Be sure to read Prof. Rashmi Jha’s article, “Emerging Memory Devices Beyond Conventional Data Storage: Paving the Path for Energy-Efficient Brain-Inspired Computing,” in the spring 2023 issue of The Electrochemical Society Interface.
The article aims to address “limitations of the memory bandwidth of machine learning and artificial intelligence algorithms, and the necessity of novel computing architectures to overcome this limitation” (Jha, 2023).
Rashmi Jha is Professor of Electrical Engineering and Computer Science at the University of Cincinnati (UC). Her research interests are in artificial intelligence; low-power neuromorphic systems; CMOS and other emerging logic and memory devices; on-die sensors; cross-technology heterogenous integration and modeling; cybersecurity with an emphasis on hardware security; additive, flexible, and wearable electronics; nanoelectronics; neuroscience and neuroelectronics; and bio-inspired computing and systems. (more…)