Han‐Seok Seo

Korea University, University of Arkansas at Fayetteville

Papers

Total Citations

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About

Han-Seok Seo is a rising researcher at the intersection of bio-inspired electronics and social intelligence, whose work bridges the gap between sensory systems and human behavior analysis. His primary research areas include self-classifying multifunctional sensors and social group activity recognition, where he has made pioneering contributions. Seo’s most notable work, the "Sensory Nervous System‐Inspired Self‐Classifying, Decoupled, Multifunctional Sensor with Resistive‐Capacitive Operation Using Silver Nanomaterials" (2024, 18 citations), introduces a groundbreaking approach to electronic skin that can autonomously discern stimuli without external circuitry—a leap toward truly intelligent prosthetics and robotics. He further advances artificial perception with "SoGAR: Self-Supervised Spatiotemporal Attention-Based Social Group Activity Recognition" (2025, 5 citations), which eliminates the need for extensive manual annotations in surveillance and human-robot interaction systems. By combining self-supervised learning with spatiotemporal attention mechanisms, Seo addresses a critical bottleneck in behavioral analysis. His work has garnered early recognition for its novelty and practical potential, positioning him as a key contributor to both sensory electronics and AI-driven social understanding.