š Hi! Iām Junhyeok Lee, a Master student at the
AIMS Lab,
Kyung Hee University.
My current research focuses on
Multimodal Medical Artificial Intelligence and
Neuroimaging.
I am also deeply interested in
Anomaly Detection,
Generative Models, and
Embodied Agent.
Feel free to explore my work and research!
š Publications
Disparities in Accelerated Brain Aging in Recent-onset and Chronic Schizophrenia
Sung Woo Joo*, Junhyeok Lee*, Juhyuk Han, Minjae Kim, Yeonwoo Kim, Howook Lee, Young Tak Jo, Jaewook Shin, Jungsun Leeo, and Won Hee Leeo
Psychological Medicine, (IF = 5.9, Top 7.1%, Q1), Feb. 2025
REVECA: Adaptive Planning and Trajectory-based Validation in Cooperative Language Agents Using Information Relevance and Relative Proximity
SeungWon Seo*, SeongRae Noh*, Junhyeok Lee, SooBin Lim, Won Hee Lee, and HyeongYeop Kango
Association for the Advancement of Artificial Intelligence (AAAI 2025), Feb. 25 - Mar. 4 2025, Philadelphia, Pennsylvania, United States
(Oral Presentation, Top 5%)
The impact of MRI data harmonization on brain age prediction
Junhyeok Lee, Juhyuk Han, Minjae Kim, Yeonwoo Kim, Tae-seong Kim and Won Hee Leeo
The 7th International Conference on Artificial Intelligence in Information and Communication (ICAIIC 2025), Fukuoka, Japan, Feb 18-21, 2025
Predicting brain age with global-local attention network from multimodal neuroimaging data: Accuracy, generalizability, and behavioral associations
SungHwan Moon, Junhyeok Lee, and Won Hee Leeo
Computers in Biology and Medicine, (IF = 7.0, Top 10%, Q1), Jan. 2025
Agentic LLM Workflows for Personalized User Experience Questionnaire Generation
Yeonwoo Kim, Junhyeok Lee, Juhyuk Han, Minjae Kim, Howook Lee, and Won Hee Leeo
IEEE International Conference on Consumer Electronics-Asia (ICCE-Asia) Nov. 2024
Unsupervised Anomaly Detection and Segmentation in Brain MRI: A Comparative Study
Junhyeok Lee, and Won Hee Leeo
Organization for Human Brain Mapping, (OHBM 2024) June. 2024
Anatomy-Aided Unsupervised Learning for Brain Anomaly Detection and Segmentation
Junhyeok Lee, and Won Hee Leeo
Korea Software Congress, (KSC 2023) Dec. 2023
(Awarded 1st Prize, Top 1)
Developing an Integrated Dashboard to Analyze Multimodal Data for User Experience Evaluation
Hyejeong Jo*, Junhyeok Lee*, Hye Won Park, Minjae Kim, Yeonwoo Kim, and Won Hee Leeo
IEEE International Conference on Consumer Electronics-Asia (ICCE-Asia) Oct. 2023
Brain Age Prediction: A Comparison between Machine Learning Models Using Brain Morphometric Data
Juhyuk Han, Seo Yeong Kim, Junhyeok Lee, and Won Hee Leeo
Sensors, (IF = 3.9, Top 29.4%, Q2), Oct. 2022
š Education
- M.E. in Software Convergence at Kyung Hee University, 2024.03 - recent
- B.E. in Software Convergence at Kyung Hee University, 2020.03 - 2024.02
š¼ Experience
-
KHU Global Ambassador in CES,
Office of Educational Innovation & Planning, KHU,
2023.11 - 2024.3
- On-site Dispatch to CES and Future Strategy Coverage
-
Undergraduate Research Intern,
Kyung Hee University
(AIMS Lab),
2022.12 - 2024.2
- Conducted research on text-based gesture animation generation
-
Department Student Council Vice President,
Software Convergence,
2021.03 - 2021.12
- Led departmental student council activities and organized various academic and social events
š Awards
-
2025 AAAI Student Scholarship (AAAI-25)
- Paper: REVECA: Adaptive Planning and Trajectory-based Validation in Cooperative Language Agents Using Information Relevance and Relative Proximity
š Teaching
- Graduate Thesis [SWCON40200], 2024.03 - 2024.12
- Software Convergence Capstone Design [SWCON40103], 2024.03 - 2024.12
- Data Anaylsis Capstone Design [SWCON32100], 2024.03 - 2024.12