The spiking neural network (SNN), where the coding scheme is based on the spike timing of neurons, has nowadays attracted tremendous research interests for their potential applications in many fields of artificial intelligence. The development of SNN could be roughly divided into two parts: 1) Hardware: design and fabrication of artificial neurons and synapses; 2) Software: development of SNN algorithms and architectures.In this talk, we are going to show the fabrication of neuromorphic devices and the associated design of spiking neural network. We highlight a hardware/software codesign approach of SNN.

Yuhui He. He received his B.S. and Ph.D from Dept. Microelectronics, Peking Univ. in 2003 and 2009 respectively. After that he first worked in Inst. Microelectronics, Chinese Academy of Sciences and then in Institute pf Scientific & Industrial Research, Osaka University respectively. In 2015, he joined School of Optical & Electronic Information, Huazhong University of Science & Technology as a full professor, and got funding support by the “Thousand Talents Programfor Young Outstanding Scientists” of China.His research interests focus on interdisciplinaryfields between nanoelectronics and biology. Currently he is developing neuromorphic devices and spiking neural network.