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Abstract Controlling electromagnetic wave propagation in multiple scattering systems is a challenging endeavor due to the extraordinary sensitivity generated by strong multi-path contributions at any given location. Overcoming such complexity has emerged as a central research theme in recent years, motivated both by a wide range of applications – from wireless communications and imaging to optical micromanipulations – and by the fundamental principles underlying these efforts. Here, we show that an in-situ manipulation of the myriad scattering events, achieved through time- and energy-efficient adjoint optimization (AO) methodologies, enables real time wave-driven functionalities such as targeted channel emission, coherent perfect absorption, and camouflage. Our paradigm shift exploits the highly multi-path nature of these complex environments, where repeated wave-scattering dramatically amplifies small local AO-informed system variations. Our approach can be immediately applied to in-door wireless technologies and incorporated into diverse wave-based frameworks including imaging, power electronic and optical neural networks. 

Controlling wave propagation in complex environments is a central challenge across wireless communications, imaging, and acoustics, where multiple scattering and interference obscure direct transmission paths. Coherent wavefront shaping enables precise energy delivery but typically requires full knowledge of the medium. Here, we introduce a universal statistical framework for targeted mode transport (TMT) that circumvents this limitation and validate it on various platforms including microwave networks, two-dimensional chaotic cavities, and three-dimensional reverberation chambers. TMT quantifies the efficiency of transferring energy between specified input and output channels in multimode wave-chaotic systems. We develop a diagrammatic theory that predicts the eigenvalue distribution of the TMT operator and identifies the macroscopic parameters—coupling strength, absorption, and channel control—that govern performance. The theory provides explicit bounds for optimal TMT wavefronts and captures phenomena like statistical transmission gaps and reflectionless states. These findings establish design principles for energy delivery and information transfer in complex environments, with broad implications for adaptive signal processing and wave-based technologies.