Workshop on Physics-Informed Learning for Optimization and Control of Sustainable Energy Systems at ACM e-Energy 2026:
This workshop aims to bring together researchers in machine learning and energy systems to highlight recent work on principled approaches that integrate physical constraints, domain knowledge, and structural information into data-driven models for sustainable energy applications.
We invite submissions of poster abstracts on original research related to physics-informed learning for sustainable energy systems. Relevant topics may include, but are not limited to:
Important Dates:
Submission deadline: April 25, 2026, anywhere on earth (AoE)
Notification of poster acceptance: April 30, 2026
Workshop date: June 22, 2026
Submission Requirements:
Submissions should be a 1 page (not including references) extended abstract formatted using the ACM small template, submitted as a PDF. Submissions should include author names and affiliations, title, and an extended abstract that describes the main results. If the abstract describes work that has already been published, the conference or journal venue should be cited as a reference.
Review Process
Submitted abstracts will be reviewed by the workshop organizers; posters will be accepted based on novelty of results and fit with the workshop's theme. Abstracts detailing work of particular interest will be invited to join the ``highlight talk session'' preceding the poster presentations.
This workshop aims to bring together researchers in machine learning and energy systems to highlight recent work on principled approaches that integrate physical constraints, domain knowledge, and structural information into data-driven models for sustainable energy applications.
We invite submissions of poster abstracts on original research related to physics-informed learning for sustainable energy systems. Relevant topics may include, but are not limited to:
- Theoretical and methodological foundations of physics-informed learning
- Principled machine learning approaches for optimization and control
- Physics- and structure-informed learning for power and energy systems
- Data-driven methods for reliable operation of safety-critical infrastructure
- Empirical studies and deployments in sustainable energy applications
Important Dates:
Submission deadline: April 25, 2026, anywhere on earth (AoE)
Notification of poster acceptance: April 30, 2026
Workshop date: June 22, 2026
Submission Requirements:
Submissions should be a 1 page (not including references) extended abstract formatted using the ACM small template, submitted as a PDF. Submissions should include author names and affiliations, title, and an extended abstract that describes the main results. If the abstract describes work that has already been published, the conference or journal venue should be cited as a reference.
Review Process
Submitted abstracts will be reviewed by the workshop organizers; posters will be accepted based on novelty of results and fit with the workshop's theme. Abstracts detailing work of particular interest will be invited to join the ``highlight talk session'' preceding the poster presentations.
Welcome to the Workshop on Physics-Informed Learning for Optimization and Control of Sustainable Energy Systems at ACM e-Energy 2026 (PILES 2026) submissions site. For general information, see https://learning-for-energy.github.io/.