Catherine D. Schuman

Oak Ridge National Laboratory, University of Tennessee at Knoxville

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About

Catherine D. Schuman is a leading researcher in neuromorphic computing, with a focus on developing brain-inspired hardware and algorithms for low-power, edge-based control systems. Her major contributions center on the creation and application of the Dynamic Adaptive Neural Network Array (DANNA) and its successor, DANNA2, which are digital spiking neuromorphic processors designed for autonomous robotics. Schuman’s work demonstrates the practical deployment of these systems in real-world scenarios, such as the NeoN robot for obstacle avoidance and navigation (42 citations) and the GRANT platform for ground-roaming targeting (5 citations). She also explores the trade-offs between evolutionary and imitation learning for neuromorphic control at the edge (21 citations), highlighting her impact on efficient AI. Notably, her recent research extends into event-based vision with the Event Detection Pixel Sensor using phase transition materials (2025), pushing the boundaries of low-latency imaging. As a core member of the TENNLab at the University of Tennessee, Schuman’s innovations have paved the way for ultra-low-power autonomous systems, making her a pivotal figure in neuromorphic engineering and edge computing.