معرفی
Yeyin Shi is an Associate Professor and Agricultural Intelligence Engineer at the University of Nebraska-Lincoln, Department of Biological Systems Engineering. His research focuses on applying artificial intelligence and remote sensing technologies to enhance agricultural productivity and sustainability. He teaches courses such as AGST 316: Technologies and Techniques for Digital Agriculture and AGEN/AGRO/AGST 431/892: Site-Specific Crop Management. He holds a Ph.D. in Biosystems and Agricultural Engineering from Oklahoma State University (2014), an M.S. (2010), and a B.S. in Mechanical Engineering from Nanjing Forestry University (2007).
Research Interests: Agricultural data generation/analysis, remote sensing systems (satellite/UAV-based), crop stress sensing, precision crop management, and high-throughput phenotyping. His work bridges machine learning, robotics, and agronomy to address challenges in sustainable farming practices. Recent projects include maize tassel detection via deep learning, UAV-based weed detection, and nitrogen stress indices for maize using hyperspectral imagery.
- Awards: ASABE Outstanding Manuscript Reviewer (2015), 1st Place Postdoc Research Poster (2015), 2nd Place Student Robotic Competition (2012)
- Grants: Active collaborations on USDA-funded projects for precision agriculture and phenotyping
- Labs/Teams: Leads the Agricultural Intelligence Research Group at UNL, focusing on AI-driven agricultural solutions
His research emphasizes scalable solutions through edge computing and cloud-based frameworks for irrigation scheduling and crop monitoring, aiming to optimize resource use in both row crops and livestock systems.
