Jul
02

CALL FOR PAPERS: HORIZONS 2026 – OPTIMIZATION FOR SUSTAINABILITY

CALL FOR PAPERS: HORIZONS 2026 – OPTIMIZATION FOR SUSTAINABILITY

July 2 – 3, 2026 | VinUniversity, Vietnam

HORIZONS 2026: Optimization for Sustainability is an international conference showcasing state-of-the-art optimization and learning theory application into practical, reliable tools for sustainable systems. By bringing together leading researchers, industry experts, and innovators, the event (i) present and synthesize recent advances in optimization and machine learning relevant to sustainability, (ii) identify concrete, high-impact research directions at the interface of learning, optimization, and decision-making, and (iii) build collaborations across academia and applied stakeholders to accelerate deployment in real-world sustainable development contexts.

We are thrilled to announce HORIZONS 2026 is now open for submissions.

Abstract Submission Portal

Abstracts (maximum 300 words) should be submitted via this LINK, latest by May 1, 2026. (Note: Corresponding co-author will need to create an account at “Oxford Abstract website“)

Important Dates

  • Abstract Submission Deadline: May 20, 2026
  • Abstract Notification of Acceptance: June 1, 2026
  • Conference Dates: July 2-3, 2026

Submission Guidelines

To ensure a high-quality conference, we invite abstract submissions of original, unpublished work.

We welcome contributions addressing, but not limited to, the following areas:

  1. Large-Scale Learning and Optimization for Sustainable Systems: Scalable AI and optimization methods for resource efficiency, sustainable infrastructure, and system-level environmental decision-making.
  2. Machine Learning for Climate and Earth Systems Modeling: Data-driven approaches for climate modeling, environmental monitoring, and risk assessment using Earth system data.
  3. Robust and Efficient Learning in Resource-Constrained Environments: Energy-efficient, resilient, and data-efficient AI designed for deployment under limited computational or data resources.
  4. Reinforcement Learning and Control for Energy Management: Learning-based control and optimization techniques for smart grids, renewable integration, and intelligent energy management.

Registration fee

  • Standard: $US 350
  • Student: $US 100

For more information and updates, please visit: horizons2026.vinuni.edu.vn

If you have any question or need any assistance regarding paper submission and the process please feel free to contact us via: [email protected]