This Collection aims to showcase original research that drives innovation in hardware and software for domain-specific optimization, advances federated and split learning to preserve privacy while enabling scalable collaborative training across edge nodes, and explores the integration of generative models into edge platforms through techniques such as model compression, quantization, and context-aware adaptive inference.