AI and ML for Next-Generation Wireless Communications and Networking (AI4NextG @ NeurIPS’25)

The field of wireless communications and networking is undergoing a paradigm shift, driven by the growing potential of Artificial Intelligence (AI) and Machine Learning (ML) to redefine traditional system design principles. This workshop aims to catalyze interest and foster collaboration between the AI/ML and wireless communications communities. The timing of this workshop is especially significant, as the next-generation (NextG) wireless standardization efforts (such as 6G and WiFi 9) are just getting started, with AI-native technologies expected to play a central role across all aspects of the wireless ecosystem – from radio access to network management and edge intelligence. NextG represents a foundational shift in global infrastructure, enabling ultra-fast, low-latency, and intelligent connectivity that will power future applications in AI, robotics, immersive environments, and autonomous systems. These technologies offer unprecedented opportunities to both drive and benefit many applications, from healthcare and transportation to industrial automation and environmental monitoring. The economic and societal implications are vast: NextG networks will underlie trillions in global GDP impact, bridge digital divides, and shape how billions of people interact with technology and each other in the decades to come.

Despite the clear promise, a significant disconnect exists between the AI/ML and wireless research communities. AI/ML experts often lack an understanding of the unique physical, algorithmic, and architectural constraints inherent in wireless systems, while wireless researchers tend to adopt generic, off-the-shelf AI/ML models that are not optimized for the intricacies of wireless environments. Wireless environments are inherently dynamic, high-dimensional, and partially observable. These unique characteristics make them ideal testbeds for developing robust learning algorithms, particularly in areas like online learning, reinforcement learning, and in-context learning. At the same time, AI/ML techniques are becoming essential for managing the growing complexity of modern wireless networks, including resource allocation, interference mitigation, and cross-layer optimization. Bridging the gap between the two communities is not only necessary for meaningful technological advances but also critical for realizing the full societal impact of intelligent wireless systems.

This workshop aims to bring together researchers and practitioners at the intersection of artificial intelligence (AI), machine learning (ML), and wireless to address the unique challenges and opportunities posed by Next-Generation (NextG) wireless systems. As the 6G era begins to take shape, AI-native designs have emerged as a cornerstone of wireless innovation, with the potential to transform the performance, efficiency, and adaptability of communication systems. The integration of AI/ML is poised to influence every layer of the network stack, from physical-layer signal processing to network control and resource management.