Low-Power IC Design for Efficient AI
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".
Deadline for manuscript submissions: 20 October 2026 | Viewed by 1
Special Issue Editors
Interests: novel energy harvester; novel power management techniques and circuits; low-power sensor interfaces; low-power analog and mixed-signal circuits
Special Issues, Collections and Topics in MDPI journals
Interests: circuits; electronics; analog electronics; microelectronics spice simulation; cadence circuit simulation; CMOS; analog signal processing; VLSI technology
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The intersection of artificial intelligence and energy efficiency represents one of the most pressing challenges in modern semiconductor design. As AI workloads proliferate across edge devices, mobile platforms, and data centers, the demand for intelligent circuits that deliver computational power without proportional increases in energy consumption has become imperative.
This Special Issue seeks to highlight cutting-edge research and practical innovations in low-power integrated circuit design specifically tailored for AI applications. We invite submissions that advance our understanding of how to build smarter, leaner, and more efficient silicon.
Scope and Topics
We welcome original research, design methodologies, and case studies addressing (but not limited to) the following:
- Circuit-Level Innovations
- Ultra-low-voltage logic and memory architecture.
- Dynamic voltage and frequency scaling (DVFS) for AI accelerators.
- Novel transistor technologies and device-level optimizations.
- Architecture and System Design
- Specialized hardware for neural networks (TPUs, NPUs, neuromorphic chips).
- Power-aware datapath design for machine learning inference.
- Memory hierarchies optimized for AI workloads.
- Design Methodologies
- Low-power design techniques for deep learning accelerators.
- Trade-offs between accuracy, latency, and energy consumption.
- Quantization and sparsity exploitation at the silicon level.
- Application-Specific Solutions
- Edge AI processors for IoT and wearables.
- Energy-efficient training circuits.
- Multi-modal AI SoCs with heterogeneous computer cores.
- Measurement, Characterization, and Analysis
- Power profiling and benchmarking methodologies.
- Real-world case studies of deployed low-power AI systems.
- Comparative analyses of emerging architectures.
We welcome original technical papers, reviews, or industrial perspectives. All submissions undergo rigorous peer review by experts in low-power design and AI systems. We encourage interdisciplinary contributions from circuit designers, system architects, and AI researchers.
Dr. Anindita Paul
Prof. Dr. Jaime Ramirez-Angulo
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 250 words) can be sent to the Editorial Office for assessment.
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. Applied Sciences is an international peer-reviewed open access semimonthly 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 2400 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
- low-power
- integrated circuit
- design techniques
- AI
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