Modern Circuits and Systems Technologies (MOCAST) on Machine Learning Applications in Communications and Electronics,

The proliferation of data-intensive applications, from 5G/6G wireless networks to the Internet of Things (IoT), is driving a paradigm shift in the design and operation of circuits and systems. Traditional methodologies, based on manual optimization and empirical modeling, are becoming increasingly insufficient to meet the demands for higher performance, efficiency, and adaptability. This article provides a comprehensive overview of how machine learning (ML) and artificial intelligence (AI) are being leveraged to address these challenges, with a focus on topics discussed at the International Conference on Modern Circuits and Systems Technologies (MOCAST). We review key applications, including ML-driven optimization for integrated circuit (IC) design, intelligent signal processing in communication systems, and predictive maintenance in deployed electronic devices. The paper highlights how ML techniques—such as deep neural networks, reinforcement learning, and supervised learning—are enabling new levels of automation, performance, and reliability, paving the way for the next generation of intelligent electronic and communication systems.