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About

Ruoshi Li is an emerging researcher specializing in agricultural robotics, computer vision, and smart farming technologies, with a particular focus on automated transplanting systems for controlled environment agriculture. Li's work sits at the intersection of precision agriculture and intelligent robotics, addressing one of horticulture's most labor-intensive challenges: the reliable, damage-free transplanting of seedlings in plant factory settings. Li's most impactful contribution, "Edge Recognition and Reduced Transplantation Loss of Leafy Vegetable Seedlings with Intel RealSense D415 Depth Camera" (2022), has garnered 23 citations, demonstrating meaningful uptake within the agricultural engineering community. This work advanced depth-sensing approaches to minimize seedling damage during mechanical transplanting. Building on this foundation, Li explored obstacle avoidance strategies using Kinect visual processing to further reduce plant injury rates during automated operations. More recently, Li has extended this research into the realm of digital twins and data-driven monitoring, developing online systems to evaluate vibration and transplanting quality in real time — a forward-thinking approach that bridges physical plant factory infrastructure with intelligent digital oversight. Collectively, Li's research contributes practical, technology-driven solutions aimed at improving seedling survival rates, operational efficiency, and the economic viability of modern plant factories.