Can LI

Can LI is an Assistant Professor in the Department of Electrical and Electronic Engineering at The University of Hong Kong. His research focuses on AI Hardware, Neuromorphic Computing, Non-volatile Memories, and Emerging Nanoelectronic Devices. Prior to joining HKU, Dr. Li worked at Hewlett Packard Labs in California, USA. He obtained his bachelor’s degree from Peking University and his Ph.D. from the University of Massachusetts Amherst. His work has led to 82 peer-reviewed publications, including 19 in Nature series journals. After joining HKU, he has received the National Natural Science Foundation of China Excellent Young Scientist Fund, the Hong Kong Research Grants Council Early Career Award, and the Croucher Tak Wah Mak Innovation Awards.

Can Li is a researcher at The University of Hong Kong, focusing on A.I. accelerator, neuromorphic computing, and non-volatile memories. His work explores the use of memristor crossbar arrays for efficient signal and image processing, in-situ learning, and pattern classification. Li's research includes memristor-based analog computation, neural network classification, and the development of true random number generators. He also investigates reinforcement learning, three-dimensional memristor circuits, and materials for resistance switching. His contributions span analog content-addressable memories, power-efficient optimization, and the integration of memristors in artificial neural networks. Li's research emphasizes the potential of memristors in advancing neuromorphic systems and machine learning hardware.