The rise of memristors as artificial synapses and neurons provides a new approach in developing a neuromorphic hardware. A memristor-based neuromorphic processor would “compute by physics” which uses intrinsic device properties as computing principles and implements circuits and architectures based on biological inspirations. In this talk, I will first introduce the promises and challenges of memristors for neuromorphic computing. I will then discuss our efforts in addressing some fundamental device challenges of memristors and present our new concept in designing memristor computing arrays. Finally, I will conclude my talk with some brief discussions into future research directions.
Dr. Peng Lin is a Postdoc Associate in Prof. Jeehwan Kim’s group at Massachusetts Institute of Technology (MIT). He received his PhD in Electrical and Computer Engineering from University of Massachusetts Amherst in 2017. His current research focuses on neuromorphic computing and heterogeneously integrated systems, emphasizing on combining novel nanoelectronics device concept, advanced nanofabrication methods and brain-inspired computing paradigms to build functional neuromorphic hardware towards real-world applications. To date, Dr. Lin has published more than 30 papers in top peer-reviewed journals, such as Nature Electronics, Nature Nanotechnology, Nature Machine Intelligence, etc.