Medical informatics is an interdisciplinary field using computational methods to improve healthcare. As the practice of medicine becomes increasingly dependent on data, new capabilities are needed to manage and transform it into useful insights about human disease and its treatment. Medical informatics involves development of novel algorithms for working with current (e.g., clinical, imaging) and emergent types of observational data (e.g., omic, mHealth), including AI-based approaches (e.g., machine/reinforcement learning) – and the translational challenges of applications (e.g., clinical decision support). Coursework in the UCLA Medical Informatics Home Area thus covers a range of foundational and contemporary materials related to biomedical informatics as well as cross-cutting topics in (bio)statistics and data science – all emphasizing biomedical/clinical applications and use cases. Research is focused broadly on methodological, evaluation, and implementation of modern techniques into real-world health environments.