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Talk Abstract: Neuromorphic computing is a popular technology for the future of computing because it natively implements AI operations and has the potential for extreme energy efficiency. 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.
Speaker: Catherine (Katie) Schuman, Assistant Professor, Department of Electrical Engineering and Computer Science, University of Tennessee.
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Catherine (Katie) Schuman is a researcher in neuromorphic computing and an assistant professor in the Department of Electrical Engineering and Computer Science at the University of Tennessee.