Principle Investigator
Dr. Jianfeng Zhou
I am an Agricultural Engineer with experience in Agricultural Mechanization and Automation, Precision Agriculture / Precision Livestock Farming, and High-throughput Phenotyping. I am working with various crop production and cropping systems, including specialty crops (tree fruit, potato and dry beans) and row crops (soybean and corn). Research projects involve a large range of targets, including sensing technologies in precision agriculture and phenomics , and mechanical and robotic technologies in crop harvesting, management and breeding. Most research projects will be multidisciplinary, with close collaboration with experts in Engineering, Plant Science (breeding, plant physiology, stress biology), Agronomy and other crop related professionals. I am eager to work with anyone.
CURRENT MEMBERS
Fengkai Tian, PhD Student
Fengkai Tian joined the lab in September 2021 as an M.S. and Ph.D. student. His research focuses on using remote sensing and environmental data in precision agriculture, with expertise in RGB and hyperspectral sensors.
Sazzad Mahmud Rifat, PhD Student
Sazzad Mahmud Rifat, a PhD student since June 2022 under Dr. Jianfeng Zhou, researches mechanical harvesting for American Elderberry, focusing on sustainable digital agriculture, 3D modeling, and precision agriculture.
Felix Michael Oguche, PhD Student
Felix Michael Oguche, PhD student, specializes in precision agriculture and innovative tool design, enhancing efficiency for women farmers. Skilled in network engineering, focused on sustainable agri-tech.
Tianqi Yao, PhD Student
Tianqi Yao, Ph.D. student, specializes in AI-driven agricultural pest monitoring, using sensor technologies, computer vision, and IoT for precision agriculture solutions.
Blessing Ademola, PhD Student
Guojie Ruan, PhD Student
Guojie Ruan is a PhD student in the Precision and Automated Agriculture Lab (PAAL) at the University of Missouri, specializing in precision agriculture. His research focuses on crop remote sensing monitoring, precision nitrogen management, and data-driven modeling to enhance agroecosystem resilience to climate change.
