About the workshop
What would it take for AI models to enter a power grid control room? A workshop on benchmarks, model training, and real-world considerations.
The power grid is one of the most consequential open problems in applied machine learning – hard physics constraints, real-time closed-loop operation, structural non-stationarity, and societal-scale consequence – yet it attracts a fraction of the methodological attention given to vision, language, or biology. This workshop brings power systems to the ML community as a first-class methodological challenge and focuses on the central bottleneck: how to evaluate learning-based methods under realistic and evolving operating conditions.
Key dates (AoE)
| Milestone | Date |
|---|---|
| Submission deadline | |
| Author notification | |
| Camera-ready deadline | November 6, 2026 |
| Workshop | Saturday, December 12, 2026 (Sydney) |
Submission tracks
- Methods with rigorous evaluation.
- Benchmarks, datasets, and evaluation protocols.
- Position and empirical-evaluation papers.
- Negative results and failure modes.
OpenReview
Submissions are now closed. View the workshop venue on OpenReview: openreview.net/group?id=NeurIPS.cc/2026/Workshop/AI4PowerGrids
See the full Call for Papers for scope, submission format, and the domain evaluation checklist.