Workshop on ML for Systems at NeurIPS 2025, TBA (will be December 6 or 7, 2025)
Workshop on ML for Systems at NeurIPS '25, TBA (will be December 6 or 7, 2025)

Workshop Overview

Machine Learning for Systems is an annual, interdisciplinary workshop that brings together researchers and practitioners in computer systems and machine learning, specifically focusing on the novel application of machine learning techniques towards computer systems problems.

Important Dates

  • Submission Deadline: August 22, 2025 by midnight (Anywhere in the World).
  • Acceptance Notifications: September 22, 2025
  • Workshop: TBA (will be December 6 or 7, 2025)

Call for Papers

We invite submission of up to 4-page extended abstracts in the broad area of using machine learning in the design and management of computer systems . We are especially interested in submissions that move beyond using machine learning to replace numerical heuristics.

This year, we additionally look for

  • Using LLMs and agentic workflows for computer systems challenges, such as program synthesis for hardware, adaptive runtime optimization, and other specialized domains.
  • Applying ML to address emerging systems challenges introduced by agentic workflows, large-scale training and serving of large models, including LLMs and multimodal models — such as compiler partitioning strategies for distributed training, efficient memory and compute allocation, workflow orchestration, and automated infrastructure management across heterogeneous accelerators.
  • Applying ML for compute sustainability, including power/energy/carbon optimization. Examples include energy-aware job scheduling, dynamic power management based on workload and carbon predictions, and ML-driven carbon footprint assessment for cloud datacenters.

Accepted papers will be optionally linked on the workshop website, but there will be no formal proceedings. Authors may therefore publish their work in other journals or conferences. The workshop will include invited talks from industry and academia, as well as oral and poster presentations by workshop participants.

You can find accepted papers to the previous iteration of ML for Systems from NeurIPS 2024, NeurIPS 2023, NeurIPS 2022, 2021, 2020, 2019, 2018, and ISCA 2019.

Areas of interest:

ML for Systems focuses on the novel application of machine learning techniques towards computer systems problems, for example:

  • Supervised, unsupervised, and reinforcement learning research with applications to:
    • Systems Software
    • Runtime Systems
    • Distributed Systems
    • Security
    • Compilers, data structures, and code optimization
    • Databases
    • Computer architecture, microarchitecture, and accelerators
    • Circuit design and layout
    • Interconnects and Networking
    • Storage
    • Datacenters
    • Programming Languages
  • Representation learning for hardware and software
  • Optimization of computer systems and software
  • Systems modeling and simulation
  • Implementations of ML for Systems and challenges
  • High quality datasets for ML for Systems problems
  • Emerging applications
    • Using LLMs and agentic workflows for systems
    • Using ML for challenges in large-scale machine learning systems, e.g., training and serving of emerging multimodal models, reasoning models, and agentic workflows
    • Using ML to solve power and carbon challenges of large scale systems

Submission Instructions

We welcome submissions of up to 4 pages, not including references or Appendices. This year, this is a strict limit. Authors are welcome to put additional material in the optional Appendix section, but reviewers are not required to read the Appendix.

All submissions must be in PDF format and should follow the NeurIPS 2025 format.

Contact Us

Contact us at mlforsystems@googlegroups.com.