Neuromorphic Chips at the Intersection of Neuroscience, Electronics and AI
A special issue of Chips (ISSN 2674-0729).
Deadline for manuscript submissions: 30 April 2026 | Viewed by 97
Special Issue Editors
Interests: neuromorphic computing; brain-inspired computing; integrated circuits; machine learning hardware; FPGA; AI hardware acceleration; edge AI
Interests: sensor interface ICs; smart sensor systems; low-energy low-noise circuit design; sensor power management ICs; PVT-insensitive circuits and systems
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Neuromorphic chips—integrating concepts from neuroscience, electronics, and artificial intelligence—are revolutionizing the landscape of intelligent hardware and computing systems. By mimicking the neural structures and processes of the brain, neuromorphic devices offer new opportunities for efficient, adaptive, and low-power computation well-suited for edge AI, brain–computer interfaces, robotics, sensory processing, and more.
Recent advances in device technologies, circuit architectures, and computational models have enabled the development of neuromorphic systems that can process information in real time, adapt to changing environments, and learn from experience—just like biological brains. These innovations bridge the gap between neuroscience-inspired algorithms and scalable silicon implementations, fostering a new generation of chips that combine the best of biological and artificial intelligence.
This Special Issue aims to showcase recent breakthroughs in neuromorphic hardware and systems at the intersection of neuroscience, electronics, and AI. We welcome submissions covering innovative circuit and system designs, emerging device technologies, brain-inspired algorithms, in-memory and event-driven computing, sensory processing hardware, and real-world applications of neuromorphic chips. We particularly encourage interdisciplinary works that highlight the synergy among neuroscience, microelectronics, and artificial intelligence.
We look forward to your contributions that will drive the future of intelligent, brain-inspired hardware.
Dr. Liangshun Wu
Dr. Pak Kwong Chan
Guest Editors
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Chips is an international peer-reviewed open access quarterly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- neuromorphic computing
- integrated circuits
- brain-inspired computing
- analog and mixed-signal IC design
- in-memory computing
- AI hardware
- sensor interfaces
- edge computing
- memristive devices
- spiking neural networks
- low-power design
- machine learning accelerators
- biomedical circuits
- IoT hardware
- bio-sensing chips
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