Artificial intelligence is rapidly becoming an essential tool in physics research, transforming how scientists approach complex problems and explore new fields. This graduate course is designed to train physics students in the effective and critical use of AI to accelerate research. Students will learn how to rapidly acquire unfamiliar concepts, navigate new areas of active research, and solve real-world physics problems with AI as a collaborator.
The course emphasizes key skills such as identifying when AI-generated solutions are flawed, selecting appropriate methods for problem-solving, and integrating AI tools into workflows—from conceptual understanding to coding simulations and data analysis. Through a series of 3–4 multi-stage problems drawn from diverse areas of physics, students will work in teams in a collaborative “hackathon” format. Minimal prior knowledge of each topic is required; the course is structured to build up the necessary background as part of the learning process.
With weekly discussion and presentation sessions (2 hours/week) and an expected total time investment of about 8 hours/week, the course aims to equip students with a new mode of research thinking: fast, adaptive, and AI-augmented. The ultimate goal is to collectively develop the ability to use AI to hack physics.