Many plasma systems and technologies, such as Hall thrusters for spacecraft propulsion, exhibit complex underlying physics that affect the global operation. When characterizing such systems in an experiment, obtaining full spatiotemporal maps of the involved state variables can be, thus, highly informative. However, this goal is not practically realizable because of various experimental limitations, e.g., spatial resolution of the employed diagnostics, and geometrical accessibility constraints. Therefore, it is greatly desirable to have the capability to reconstruct from low-dimensional time history measurements the full high-dimensional states of the plasma system. Compressed sensing is a signal processing technique that can answer this crucial need. The compressed sensing framework is applicable in a numerical simulation context as well, establishing a “super-resolution” mapping between a low- and a high-resolution simulation, thus, enabling the recovery of detailed features below the simulation’s grid size. However, existing compressed sensing approaches have several limitations that restrict their effective applicability to complex physical systems like plasma technologies. These include the need for abundant sensor measurements and a principled sensor placement. In this paper, we demonstrate the novel Shallow Recurrent Decoder (SHRED) architecture as a highly promising approach for compressed sensing and super-resolution enhancement. In terms of compressed sensing, we show that SHRED can reconstruct full high-dimensional state vector of a plasma system (all plasma properties) from minimal system information. This minimal information can consist of three finite time history measurements of either local values of a plasma property or the global properties (spatially averaged or performance parameters). Toward super-resolution enhancement, we illustrate the effectiveness of SHRED, and provide some perspectives on how this architecture can be integrated within the loop of the reduced-order particle-in-cell (PIC) scheme to further improve the cost-efficiency of this powerful kinetic plasma simulation tool.