Garrett S. Rose
Professor of Electrical Engineering and Computer Science
University of Tennessee
Seminar: Neuromorphic Computing Hardware Design
Abstract: The concept of neuromorphic systems is a "natural" candidate for emerging computer architectures. Neuromorphic computer architectures are inspired by biology in that their operation is based on our best understanding of the functionality of the mammalian brain. While artificial neural networks can be constructed from conventional electronic devices such as transistors, emerging nanoscale devices (e.g. memristors) exhibit properties particularly well suited for building high density, power-efficient neuromorphic systems. Rose will discuss his group's research, including how memristive devices can be exploited as synaptic elements in complex neural networks. This approach of "memristors as synapses" has been applied to several neuromorphic architectures. He will also discuss training methods for the memristor-based neuromorphic systems designed by his group.
About the Speaker: Garrett S. Rose in a professor in the Department of Electrical Engineering and Computer Science at the University of Tennessee, where he has been since 2014. He received the B.S. in Computer Engineering from Virginia Tech in 2001. He recceived the M.S. and Ph.D. degrees in Electrical Engineering from the University of Virginia in 2003 and 2006, respectively. From 2006 through 2011 he was an assistant professor with the Electrical and Computer Engineering Department at Polytechnic University (now NYU Polytechnic School of Engineering) in Brooklyn, NY. From 2011 through July 2014 he was a senior electronics engineer with the Air Force Research Laboratory, Information Directorate in Rome, NY. Throughout his career, his research interests have focused on nanoelectronic circuit design for a range of applications including reconfigurable computing, neuromorphic computing and hardware security.
Host: Mircea Stan, Virginia Microelectronics Consortium Professor, Electrical and Computer Engineering