Tarek Shalaby
Papers
1
Total Citations
5
H-Index
1
About
Tarek Shalaby is a leading researcher at the intersection of artificial intelligence, machine learning, and agricultural technology, with a primary focus on fruit quality management. His most-cited work, "Harnessing artificial intelligence and machine learning for fruit quality management: A comprehensive review" (2025), has already garnered 5 citations, signaling its rapid influence in the field. Shalaby's major contributions lie in developing and synthesizing AI-driven methods to automate and enhance the assessment of fruit ripeness, defects, and overall quality, addressing critical challenges in post-harvest handling and supply chain efficiency. By integrating computer vision and deep learning models, his research offers scalable, non-destructive solutions that reduce waste and improve food safety. This work has practical implications for growers, packers, and retailers, positioning him as a key figure in precision agriculture. Shalaby’s achievements include bridging the gap between theoretical AI advancements and real-world agricultural applications, making his research a valuable resource for students and professionals seeking to modernize fruit quality control. His growing citation count reflects the timeliness and relevance of his contributions to sustainable food systems.
Research Focus
Key Achievements
Top Papers
- 1