Hyeonwoo Kim is currently pursuing his M.S. degree in the Department of Computer Engineering at Kwangwoon University, Seoul, South Korea. His research interests include spiking neural networks (SNNs), deep learning, and AI for healthcare. His work on SNNs focuses on energy-efficient training and inference methods, aiming to reduce computational cost for deployment on resource-constrained hardware. In healthcare, he develops privacy-preserving bed-fall prediction systems for clinical environments, using physics-based simulation to generate synthetic training data and investigating how to bridge the gap between simulated and real-world data.

Awards

• Encouragement Award(장려상) - “Confidence-Aware SPACE: 효율적인 스파이킹 신경망을 위한 선택적 테스트 시점 적응”
  대한전자공학회 2026 인공지능논문학부생경진대회, Jun 2026