Zhou Zhang

Zhou Zhang seeks to improve agricultural productivity with data science through precision farming tools. Her lab uses remote sensing and machine learning to improve field crop production, decrease the use of farm inputs like nitrogen, reduce production costs and labor needs, and protect the environment. Zhou uses drone imagery to monitor crop and weed growth and predict yields. Farmers and agronomic researchers can use this information to apply inputs like herbicides and fertilizer only when needed, in just the right amounts, protecting groundwater and soil without compromising yields.

While she trained as a data scientist, Zhou’s Ph.D. research included a project on high-throughput, image-based plant phenotyping that sparked her interest in agriculture. Plant phenotypes are measurable traits, like leaf size or plant height, that are traditionally measured by hand in the field. Zhou continues to work in this area, using machine learning to accelerate breeding for desired plant traits.

Through her research, Zhou aims to use data science tools to solve real-world problems in agriculture. She sees this as a new and exciting research area that is poised for growth as more people realize how data science can benefit farmers and the environment.

“I apply data science and machine learning tools to solve pressing issues in agriculture, food security, land, water, and other natural resource issues. Connecting machine learning theory to real-world problems is why I’m here and why I choose to do this work.”