Kyeonghun Kim is a Research Assistant at IMSI Research Group, Seoul National University, specializing in medical imaging, generative AI, and multimodal deep learning applications. He leads the SUDAL Medical Imaging Team and has extensive experience in developing state-of-the-art AI solutions for medical image analysis, including 3D MRI synthesis, diffusion models, and vision-language models.

He is currently pursuing research on conditional abdominal MRI synthesis using segmentation-guided ControlNet pipelines and label-guided diffusion frameworks. His work involves close collaboration with Samsung Medical Center radiologists and NVIDIA researchers, focusing on clinically relevant AI applications in medical imaging.

Research Interests

  • Medical Image Analysis
  • Generative AI & Diffusion Models
  • 3D Medical Imaging
  • Multimodal Deep Learning
  • Computer Vision
  • Foundation Models
  • Hyperspectral Imaging

Education

  • MSc in Artificial Intelligence, 2024

    Kookmin University (GPA: 4.03/4.5)

  • BSc in Computer Science, 2022

    Hankyong National University (GPA: 4.12/4.5)

Recent Publications

  • 3D-LLDM: Label-Guided 3D Latent Diffusion Model, IEEE ISBI 2026
  • LOSA-NET: Localized and Scale-Adaptive Network, IEEE ISBI 2026
  • MMA-FORMER: Multi-Window Attention Transformer, IEEE ISBI 2026
  • NeoNet: Neoplastic End-to-End Original 3D MRI-Based Deep Learning Framework, AAAI 2026 Workshop
  • CATATPAD: Context-Aware Transfer Adaptation for Trajectory Prediction in Autonomous Driving, IEEE ICEIC 2026
  • MAESIL: Masked Autoencoder for Enhanced Self-supervised Medical Image Learning, IEEE ICEIC 2026
  • CIPHER: Counterfeit Image Pattern High-level Examination via Representation, IEEE ICCE-Asia 2025
  • FOSCU: Feasibility of Synthetic MRI Generation via Duo-Diffusion Models, IEEE APCCAS 2025
  • Boundary Guidance for Efficient 3D CT Vision–Language Reasoning, MICCAI 2025 Workshop
  • Automated Dental Caries Segmentation in Panoramic Radiographs Using Dual-Stage Deep Learning, MICCAI 2025 Workshop

Professional Experience

  • AI Researcher at GNEWSOFT (Oct. 2024 – Present)
  • Medical Imaging Team Lead at OUTTA (Jul. 2023 – Present)
  • AI Researcher at Weatherpia (Mar. 2024 – Aug. 2024)
  • Data Scientist at LG Uplus (Jan. 2024 – Mar. 2024)
  • AI Instructor at SK Telecom (Dec. 2023)
  • AI Software Engineer at AI O2O Inc. (Aug. 2023– Dec. 2023)
  • Data Analyst at OESON (Jan. 2023– Mar. 2023)
  • Software Engineer at NuriFlex Holdings Inc. (Nov. 2021– Dec. 2022)
  • Junior Developer at AST Global (Oct. 2020– Apr. 2021)

Latest

  • February 2026: Selected for presentation at IEEE ICEIC 2026
  • January 2026: Accepted paper on MAESIL for enhanced self-supervised medical image learning
  • December 2025: Collaboration started with Samsung Medical Center on AI-driven radiology solutions
  • November 2025: 3D-LLDM paper accepted at IEEE ISBI 2025
  • October 2025: Joined GNEWSOFT as AI Researcher
  • September 2025: FOSCU paper accepted at IEEE APCCAS 2025

Key Achievements

  • Built the official IMSI Research Group website from ground up
  • Developed HyperspectralMAE foundation model achieving SOTA performance
  • Led deep learning bootcamps for 450+ participants (2023) and 650+ participants (2024)
  • Collaboration with NVIDIA researchers on medical AI projects
  • Multiple publications in top-tier medical imaging conferences