Xianpo Ni
Papers
1
Total Citations
2
H-Index
1
About
Xianpo Ni is a leading researcher in the field of edge AI hardware reliability, with a focus on fault-tolerant architectures for streaming convolutional engines. His work addresses the critical challenge of ensuring dependable operation in resource-constrained edge devices—such as image sensors, drones, and wearable technology—where permanent faults can compromise system integrity. Ni’s most-cited paper, "Resource-Aware Online Permanent Fault Detection Mechanism for Streaming Convolution Engine in Edge AI Accelerators" (2023), introduces an innovative, lightweight detection framework that balances fault coverage with minimal hardware overhead. This contribution is pivotal for enabling robust, real-time AI inference in safety-critical applications like remote sensing and robotics. With growing citation impact, Ni’s research bridges the gap between high-performance edge computing and the stringent reliability demands of modern autonomous systems. His work not only advances the theoretical understanding of fault tolerance but also provides practical, resource-efficient solutions for next-generation AI accelerators, making him a key figure in the evolution of dependable edge intelligence.
Research Focus
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Top Papers
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