This talk briefly introduces cardiovascular physiology and pathophysiology, from an engineering point of view. Cardiac structure and function can be modeled with reasonable fidelity using familiar concepts from physics, such as fluid dynamics and electromagnetism. For example, flow through the large vessels of the heart can be expressed using a compact circuit, the Windkessel model. Many such relatively simple models form the basis for the “mental models” that cardiologists utilize regularly in patient care. Therefore, an understanding of these models can be leveraged in the development of translatable computational clinical tools. More specifically, physiological models form the basis for physiologically-inspired machine learning models, which leverage prior scientific and medical knowledge to both improve model performance and provide reliable explanations for model inferences.