Seong Tae Kim

Seong Tae Kim is a Professor at Kyung Hee University's Department of Biomedical Engineering. He previously held affiliations at the Technical University of Munich (Germany) and KAIST's Image and Video Systems Laboratory in South Korea. His research focuses on computer vision, medical imaging, and AI applications in healthcare.

Kim's work emphasizes explainable AI, neural network interpretability, and deep learning for medical diagnosis. He has contributed to advancements in knowledge graph-based reasoning, video object segmentation, and generative models for medical data synthesis. His research often bridges computer vision techniques with biomedical applications, such as cancer diagnosis and surgical phase recognition.

Over 100 publications since 2003 highlight his expertise in neural networks, federated learning, and robust training methods. Notable projects include developing frameworks for COVID-19 CT analysis and generating realistic biomedical datasets. He collaborates widely with institutions like the Max Planck Institute for Informatics (via Nassir Navab's lab) and Samsung Research.

Current research interests include interpretable machine learning models, longitudinal medical image analysis, and AI-driven healthcare solutions. His work frequently appears in top conferences like CVPR, MICCAI, and ECCV.