Dynamic spectrum access (DSA) and multi-input multi-output (MIMO) technologies have received great attention in recent years. While the former is viewed as a new communications paradigm to improve the utilization of the licensed spectrum, the latter has already proven itself as a powerful signal processing technique for boosting spectral efficiency. Through channel sensing and/or database access, DSA devices, a.k.a. secondary users (SUs), can opportunistically communicate on temporarily available spectrum bands while avoiding interference with licensed users. By exploiting spatial diversity, MIMO enables two communicating devices to extend their reach, reduce their energy consumption, and/or increase the throughput. In a multi-user (multi-link) setting, MIMO offers significant benefits related to interference avoidance, beamforming/directionality, anti-jamming, and spatial reuse. The main goal of this project is to tightly integrate MIMO into DSA systems, considering optimizations at both the signal level (via adapting the precoding matrices) as well as the antenna level (via cognitive and reconfigurable antennas). Our research addresses the technical challenges associated with operating MIMO/DSA in both centralized and distributed environments. The research agenda includes: (i) Novel cognitive MIMO (CMIMO) adaptation and resource allocation techniques, (ii) reconfigurable and cognitive antennas for supporting simultaneous transmit and sense (STAS) and full-duplex CMIMO functionalities, and (iii) game theoretic pricing and incentive mechanisms for managing MIMO-related interference in a networked (multi-link) setting. Our CMIMO adaptation approach is based on dynamic tuning of the precoding matrices at various CMIMO transmitters, with the goal of optimizing a given network utility function (e.g., network throughput, proportional fairness, total energy consumption) subject to different scheduling and power/rate constraints.