2026 AI Educator Summer Institute

AI is fundamentally changing research. This session will draw directly from active research in plant phenomics, image-based trait analysis, and plant breeding to demonstrate what AI-assisted science looks like in practice. We'll walk through concrete examples: how convolutional neural networks and on-device models are automating the extraction of morphological traits from field images, how large language models are accelerating literature synthesis in crop science, and how AI pipelines are compressing analyses. What do these shifts mean for how we teach science? When a model can segment an image or predict yield, what skills actually matter? We'll dig into how to design data collection exercises and research projects so that students build genuine scientific judgment rather than just prompt-writing habits. You'll leave with a grounded understanding of where plant science and phenomics research is heading, and practical strategies to make your classroom reflect that reality.


Understand how image data can be used with AI for effective research outcomes