Jingyong Su

Shenzhen Institute of Information Technology

Papers

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About

Jingyong Su is a researcher at the forefront of intelligent sensing and material recognition, with a particular focus on integrating transformer-based architectures into tactile and contact-driven perception systems. His most notable contribution, the 2025 paper "Transformer-based material recognition via short-time contact sensing," introduces a novel approach that leverages the power of transformer models to classify materials based on brief physical interactions. This work has already garnered 3 citations, signaling its early impact in the growing field of embodied AI and robotic perception. Su’s research bridges the gap between deep learning and physical sensing, enabling machines to identify materials—such as fabric, wood, or metal—through touch alone, a capability critical for applications in robotics, prosthetics, and human-machine interaction. By demonstrating that short, non-visual contact signals can be effectively processed by transformer architectures, he has opened new pathways for efficient, real-time material classification. His work stands out for its practical relevance and methodological innovation, offering a scalable solution that reduces reliance on visual data. For students and researchers exploring the intersection of machine learning and tactile sensing, Su’s contributions provide a compelling foundation for future advances in intelligent, context-aware systems.