Hao Chen

University of Chinese Academy of Sciences, City University of Hong Kong

Papers

Total Citations

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About

Hao Chen is a versatile researcher whose work spans two frontier domains: neuromorphic computing and multimodal computer vision. In neuromorphic electronics, Chen has pioneered the development of organic optoelectronic synapses capable of mimicking human auditory perception, achieving a landmark breakthrough in sound recognition across dimensions of volume, tone, and timbre — capabilities previously unrealized in bioinspired systems. This work, published in 2023 and already amassing 43 citations, positions Chen at the cutting edge of next-generation humanoid robotics and brain-inspired hardware. Complementing this, Chen has also made significant contributions to RGB-D salient object detection through the M³Net architecture, a sophisticated multi-scale, multi-path, multi-modal fusion network that advances how machines integrate visual and depth information for robotic perception tasks. Together, these contributions reflect a research vision that bridges materials science, artificial intelligence, and robotics — addressing how machines can be built to sense and interpret the world more like biological organisms. Chen's interdisciplinary reach, from organic semiconductors to deep learning architectures, makes their body of work particularly valuable for students and researchers working at the intersection of neuromorphic engineering and intelligent perception systems.