Machine Learning for Systems

Course overview

From classical learning-based approaches to generative and agentic AI, machine learning (ML) is transforming computer systems and networks in profound ways. This course examines both seminal and state-of-the-art work on ML for systems. Students will read, critique, present, and discuss research papers, with guidance and context provided by the instructor. In parallel, students will undertake a structured group research project aimed at producing a high-quality conference-style paper (although an actual submission is not required).

Recommended prerequisites: at least one course in AI/ML (e.g., CS 440, CS 443, CS 446) and one course in systems and networking (e.g., CS 423, CS 425, CS 438).