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Xinming Shi

School of Electronics, Electrical Engineering and Computer Science

Xinming Shi

School of Electronics, Electrical Engineering and Computer Science

Inspired by the human brain, the development of brain-inspired intelligence is a rapidly expanding area in AI. Facing the constraints of traditional von Neumann architectures and the diminishing of Moore's Law, the computing performance of the intelligent hardware needs to be continuously improved. We delve into devices, algorithms, circuits, and architecture, focusing on the use of brain-inspired learning, memory, and evolution in designing software algorithms and hardware, targeting applications in edge computing, robotics, and large language models, including:

Neuromorphic Computing Hardware & Software
Evolutionary Learning
Trustworthy Brain-inspired Intelligence

Contact info

Research Interests

We are actively seeking individuals with strong programming and circuit design skills to tackle challenges at the intersection of neuromorphic computing and computational intelligence. If you are interested, we have multiple PhD, Joint PhD, Part-time PhD, RA, and Visiting Scholar positions available. Our research focuses on the following prospective topics: