Neuromorphic computing is a popular technology for the future of computing. Much of the focus in neuromorphic computing research and development has focused on new architectures, devices, and materials, rather than in the software, algorithms, and applications of these systems. In this talk, I will overview the field of neuromorphic from the computer science perspective. I will give an introduction to spiking neural networks, as well as some of the most common algorithms used in the field. Finally, I will discuss the potential for using neuromorphic systems in real-world applications from scientific data analysis to autonomous vehicles.
Biosketch:
Catherine (Katie) Schuman is an assistant professor at the University of Tennessee, Knoxville, specializing in neuromorphic computing and spiking neural networks. With a Ph.D. in computer science from UT and research experience at Oak Ridge National Laboratory, she has published widely and received the Department of Energy Early Career Award. Dr. Schuman is recognized for her innovative work at the intersection of artificial intelligence, hardware, and brain-inspired computing.