The Conference convenes experts working in foundational AI, computer vision, machine learning, data analytics, and sustainability science. The track emphasizes how these complementary, multi-disciplinary approaches collectively generate richer, more actionable insights into farm management, crop health, and environmental stewardship. We invite submissions that explore a wide range of research, including but not limited to:

Foundational AI for Agriculture:
- Generative AI
- Foundation Models
- Multimodal Learning
- Self-Supervised and Few-Shot Learning

Computer Vision and Image Processing:
- 3D Vision for Agriculture
- Semantic and Instance Segmentation
- Scene Understanding and Analysis

Machine Learning for Crop Management:
- Predictive Modeling and Forecasting
- Reinforcement Learning for Control

Advanced Agricultural Systems:
- Agentic AI and Autonomous Systems
- Digital Twins and Simulation
- Neurosymbolic AI

Trustworthy and Responsible AI in Agriculture:
- Interpretability and Explainability (XAI)
- Robustness and Uncertainty Quantification
- Fairness, Ethics, and Policy