Wireless signals have long been a cornerstone for many communication-based applications, from mobile cellular systems to navigation. This project aims to use wireless signals in a new direction, i.e., computation, particularly for machines interacting with each other wirelessly, with the ultimate goal of faster computation for fast decision-making, learning, and coordination. To this end, the project plans to use the wireless medium as a computational substrate, i.e., over-the-air computation (OAC), to perform underlying calculations in various applications by harnessing the additive nature of electromagnetic waveforms in the wireless medium. The project plans to answer the fundamental research questions on the reliability, scalability, and feasibility of OAC with three interrelated research thrusts. The foundations of OAC for large-scale systems will be established by designing and advancing (1) reliable OAC schemes that are robust against distortion in wireless channels, impairments, and noise through non-coherent waveforms compatible with continuous functions, new error-correction codes based on modulo-lattice modulation and modulation-on-zeros, and analytical over-the-air computable function expressions based on Kolmogorov-Arnold superposition theorem; (2) scalable OAC frameworks for decentralized optimization, consensus for networked robotics and control systems under latency constraints, and distributed machine learning architectures over wireless networks; (3) meth