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About

Stefano Poni is a leading researcher at the intersection of precision viticulture and agricultural robotics, whose work is transforming traditional vineyard management. His primary research areas span grapevine winter pruning automation, non-destructive fruit ripeness assessment, and the application of deep learning and robotics to viticulture. Poni’s major contributions include pioneering mechanical winter pruning techniques grounded in plant physiology, and more recently, developing integrated robotic systems that combine 2D segmentation with 3D point clouds to generate precise pruning points—a critical step toward fully autonomous vineyard operations. His highly cited 2016 paper on the physiological bases of mechanical pruning (64 citations) laid the groundwork for this work. Poni has also advanced on-the-go ripeness estimation using snapshot hyperspectral imaging, enabling real-time, non-destructive quality monitoring. His impact is evident in a growing body of work that bridges computer vision, robotics, and agronomy, with recent publications on deep learning for organ segmentation and fuzzy dynamical systems for robot learning. Notably, he created the VINEPICs dataset, a valuable open resource for the research community. Poni’s research is directly addressing the critical labor shortages and skill demands in viticulture, making him a key figure in the future of smart farming.