Konlavach Mengsuwan
Papers
1
Total Citations
15
H-Index
1
About
Konlavach Mengsuwan is an emerging researcher at the intersection of artificial intelligence, ecology, and sustainable agriculture. His most-cited work, "Deep learning for sustainable agriculture needs ecology and human involvement" (2022, 15 citations), offers a critical bibliometric analysis of 156 articles, revealing that while deep learning can enhance predictability and efficiency in farming, its success hinges on integrating ecological principles and human decision-making. This contribution underscores a major theme in Mengsuwan’s research: the need for holistic, interdisciplinary approaches to technology deployment. By highlighting the limitations of purely data-driven models, he advocates for systems that respect biodiversity and farmer expertise. Though early in his career, his work has already shaped conversations around responsible AI in agriculture, emphasizing that sustainability requires more than algorithmic optimization. Mengsuwan’s scholarship serves as a vital reminder for students and researchers that the most impactful innovations emerge when technology is grounded in real-world ecological and social contexts.
Research Focus
Key Achievements
Top Papers
- 1