Yusung Chu

I am an Assistant Professor in the Department of Biomedical Engineering at Konyang University. My research focuses on medical artificial intelligence, with particular interests in medical image analysis, dermatology AI, multimodal learning, generative AI, and robust and fair AI.

Medical AI

Education

  • Ph.D. in Biomedical Engineering, Yonsei University, South Korea, 2019–2024
    Advisor: Prof. Sejung Yang
  • B.S. in Biomedical Engineering, Yonsei University, South Korea, 2014–2020

Professional Experience

  • Assistant Professor, Konyang University, South Korea, Sep. 2026–Present
    Department of Biomedical Engineering
  • Postdoctoral Researcher, Yonsei University Wonju College of Medicine, South Korea, Sep. 2024–Aug. 2026
    Precision Medicine
  • Visiting Scholar, University of North Carolina at Chapel Hill, NC, U.S.A., May 2026–Aug. 2026
    Department of Psychiatry, School of Medicine

Research Interests

  • Deep learning-based diagnostic support systems for dermatology
  • Medical augmented intelligence for clinical decision support
  • Explainable AI and visual concept-based interpretation
  • Robust and fair medical AI across diverse data conditions
  • Generative AI and foundation models for medical imaging

Recent News

  • 2026.10 One Paper was accepted in BMC Medical Imaging.
  • 2026.9 Joined the Department of Biomedical Engineering at Konyang University as an Assistant Professor.
  • 2026.6 VL-RewardGen was accepted to MICCAI 2026.
  • 2026.6 One Paper was accepted in npj Digital Medicine.
  • 2026.3 One Paper was accepted in Journal der Deutschen Dermatologischen Gesellschaft.
VL-RewardGen overview
VL-RewardGen: Vision–Language Reward Driven Skin Lesion Image Generation.
Yusung Chu and Sejung Yang.
MICCAI 2026 (정보과학회 S급 최우수국제학술대회)
Frozen-to-FFPE generative AI overview
Translation of frozen sections into FFPE images for skin cancer resection margins using generative AI.
Sang-Hoon Lee*, Yu-Sung Chu*, Yosep Chong, Seong Min Hong, Eung Ho Choi, Seung-Phil Hong, Taeyeong Kim, Sejung Yang, and Minseob Eom.
npj Digital Medicine, 2026.
JCR 헬스케어 과학 분야 1위; IF: 18.0
Robust melanoma prediction overview
xf Class-Agnostic Feature-Learning-Based Deep-Learning Model for Robust Melanoma Prediction.
Yuseong Chu, Solam Lee, Byungho Oh, and Sejung Yang.
IEEE Journal of Biomedical and Health Informatics, 2025.
JCR 전산생물학 분야 상위 7.5%; IF: 7.7
Automated point defect analysis overview
Full automation of point defect detection in transition metal dichalcogenides through a dual mode deep learning algorithm.
Dong-Hwan Yang*, Yu-Seong Chu*, Odongo Francis Ngome Okello, Seung-Young Seo, Gunho Moon, Kwang Ho Kim, Moon-Ho Jo, Dongwon Shin, Teruyasu Mizoguchi, Sejung Yang, and Si-Young Choi.
Materials Horizons, 2024.
JCR 종합화학 분야 상위 11%; IF: 11.4
Breslow thickness prediction overview
Deep Learning Algorithms for Predicting Breslow Thickness from Dermoscopic Images of Acral Lentiginous Melanomas.
Yu Seong Chu*, Solam Lee*, Sang Gyun Lee, Kee Yang Chung, Mi Ryung Roh, Byung Ho Oh, and Sejung Yang.
Journal of Investigative Dermatology, 2022.
JCR 피부과 분야 상위 7.1%; IF: 7.0

Publications (International journals & conferences)

* Equal contribution. † Corresponding author.

Under Review / Submitted

  1. Prediction of pre-frailty and frailty in community-dwelling older adults using machine learning.
    Yusung Chu, Hunju Lee, Sangbaek Koh, Taesic Lee, and Sejung Yang. BMC Medical Informatics and Decision Making. Under review.
  2. DIST: Training-Free Dermoscopic Image Skin Tone Style Transfer with Lesion Preservation.
    Yusung Chu, Byungho Oh, and Sejung Yang. IEEE Journal of Biomedical and Health Informatics. Under review.
  3. High-Resolution CAM-Guided Weakly Supervised Skin Lesion Segmentation using FeatUp and SAM.
    Yusung Chu and Sejung Yang. Scientific Reports. Under review.
  4. Skin-tone perception and diagnostic performance across skin-tone groups in dermatology vision-language models.
    Yusung Chu, Byungho Oh, and Sejung Yang. BMC Medical Informatics and Decision Making. Under review.

2026

  1. Dermoscopy-Dominant Correction Fusion for Multimodal Skin Lesion Classification.
    Yusung Chu and Sejung Yang. BMC Medical Imaging, 2026.
  2. Objective and Quantitative Assessment of Facial Vitiligo via AI-powered 3D Analysis for Diagnostic Support.
    Sena Lee, You Hyun Kim, Younghyun Park, Yerin Lee, Yusung Chu, Jae Joon Jeon, Solam Lee, and Sejung Yang. British Journal of Dermatology, 2026.
  3. Classification of Functional Movement Screening Scores and Incidence of Falls During Deep Squats among Logistics Service Workers Using Deep Learning.
    Ui-jae Hwang*, Yusung Chu*, Oh-yun Kwon, Hwa-ik Yoo, Junghun Han, and Sejung Yang. Scientific Reports, 2026.
  4. Translation of frozen sections into FFPE images for skin cancer resection margins using generative AI.
    Sang-Hoon Lee*, Yu-Sung Chu*, Yosep Chong, Seong Min Hong, Eung Ho Choi, Seung-Phil Hong, Taeyeong Kim, Sejung Yang, and Minseob Eom. npj Digital Medicine, 2026.
  5. VL-RewardGen: Vision–Language Reward Driven Skin Lesion Image Generation.
    Yusung Chu and Sejung Yang. Medical Image Computing and Computer Assisted Intervention (MICCAI) , 2026.
  6. AI-Assisted Diagnosis of Nail Unit Melanoma and Melanonychia Using Clinical Deep Learning Model.
    Yusung Chu, Sejung Yang, Jin-Woong Jung, Jun Young Kim, Joo Goon Kim, Hae June Sung, and Byungho Oh. Journal der Deutschen Dermatologischen Gesellschaft , 2026. Accepted.
  7. Development of a multi-task learning framework with gradnorm for precise wound tissue analysis.
    Hyunyoung Kang, Byungho Oh, Solam Lee, YuSung Chu, Jiye Kim, and Sejung Yang. PLOS ONE, 2026.

2025

  1. Identifying Gender-Specific Visual Bias Signals in Skin Lesion Classification.
    Heejae Lee, Sejung Yang, Yuseong Chu†, and Byungho Oh†. MICCAI Workshops, 2025. Best Poster Presentation Award.
  2. Evaluating the Trustworthiness of Foundation Models for Skin Lesion Segmentation.
    Yusung Chu, Byungho Oh, and Sejung Yang. ICCV Workshops, 2025.
  3. Classifying office workers with and without cervicogenic headache or neck and shoulder pain using posture-based deep learning models: a multicenter retrospective study.
    Ui-Jae Hwang, Junghun Han, Oh-Yun Kwon, Yu Seong Chu, and Sejung Yang. Frontiers in Pain Research, 2025.
  4. Vision-language foundation models for medical imaging: a review of current practices and innovations.
    Ji Seung Ryu, Hyunyoung Kang, Yuseong Chu, and Sejung Yang. Biomedical Engineering Letters, 2025.
  5. Class-Agnostic Feature-Learning-Based Deep-Learning Model for Robust Melanoma Prediction.
    Yuseong Chu, Solam Lee, Byungho Oh, and Sejung Yang. IEEE Journal of Biomedical and Health Informatics , 2025.
  6. Deep Learning Algorithms for Assessment of Post-Thyroidectomy Scar Subtype.
    Yuseong Chu*, Seung-Won Jung*, Solam Lee, Sang Gyun Lee, Yeon-Woo Heo, Sang-Hoon Lee, Hang-Seok Chang, Yong Sang Lee, Seok-Mo Kim, Sang Eun Lee, Byungho Oh, Mi Ryung Roh, and Sejung Yang. Dermatologic Therapy, 2025.

2024

  1. Atomistic Probing of Defect-Engineered 2H-MoTe2 Monolayers.
    Odongo Francis Ngome Okello, Dong-Hwan Yang, Seung-Young Seo, Jewook Park, Gunho Moon, Dongwon Shin, Yu-Seong Chu, Sejung Yang, Teruyasu Mizoguchi, Moon-Ho Jo, and Si-Young Choi. ACS Nano, 2024.
  2. Full automation of point defect detection in transition metal dichalcogenides through a dual mode deep learning algorithm.
    Dong-Hwan Yang*, Yu-Seong Chu*, Odongo Francis Ngome Okello, Seung-Young Seo, Gunho Moon, Kwang Ho Kim, Moon-Ho Jo, Dongwon Shin, Teruyasu Mizoguchi, Sejung Yang, and Si-Young Choi. Materials Horizons, 2024.

2023

  1. CoAt-Mixer: Self-attention deep learning framework for left ventricular hypertrophy using electrocardiography.
    Ji Seung Ryu, Solam Lee, Yuseong Chu, Min-Soo Ahn, Young Jun Park, and Sejung Yang. PLOS ONE, 2023.
  2. Deep Learning Algorithms for Estimation of Demographic and Anthropometric Features from Electrocardiograms.
    Ji Seung Ryu, Solam Lee, Yuseong Chu, Sang Baek Koh, Young Jun Park, Ju Yeong Lee, and Sejung Yang. Journal of Clinical Medicine, 2023.

2022

  1. Artificial Intelligence for Detection of Cardiovascular-Related Diseases from Wearable Devices: A Systematic Review and Meta-Analysis.
    Solam Lee*, Yuseong Chu*, Ji Seung Ryu, Young Jun Park, Sejung Yang, and Sang Baek Koh. Yonsei Medical Journal, 2022.
  2. Deep Learning Algorithms for Predicting Breslow Thickness from Dermoscopic Images of Acral Lentiginous Melanomas.
    Yu Seong Chu*, Solam Lee*, Sang Gyun Lee, Kee Yang Chung, Mi Ryung Roh, Byung Ho Oh, and Sejung Yang. Journal of Investigative Dermatology, 2022.

2021

  1. Atomic-level defect modulation and characterization methods in 2D materials.
    Odongo Francis Ngome Okello, Dong-Hwan Yang, Yu-Seong Chu, Sejung Yang, and Si-Young Choi. APL Materials, 2021.
  2. Deep learning models for the prediction of intraoperative hypotension.
    Solam Lee, Hyung-Chul Lee, Yu Seong Chu, Seung Woo Song, Gyo Jin Ahn, Hunju Lee, Sejung Yang, and Sang Baek Koh. British Journal of Anaesthesia, 2021.

2020

  1. Artificial Intelligence in Cutaneous Oncology.
    Yu Seong Chu, Hong Gi An, Byung Ho Oh, and Sejung Yang. Frontiers in Medicine, 2020.
  2. Augmented decision-making for acral lentiginous melanoma detection using deep convolutional neural networks.
    Solam Lee, Yuseong Chu, Sang Kyun Yoo, Sung Hee Choi, Sung Jay Choe, Sang Baek Koh, Kee Yang Chung, Lei Xing, Byung Ho Oh, and Sejung Yang. Journal of the European Academy of Dermatology and Venereology , 2020.

Grants & Fellowships

  • Postdoctoral Research Fellowship, National Research Foundation of Korea (NRF). Principal Investigator: Yusung Chu. Sep. 2025 – Aug. 2026. Approx. USD 44,500.
  • Postdoctoral Researcher Support Program, Yonsei University Wonju College of Medicine. Mar. 2025 – Aug. 2025. Approx. USD 5,200.
  • Postdoctoral Researcher Support Program, Yonsei University Wonju College of Medicine. Sep. 2024 – Feb. 2025. Approx. USD 5,200.

Honors & Awards

  • Best Poster Presentation Award, MICCAI Workshops, 2025. Corresponding author.
  • Yonsei University Graduate School Best Academic Paper Award, 2024. First author.
  • Yonsei Medical Journal Best Paper Award for the Best Published Manuscript in 2022–2023. First author.
  • Grand Award, Korea Society of Digital Health, 2023. First author.

Patents

  1. 생성적 대립 신경망(GAN, Generative Adversarial Network)을 활용한 주사투과전자현미경 영상에서의 노이즈 제거 방법.
    Korea Patent Registration No. 10-2826899, registered Jun. 25, 2025.
  2. 딥러닝을 이용한 흑색종 진단 방법, 장치 및 프로그램.
    Korea Patent Registration No. 10-2376717, registered Mar. 16, 2022.
  3. Method, Device and Program for Diagnosis of Melanoma Using Deep Learning.
    Korea Patent Registration No. 10-2297242, registered Aug. 27, 2021.
  4. METHOD FOR ANALYZING ATOMIC IMAGES OF LOW DIMENSIONAL MATERIALS.
    Korea Patent Registration No. 10-2253227, registered May 12, 2021.