Papers
3
Total Citations
16
H-Index
3
About
Sungho Suh is at the forefront of integrating artificial intelligence with industrial safety and automation, specializing in computer vision and wearable sensor technologies for manufacturing environments. His research focuses on two critical pillars of Industry 5.0: enhancing worker safety through human activity recognition and enabling seamless human–robot interaction. Suh’s most influential work, “Object Detection for Human–Robot Interaction and Worker Assistance Systems” (2023, 7 citations), establishes foundational frameworks for deploying real-time detection algorithms on production lines, addressing unique challenges like occlusion and dynamic lighting. He further advances the field with “TSAK: Two-Stage Semantic-Aware Knowledge Distillation” (2024, 5 citations), a novel optimization technique that efficiently compresses deep learning models for wearable devices without sacrificing accuracy—a breakthrough for resource-constrained industrial settings. His complementary study on wearable sensor-based human activity recognition (2023, 4 citations) directly contributes to proactive worker safety monitoring. Collectively, Suh’s work bridges the gap between cutting-edge AI and practical industrial deployment, earning recognition for its direct impact on reducing workplace hazards while improving productivity. His research is essential reading for engineers and researchers developing intelligent, human-centric manufacturing systems.
Research Focus
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