Special Topics: Transformers and Agentic AI in Biomedical Engineering

12 units · Graduate

Spring: 12 units This course will cover applications of AI in biomedical engineering through the exploration of transformers and agentic AI. Transformers are the basis of generative models, and their sequence-to-sequence predictions can be used to analyze text, tabular data, and images. Agentic AI leverages transformers and large language models to perform a broad range of tasks, including automated workflows, decision-making, and human-computer interactions. These topics will be discussed in the context of both laboratory research and clinical settings. A central component of the course will be independent projects in which students apply the content of this course to research topics of their choosing. Students should have proficiency in Python and a foundational knowledge of machine learning and artificial intelligence. Prerequisite: 24-787 Min. grade C