About
Welcome, and thank you for visiting my homepage.
I am currently a student at CHA University Graduate School of Medicine, with a strong academic interest in artificial intelligence and its applications in medicine. Prior to pursuing medical training, I received my master’s degree from Kim Jaechul Graduate School of Artificial Intelligence at KAIST, under the supervision of Professor Juho Lee, following a bachelor’s degree in Electrical Engineering, also from KAIST.
During my master’s studies, I focused on generative models—particularly diffusion models and flow matching—with an emphasis on extending their applicability beyond image-based domains. Through this work, I developed a growing interest in AI-driven drug discovery and protein generation. These experiences ultimately shaped my broader vision of artificial intelligence as a transformative force in medicine and motivated my decision to pursue medical training.
I believe, as many do, that the integration of artificial intelligence into clinical practice will fundamentally expand the boundaries of medicine in the near future. I hope to contribute to this ongoing transformation as a clinician-scientist. I welcome any discussions on medical AI research, interdisciplinary collaboration, and the future role of artificial intelligence in clinical medicine.
Publications
ForestPersons: A Large-Scale Dataset for Under-Canopy Missing Person Detection
Deokyun Kim*, Jeongjun Lee*, Jungwon Choi*, Jonggeon Park*, Giyoung Lee, Yookyung Kim, Myungseok Ki, Juho Lee, Jihun Cha
The Fourteenth International Conference on Learning Representations (ICLR), 2026
[Paper]
[HuggingFace]
Axial Neural Networks for Dimension-Free Foundation Models
Hyunsu Kim, Jonggeon Park, Joan Bruna, Hongseok Yang, Juho Lee
The Thirty-ninth Annual Conference on Neural Information Processing Systems (NeurIPS), 2025
(Spotlight Presentation; Top 3.2%)
[Paper]
[GitHub]
Ensemble Distribution Distillation via Flow Matching
Jonggeon Park*, Giung Nam*, Hyunsu Kim, Jongmin Yoon, Juho Lee
Forty-second International Conference on Machine Learning (ICML), 2025
[Paper]
[GitHub]
Stabilizing the Training of Consistency Models with Score Guidance
Jeongjun Lee*, Jonggeon Park*, Jongmin Yoon, Juho Lee
ICML 2024 Workshop on Structured Probabilistic Inference & Generative Modeling, 2024
[Paper]
[GitHub]