Ali Moghimi

Ali Moghimi is an Assistant Professor of Teaching in the Department of Biological and Agricultural Engineering at the University of California, Davis, within the College of Engineering. He specializes in remote sensing, artificial intelligence, and digital agriculture, with a strong focus on the food-water-energy nexus. His work integrates UAVs, LiDAR, and hyperspectral imaging for agricultural innovation.

Research Interests:

• Remote Sensing and AI in Agriculture
• Precision and Digital Agriculture
• Unmanned Aerial Systems (UAS)
• Machine Learning and Deep Learning for Plant Phenotyping
• Food-Water-Energy Nexus
• LiDAR and Multispectral/Hyperspectral Imaging

His recent publications show a consistent trend in applying deep learning and remote sensing to crop monitoring, yield prediction, and disease detection, particularly in wheat and grapevines. The work bridges engineering, computer science, and agricultural science, emphasizing automation and data-driven decision-making in farming.

Scientific Contributions:

• Developed machine learning models for nitrogen estimation in grapevines
• Applied deep neural networks for Fusarium head blight detection
• Advanced hyperspectral imaging for salt stress assessment in wheat
• Innovated in fruit quality assessment using NIR spectroscopy

Dr. Moghimi teaches ABT 060, "Introduction to Unmanned Aerial Systems for Agriculture & Environmental Science," and is passionate about interdisciplinary education. He advises graduate students as part of the graduate faculty and conducts research supported by interdisciplinary collaborations. His work contributes to sustainable agricultural practices through technological innovation.