Track 9

Track 9. RF, Analog, and Mixed-Signal Circuits for Communications​​​

Chair: Kazuyuki Wada, Meiji University, Japan​

This track focuses on advanced integrated circuit technologies for artificial intelligence and machine learning applications. It explores novel architectures, circuit designs, and hardware–software co-design approaches that enable efficient AI computation. Topics include AI accelerators, neuromorphic and in-memory computing, low-power and high-performance IC design, and emerging device technologies. The track also addresses challenges in scalability, energy efficiency, and reliability for edge and data-center AI systems. By tightly integrating algorithms with hardware innovation, advanced ICs can significantly improve computing efficiency and performance. Contributions are welcomed on theoretical analysis, design methodologies, and practical implementations that support intelligent computing for next-generation AI and machine learning systems.

 Submission Link: https://easychair.org/conferences/?conf=icccas2026
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Track Chair Introduction

 

Kazuyuki Wada, Meiji University, Japan

 

Biography: TBA...