Papers
1
Total Citations
8
H-Index
1
About
Yaning Shi is a researcher advancing the safety and intelligence of consumer electronics through innovative applications of artificial intelligence and power systems. Their primary research areas include DC arc fault detection, neural network architectures, and the integration of AI in power electronics for consumer devices. Shi’s most notable contribution is the development of a DC arc fault sensor employing a leftover gated recurrent neural network, a cutting-edge approach that enhances the reliability and safety of lithium battery-powered devices like sweeping robots, dining robots, and electric vehicles. This work, published in 2023 and garnering 8 citations, addresses the critical challenge of arc fault detection in consumer electronics, where increasing power demands heighten fire and failure risks. By leveraging recurrent neural networks for real-time monitoring, Shi’s research bridges the gap between artificial intelligence and practical power system safety, offering a scalable solution for next-generation smart devices. Their achievements underscore a commitment to making consumer electronics safer and more efficient, with potential impacts on the design of autonomous systems and energy storage technologies. Shi’s work is a valuable resource for students and researchers exploring AI-driven fault diagnosis and power electronics integration.
Research Focus
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Top Papers
- 1