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About

Junliang Yang is a pioneering researcher at the intersection of neuromorphic electronics, artificial sensory systems, and advanced semiconductor devices. His work focuses on emulating biological sensory functions through innovative transistor architectures, with particular emphasis on pain perception, vision, and human-machine interaction. Yang's most celebrated contribution is his development of a sub-10 nm vertical organic/inorganic hybrid transistor capable of mimicking nociceptive pain signaling (186 citations), demonstrating remarkable miniaturization in bioinspired hardware. Building on this, he extended nociceptor emulation to transistor array networks capable of spatiotemporal pain-perception mapping, advancing the field toward practical neuromorphic implementations. His vision-inspired work is equally transformative: by engineering mixed-dimensional CsPbBr₃/MoS₂ heterojunction transistors, he replicated photoelectric visual adaptation with striking fidelity (158 citations), while his In-Ga-Zn-O memtransistors established frameworks for artificial vision systems in biological robotics (95 citations). More recently, Yang has expanded into wearable intelligence, developing machine learning-integrated printed strain sensors for gesture recognition and retina-inspired neuromorphic color classification. Collectively, his research—spanning nearly 600 total citations—has meaningfully advanced the hardware foundations of brain-inspired computing, positioning him as a significant voice in next-generation neuromorphic and bio-mimetic electronics.