Neuromorphic Computing from the Computer Science Perspective: Algorithms and Applications

Abstract: 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, Katie will overview the field of neuromorphic from the computer science perspective. She will introduce spiking neural networks, as well as some of the most common algorithms used in the field. Finally, Katie will discuss the potential for using neuromorphic systems in real-world applications from scientific data analysis to autonomous vehicles.

Bio: Catherine (Katie) Schuman is an Assistant Professor in the Department of Electrical Engineering and Computer Science at the University of Tennessee (UT). She received her Ph.D. in Computer Science from UT. She received the Department of Energy Early Career Award in 2019.