Papers
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Total Citations
2
H-Index
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About
Yuan Liang is pioneering the intersection of neuromorphic engineering and space exploration, with a focus on radiation-hardened vision systems for extreme environments. Their most-cited work introduces a groundbreaking radiation-hardened neuromorphic imager designed for space robotics, featuring self-healing spiking pixels that autonomously recover from radiation-induced damage. This fully spike-based vision system integrates a unified spiking neural network (USNN) with adaptive neurons and synapses, enabling robust, energy-efficient perception in harsh orbital or planetary conditions. By merging in-pixel resilience with neuromorphic computing, Liang’s prototype addresses a critical challenge in space missions: maintaining reliable visual sensing despite constant radiation exposure. Their contributions push the boundaries of bio-inspired hardware, offering a path toward autonomous, self-repairing robotic explorers. With 2 citations on this cutting-edge 2025 work, Liang’s research is gaining traction among engineers and scientists working on resilient AI for aerospace. Their achievements exemplify how neuromorphic principles can be harnessed for real-world, high-stakes applications, making their profile essential reading for students and researchers interested in the future of space robotics and radiation-tolerant computing.
Research Focus
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Top Papers
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