Xiaohan Wu

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About

Xiaohan Wu is a leading researcher in neuromorphic computing and advanced optoelectronic devices, with a focus on developing bio-inspired hardware for next-generation artificial intelligence. Their most-cited work, "Floating-gate photosensitive synaptic transistors with tunable functions for neuromorphic computing" (2020, 26 citations), introduces a novel device architecture that mimics synaptic plasticity by integrating floating-gate structures with photosensitivity. This breakthrough enables tunable, light-responsive synaptic functions, offering a pathway toward energy-efficient, parallel-processing neuromorphic systems that can adapt to visual stimuli. Wu’s contributions bridge the gap between photonics and neural networks, demonstrating how optical inputs can modulate synaptic weights—a key step toward realizing brain-like computing. By engineering devices that combine memory, sensing, and processing, their research addresses critical challenges in von Neumann bottlenecks and power consumption. With growing recognition in the field, Wu’s work continues to inspire innovations in smart sensors, artificial retinas, and adaptive hardware, positioning them as a rising voice in the quest for intelligent, bio-inspired electronics.