Ph.D. Candidate | Guizhou University | China
Dr. Xingcai Wu, an active researcher at Guizhou University, Guiyang, China, has established a growing research portfolio focused on the intersection of artificial intelligence, precision agriculture, and environmental sustainability. With 17 publications, over 141 citations, and an h-index of 7, his work emphasizes the integration of machine learning, computer vision, and data analytics to enhance agricultural productivity and resource efficiency. A notable contribution is his recent 2025 publication titled “Multimodal Weed Infestation Rate Prediction Framework for Efficient Farmland Management” in Computers and Electronics in Agriculture, which highlights his innovative use of multimodal sensing technologies to optimize weed detection and control systems. His research approach combines remote sensing data, UAV imagery, and AI-driven prediction models to enable real-time decision-making for crop management, soil monitoring, and sustainable land use. Dr. Wu’s broader research interests include smart farming systems, automation in agricultural operations, and environmental data modeling, with a particular focus on developing scalable, data-driven frameworks that address global food security and environmental challenges. Collaborating with a network of over 60 co-authors, his interdisciplinary work bridges computer science, environmental engineering, and agricultural science, contributing to the advancement of intelligent agricultural ecosystems. Through his studies, Dr. Wu aims to promote climate-resilient and technology-enabled farming solutions, positioning his research at the forefront of digital agriculture innovation and reinforcing the role of AI in sustainable rural development.
Profile: Scopus
Featured Publications
1. Wu, X., [Other authors]. (2025). Multimodal weed infestation rate prediction framework for efficient farmland management. Computers and Electronics in Agriculture.
Cited by: 1
