ABSTRACT:

The Willamette Valley is known as the grass seed capital of the world. In Oregon, grass seed is a $640 million annual industry, and across the U.S., it exceeds $60 billion. Seed testing, crucial for determining the quality and price of seed lots, involves separating impurities from grass seeds. Traditional methods rely on manual, repetitive tasks that contribute to occupational injuries and mental stress. This outdated approach is also facing staffing challenges.

Leveraging recent advancements in computer vision, AI, and robotics, my collaborators and I aim to transform seed analysis. We have built a prototype device that automates grass seed analysis. I will share how we have overcome many engineering challenges in bringing computer vision and AI to solving practical problems.

BIO:

Yanming Di is an Associate Professor of Statistics with expertise in statistical genetics, genomics, and bioinformatics. Over the years, he has provided statistical consulting for numerous projects across diverse fields. Recently, he has been exploring ways to drive real-world impact, with the grass seed project being one of his latest endeavors to bridge research and practical applications.