PHYS 780:001 Special Topics: AI-Augmented Physics Research
Semester: Fall 2026
Day: T
Time: 6:00 PM - 8:50 PM
Instructor: Barry Cohen
Course Description
This course examines the integration of AI and machine learning tools into the research lifecycle, from literature synthesis and hypothesis generation to data analysis, simulation, and scientific writing. Students will develop hands-on proficiency with AI-assisted workflows while critically evaluating the epistemic status of AI-generated outputs—learning when to trust, interrogate, and responsibly integrate them into rigorous scientific practice.
Topics include large language models for research acceleration, AI-assisted code generation and debugging, automated data analysis pipelines, and the evolving role of human judgment in AI-augmented discovery.
No prior machine learning background required; curiosity and willingness to experiment are essential.
This course is designed for graduate students in Physics and related disciplines.
AI tools for literature synthesis
Idea generation, hypothesis exploration
Identifying gaps/connections in existing literature.
