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About

Agnese Denaro is a researcher at the forefront of applying robotics and artificial intelligence to ecological conservation. Her work centers on the intersection of computer vision, robotics, and biodiversity monitoring, with a particular focus on Mediterranean flora. Denaro’s major contribution is the development of labeled datasets and artificial vision models that enable automated plant detection in natural habitats. Her most-cited paper, "Robotic monitoring of European habitats: a labeled dataset for plant detection in Annex I habitats of Italy" (2025, 5 citations), introduces a pioneering dataset captured using the quadrupedal robot ANYmal C, targeting ecologically important species across EU-protected habitats. This work bridges the gap between field robotics and conservation biology, offering a scalable solution for habitat assessment. In a related study, "Artificial vision models for the identification of Mediterranean flora: An analysis in four ecosystems" (2025, 2 citations), Denaro advances object detection models for identifying plant species in complex, unstructured environments—a domain where little prior research exists. Though early in her career, her innovative use of legged robots for ecological monitoring marks a significant step toward autonomous, non-invasive biodiversity surveys. Her research holds promise for transforming how scientists monitor fragile ecosystems, making her a rising figure in conservation technology.