Papers
3
Total Citations
21
H-Index
2
About
Ashley DeMange’s research sits at the intersection of neuromorphic computing, autonomous systems, and cognitive robotics, with a focus on translating biological principles into efficient machine intelligence. Her most cited work, “Associative Memory in Spiking Neural Network Form Implemented on Neuromorphic Hardware” (2020, 15 citations), pioneers the implementation of cognitive algorithms on neuromorphic hardware, advancing the goal of creating autonomous artificial agents that operate with brain-like efficiency. DeMange also tackles the computational bottlenecks of robotic navigation in “An Implementation of Simultaneous Localization and Mapping Using Dynamic Field Theory” (2021), proposing a lower-cost SLAM approach that reduces memory overhead. Beyond technical contributions, she champions interdisciplinary education through “From Lab to Internship and Back Again” (2019), which outlines a research and development ecosystem integrating AI, biology, psychology, and robotics. This work reflects her commitment to bridging academic research with real-world application. With a growing citation impact and a portfolio that spans hardware, algorithms, and pedagogy, DeMange is shaping how autonomous systems learn, navigate, and evolve—making her a compelling figure for students exploring the future of embodied AI.
Research Focus
Key Achievements
Top Papers
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