Daniel Uyeh

Daniel Uyeh is an Assistant Professor in the Department of Biosystems and Agricultural Engineering at Michigan State University's College of Engineering. Previously, he served as a Research Professor at Kyungpook National University's Upland Field Machinery Research Center and a Researcher at their Smart Agriculture Innovation Center. His research focuses on climate-smart decision support systems, integrating machine learning, sensor technology, and automation to enhance agricultural sustainability and resilience.

His work spans multidisciplinary areas including precision livestock feed formulation, smart farming systems, and AI-driven decision-making frameworks for resource optimization. He explores applications of computer vision, evolutionary algorithms, and sensor networks to address challenges in crop production, dairy cattle nutrition, and soil analysis.

Recent research trends emphasize resilience in specialty crop production, workforce development through remote training, and bridging technological advancements with global agricultural needs. Daniel's projects often involve cross-sector collaborations to translate technical innovations into scalable solutions for farmers and agribusinesses.

His contributions highlight the strategic role of digitalization in modern agriculture, particularly in developing economies where AI and automation can drive food security and economic growth. Current initiatives include optimizing feed formulations for varying market conditions and enhancing greenhouse micro-climate prediction through machine learning.