Full paper lists

2026 Publications

3D-LLDM: Label-Guided 3D Latent Diffusion Model Kyeonghun Kim, Jaehyeok Bae, Youngung Han, Joo Young Bae, Seoyoung Ju, Junsu Lim, Gyeongmin Kim, Nam-Joon Kim^†, Woo Kyoung Jeong, Ken Ying-Kai Liao, Won Jae Lee, Pa Hong, Hyuk-Jae Lee IEEE Int. Symp. Biomedical Imaging (ISBI) 2026
LOSA-NET: Localized and Scale-Adaptive Network Youngung Han, Hyunsu Go, Kyeonghun Kim, Induk Um, Junga Kim, Jaewon Jung, Nam-Joon Kim^†, Woo Kyoung Jeong^†, Won Jae Lee, Ken Ying-Kai Liao, Pa Hong, Hyuk-Jae Lee IEEE Int. Symp. Biomedical Imaging (ISBI) 2026
MMA-FORMER: Multi-Window Attention Transformer Youngung Han, Induk Um, Kyeonghun Kim, Junga Kim, Hyunsu Go, Jaewon Jung, Nam-Joon Kim^†, Woo Kyoung Jeong^†, Won Jae Lee, Ken Ying-Kai Liao, Pa Hong, Hyuk-Jae Lee IEEE Int. Symp. Biomedical Imaging (ISBI) 2026
NeoNet: Neoplastic End-to-End Original 3D MRI-Based Deep Learning Framework Youngung Han, Minkyung Cha, Kyeonghun Kim, Induk Um, Myeongbin Sho, Joo Young Bae, Jaewon Jung, Jung Hyeok Park, Seojun Lee, Nam-Joon Kim^†, Woo Kyoung Jeong, Won Jae Lee, Pa Hong, Ken Ying-Kai Liao, Hyuk-Jae Lee Workshop on Health Intelligence (W3PHIAI), AAAI 2026
CATATPAD: Context-Aware Transfer Adaptation for Trajectory Prediction in Autonomous Driving Seohyoung Park, Jaeyeol Lim, Seoyoung Ju, Kyeonghun Kim, Ken Ying-Kai Liao, Nam-Joon Kim^†, Hyuk-Jae Lee IEEE Int. Conf. Electronics, Information, and Communication (ICEIC) 2026
MAESIL: Masked Autoencoder for Enhanced Self-supervised Medical Image Learning Kyeonghun Kim, Hyeonseok Jung, Youngung Han, Junsu Lim, YeonJu Jean, Seongbin Park, Eunseob Choi, Hyunsu Go, SeoYoung Ju, Seohyoung Park, Gyeongmin Kim, MinJu Kwon, KyungSeok Yuh, Soo Yong Kim, Ken Ying-Kai Liao, Nam-Joon Kim^†, Hyuk-Jae Lee IEEE Int. Conf. Electronics, Information, and Communication (ICEIC) 2026

2025 Publications

CIPHER: Counterfeit Image Pattern High-level Examination via Representation Kyeonghun Kim, Youngung Han, SeoYoung Ju, Yeonju Jean, YooHyun Kim, Minseo Choi, SuYeon Lim, Kyungtae Park, Seungwoo Baek, Sieun Hyeon, Nam-Joon Kim^†, Hyuk-Jae Lee IEEE Int. Conf. Consumer Electronics - Asia (ICCE-Asia) 2025
Improving Deep Learning-based Diagnosis of Hepatic Tumors on Multi-phase CEUS Taehoon Lee, Jaeyeol Lim, Nam-Joon Kim^†, Woo Kyoung Jeong, Won Jae Lee, Kyeonghun Kim ULTRASONICS 2025
FOSCU: Feasibility of Synthetic MRI Generation via Duo-Diffusion Models Youngung Han, Kyeonghun Kim, Seoyoung Ju, Yeonju Jean, Minkyung Cha, Seohyoung Park, Hyeonseok Jung, Nam-Joon Kim^†, Woo Kyoung Jeong, Ken Ying-Kai Liao, Hyuk-Jae Lee IEEE Asia Pacific Conf. Circuits and Systems (APCCAS) 2025
Boundary Guidance for Efficient 3D CT Vision–Language Reasoning Soo Yong Kim^*, Kyeonghun Kim^*, Taejin Kim, Yoonkyoung Chun, Hyungjun Kim, Dayoon Lee, Jeongmin Shin, Pa Hong, Nam-Joon Kim^† Workshop on Emerging LLM/LMM Applications in Medical Imaging (ELAMI), MICCAI 2025
Automated Dental Caries Segmentation in Panoramic Radiographs Using Dual-Stage Deep Learning Jihun Kim^*, Kyeonghun Kim^*, Jong-yeol Lee, Yeongseok Seo, Dohyun Chun^† Workshop on Machine Learning in Medical Imaging (MLMI), MICCAI 2025

NVIDIA GTC 2026 Poster Presentations

GLARE: GPU-Accelerated 3D CT Vision–Language Reasoning (P81268) Youngung Han, Junsu Lim, Eunseob Choi, Soo Yong Kim, Yi Kwan Ginny Wong, Nam-Joon Kim, Kyeonghun Kim (contributor) NVIDIA GTC 2026
RAPIDS: Real-Time Accelerated Dental Segmentation (P81266) Kyeonghun Kim, Youngung Han, Hyeonseok Jung, Gyeongmin Kim, Ken Ying-Kai Liao, Nam-Joon Kim NVIDIA GTC 2026
GRAVEX: GAN–Diffusion Representation for Counterfeit Analysis (P81285) Kyeonghun Kim, Eunseob Choi, Junsu Lim, Induk Um, Ken Ying-Kai Liao, Hyuk-jae Lee NVIDIA GTC 2026

Patents

Hyunjae Park, Seonghun Jeong, Kyeonghun Kim, Taehoon Lim, Dongil Kim, “Method for Refining Hyperspectral Images Using Deep Learning”, Korean Patent Application No.: 10-2024-0199713, Gnewsoft Co., Ltd., Dec. 2024

Book Chapters

Kyeonghun Kim (contributor), “Getting Started with Natural Language Processing”, Hongneung Science Publishing, Seoul, South Korea, 2026 - Contributed three chapters on foundational language models, autoencoders, and CNN applications with PyTorch implementation code

Research Highlights

HyperspectralMAE: Developed a proprietary foundation model achieving state-of-the-art (SOTA) performance in hyperspectral imagery classification (GNEWSOFT, 2024-2025)
Medical AI Collaborations: Leading research partnerships with Samsung Medical Center radiologists and NVIDIA researchers on diffusion-based medical imaging
IMSI Lab Website: Solely built the official IMSI Lab website providing centralized research platform
Deep Learning Education: Taught nationwide bootcamps for 450+ participants (2023) and 650+ participants (2024)

Technical Publications & Presentations

My research spans medical image analysis, generative AI, foundation models, and hyperspectral imaging. I have contributed to over 15 peer-reviewed publications and presented at major conferences including IEEE ISBI, ICEIC, APCCAS, MICCAI workshops, and NVIDIA GTC.

Research Impact: My work focuses on developing AI solutions that bridge the gap between cutting-edge research and clinical applications, with particular emphasis on medical imaging, synthetic data generation, and multimodal learning systems.