ML for Systems

The 9th Machine Learning for Systems (ML for Systems) workshop brings together researchers and practitioners applying machine learning to core computer systems challenges. This year, we focus on three themes: (1) using LLMs and agentic workflows for systems tasks such as program synthesis and adaptive optimization; (2) applying ML to manage the complexity of large-scale training and serving of multimodal and reasoning models; and (3) leveraging ML for sustainable computing, including energy-, power-, and carbon-aware optimization. The workshop will feature invited talks, contributed presentations, and discussions aimed at advancing the frontier of ML for Systems research.