Controllers interact with many other aspects of a system: hardware, software, users, decision-makers, planners…topics often studied in Computer Science. Some of these interactions are unknown or ignored in control system theory and design. This can lead to system fragility, suboptimal performance, or limited capabilities. Studying these interactions improves understanding of the strengths and weaknesses of current models and assumptions. Leveraging this understanding can lead to improved system performance by creating new models and methods that account for and exploit these interactions. In this talk, I will present research that exemplifies the benefits of deep study of the interactions between control and four topics in computer science: real-time systems, machine learning, user interactions, and software. Each project is couched in deployed systems in the NIMBUS lab at the University of Nebraska - Lincoln.