Overview
The AI for Energy Networks Workshop is set to take place on January 16, 2026, at the University of Bath, UK. This event aims to bring together leading researchers and practitioners in AI and machine learning to explore the intersection of these technologies with energy networks. The workshop will focus on collaborative problem-solving and knowledge sharing, addressing the unique challenges and opportunities presented by the transition to net zero in the energy sector.
Background & Relevance
The energy sector is undergoing significant transformation due to the push for renewable energy sources and the integration of low carbon technologies. This evolution is accompanied by both opportunities and challenges, particularly in the management and optimization of energy networks. AI technologies are poised to play a crucial role in enhancing grid resilience, optimizing asset management, and improving forecasting accuracy. Understanding these dynamics is essential for researchers and practitioners aiming to contribute meaningfully to this critical area of national infrastructure.
Key Details
- Date: January 16, 2026
- Location: University of Bath, UK
- Format: In-person workshop
- Focus Areas: AI applications in energy networks, including prediction, optimization, and decision-making under uncertainty
- Application Deadline: December 19, 2025 (applications reviewed on a rolling basis)
- Application Link: Apply here
Eligibility & Participation
This workshop is designed for AI researchers and practitioners with expertise across various AI disciplines. Participants are encouraged to apply regardless of their prior knowledge of the energy sector. The focus is on those who can address critical energy challenges through innovative AI solutions.
Submission or Application Guidelines
Interested individuals should apply through the provided link. Applications will be reviewed continuously until the deadline, so early submission is encouraged.
More Information
The workshop will facilitate a working session aimed at identifying high-impact problems in energy networks that can benefit from AI research. The outcome will be a position paper summarizing recommendations and setting a research agenda for future AI applications in this field. This initiative aligns with broader efforts to enhance the resilience and efficiency of energy systems, which are vital for achieving sustainability goals.
Conclusion
The AI for Energy Networks Workshop presents a unique opportunity for professionals in AI and machine learning to engage with pressing challenges in the energy sector. Participants will not only contribute to meaningful discussions but also help shape the future of AI applications in energy networks. Interested individuals are encouraged to apply and join this important dialogue.
Category: Conferences & Workshops
Tags: ai, energy networks, machine learning, deep learning, reinforcement learning, natural language processing, computer vision, time-series forecasting, explainable ai, generative ai, anomaly detection, graph neural networks
