Society of Magnetic Resonance in Medicine
2025
Summa Cum Laude Merit Award (top 5%)
"Harmonization for a black-box deep learning model", Annual Meeting of International Society of Magnetic Resonance in Medicine
2025
Best Trainee Scientific Awards (Oral) - Silver
"BboxHarmony: A Novel Harmonization Framework for a Black-box Deep-Learning Model", International Congress on MRI & Annual Scientific Meeting of KSMRM
2021
Best Trainee Scientific Awards (Poster) - 1st place
"χ-separation net: Susceptibility source separation in the brain using deep neural network", International Congress on MRI & Annual Scientific Meeting of KSMRM
2021
Pre-Startup Package - 1st place
Korea Institute of Startup and Entrepreneurship Development
2019
Graduation Project Contest - 4th place
Hongik University
2020
Startup Contest - 1st place
Dongduk Women’s University
2016-20
Academic Excellence Scholarship
Hongik University