Neuromorphic engineering/computing
- Submission status
- Closed
- Submission deadline
Neuromorphic computing is an area of engineering that seeks to emulate the biophysical architecture of our nervous system. Such models can take a variety of forms including hardware chips composed of ‘silicon neurons’, as well as software implementations of neural systems. Artificial neural systems have been previously successfully demonstrated, and are now inspiring a new generation of computing technologies that exploit the physics of computation present in biological neural systems.
This Collection brings together the latest results in the topic of neuromorphic engineering, spanning from the design of artificial neural systems to their experimental realisations.
Editors
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Ahmedullah Aziz
University of Tennessee Knoxville, USA
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Bhagwati Prasad
Indian Institute of Science, India
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J. Joshua Yang
University of Southern California, USA
Ahmedullah Aziz is an Assistant Professor of Electrical Engineering & Computer 
Science at the University of Tennessee, Knoxville, USA. His research interests include neuromorphic hardware, cryogenic electronics, and beyond CMOS device design. Dr. Aziz has been an Editorial Board Member for Scientific Reports since 2022.
Bhagwati Prasad is an Assistant Professor in the Department 
of Materials Engineering at the Indian Institute of Science, Bengaluru, India. His major research interest is related to spintronics, ferroelectrics, and magnetoelectric-based neuromorphic computing materials, and devices. Dr. Prasad has been an Editorial Board Member for Scientific Reports since 2022.
J. Joshua Yang is a Professor at the University o
f Southern California. His research interest is Post-CMOS materials and devices to enable non von Neumann hardware, architecture and algorithms. Dr. Yang was elected to IEEE fellow and NAI fellow for his contributions to resistive switching materials and neuromorphic computing. Dr. Yang has been an Editorial Board Member for Scientific Reports since 2018.
