Brain Inspired Large Models with Spiking Neural Networks

Professor Guoqi Li
Institute of Automation, Chinese Academy of Sciences, China

Brain-inspired intelligence focuses on technologies inspired by the information processing mechanism of the human brain, based on the structure and function of neurons and neural circuits, and it aims to build computing systems with more general artificial intelligence. In recent years, spiking neural networks (SNNs) have approached the mainstream network performance of traditional deep learning in general scenarios, showing the potential to lead future intelligent technologies. This report introduces the models, algorithms of SNNs and their deployment on Brain inspired chips, as well as the research progress of large models based on SNNs.

Biosketch

Guoqi Li is currently a Full Professor with the Institute of Automation, Chinese Academy of Sciences. His research focuses on Brain-inspired Computing and Brain Inspired Intelligence. He has authored or co-authored over 200 papers in prestigious journals and top AI conferences. His papers have been cited more than 11000 times according to Google Scholar. Prof. Li has actively contributed to various professional services, including serving as a Tutorial Chair, an International Technical Program Committee Member, a PC member, a Publication Chair, a Track Chair, and a workshop chair for several international conferences. He holds positions as an Associate Editor for IEEE TNNLS, IEEE TCDS, Neuromorphic Computing and Engineering. He was honored with the Outstanding Young Talent Award from the Beijing Natural Science Foundation in 2021, and was selected to participate in the Hundred Talents Program of the Chinese Academy of Sciences in 2022. In 2023, Prof. Li was awarded the National Science Foundation for Distinguished Young Scholars of China.