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Neuromorphic Computing and Engineering - Institute of Physics | 2024 Impact factor: 6.1 | Cite Score: 9.2 | Q1

neuromorphic-computing-and-engineering.jpg

Neuromorphic Computing and Engineering - Institute of Physics | 2024 Impact factor: 6.1 | Cite Score: 9.2 | Q1

  • About this Journal:
  • Neuromorphic Computing and Engineering is a peer-reviewed, interdisciplinary journal focusing on the design, development, and application of neuromorphic systems inspired by the structure and function of biological neural networks.Neuromorphic Computing and Engineering is a multidisciplinary, open access journal publishing cutting edge research on the design, development and application of artificial neural networks and systems from both a hardware and computational perspective. For detailed information about subject coverage see the About the journal section.
  • Published by IOP Publishing, the journal provides a platform for cutting-edge research that bridges neuroscience, computer engineering, materials science, and artificial intelligence.
  • It features original research articles, reviews, perspectives, and technological breakthroughs related to energy-efficient computation, brain-inspired hardware, and next-generation intelligent systems.
  • The journal encourages contributions from researchers in neuromorphic engineering, cognitive computing, hardware design, computational neuroscience, and emerging memory technologies.

  • Editor-in-Chief:  Giacomo Indiveri

  • Scope of the Journal:
  • Neuromorphic devices, circuits, and architectures inspired by neural systems.
  • Brain-inspired algorithms for machine learning, pattern recognition, and adaptive control.
  • Spiking neural networks (SNNs), event-driven computation, and low-power AI models.
  • Emerging materials and devices for neuromorphic hardware (e.g., memristors, phase-change memory, resistive RAM).
  • Hybrid neuro-computational systems combining biological and artificial components.
  • Neuromorphic sensors, robotics, edge computing, and autonomous systems.
  • Hardware-software co-design for energy-efficient AI and real-time processing.
  • Computational neuroscience models supporting neuromorphic engineering.
  • Benchmarking, performance evaluation, and applications of neuromorphic technologies in real-world environments.
  • Latest Research Topics for PhD in Computer Science
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  • Latest Research Topics for PhD in Machine Learning
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  • Latest Research Topics for PhD in Artificial Intelligence
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  • Print ISSN:  26344386

    Electronic ISSN:  

  • Abstracting and Indexing:  Scopus

  • Imapct Factor 2024:  6.1

  • Subject Area and Category:  Artificial Intelligence, Hardware and Architecture,Electrical and Electronic Engineering

  • Publication Frequency:  

  • H Index:  19

  • Best Quartile:

    Q1:  Artificial Intelligence

    Q2:  

    Q3:  

    Q4:  

  • Cite Score:  9.2

  • SNIP:  1.505

  • Journal Rank(SJR):  1.548