Uti Daniel Ejim
Papers
1
Total Citations
11
H-Index
1
About
Uti Daniel Ejim is a forward-thinking researcher at the intersection of artificial intelligence and sustainable agriculture, with a primary focus on data-driven crop management. His most cited work, a 2025 systematic review, synthesizes 95 studies from 2013 to 2023 to demonstrate how AI and machine learning algorithms can optimize resource use, enhance yield prediction, and improve agricultural sustainability. Garnering 11 citations in a short time, this paper has quickly become a foundational reference for researchers exploring precision farming technologies. Ejim’s contributions lie in bridging computational methods with real-world agricultural challenges, offering a roadmap for implementing intelligent systems that reduce waste and boost productivity. His work is particularly notable for its practical emphasis on data-driven decision-making, making complex AI tools accessible to agronomists and farmers alike. As a rising voice in the field, Ejim continues to shape how technology can address global food security, positioning himself at the forefront of a transformative shift toward smarter, more resilient farming systems.
Research Focus
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Top Papers
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