معرفی
Catherine Schuman is an Assistant Professor in the Min H. Kao Department of Electrical Engineering and Computer Science at the University of Tennessee, Knoxville, part of the Tickle College of Engineering. Her work focuses on neuromorphic computing, spiking neural networks, and AI-driven hardware-software co-design. She holds a Ph.D. and B.S. in Computer Science and Mathematics from the University of Tennessee (2015 and 2010, respectively).
Research interests include neuromorphic systems, energy-efficient computing architectures, stochastic devices, and applications of neuromorphic computing in scientific domains like materials science and quantum materials. She emphasizes benchmarking frameworks (NeuroBench) and real-world applications such as radiation detection and control systems.
Her recent publications (2023-2025) highlight advancements in neuromorphic hardware-software co-design, spiking reinforcement learning frameworks, and neuromorphic implementations for scientific computing. Notable contributions include frameworks like SpikeRL, NeuroPong, and the RISP neuroprocessor, emphasizing open-source tools for embedded neuromorphic computing.
No scientific awards are explicitly listed in the provided information. She actively explores cross-disciplinary applications, including combustion control and materials discovery through AI-enhanced device design.
