Alessandro Gentili
Papers
3
Total Citations
9
H-Index
2
About
Alessandro Gentili is a researcher at the forefront of underwater robotics and autonomous systems, specializing in perception, object detection, and acoustic sensing for marine environments. His work centers on enabling Autonomous Underwater Vehicles (AUVs) to achieve true autonomy—moving beyond pre-programmed missions to make real-time decisions. Gentili’s major contributions include developing deep learning strategies for the identification of artificial objects, a critical step for tasks like infrastructure inspection and environmental monitoring. He has also advanced passive acoustic monitoring (PAM) by comparing sensor technologies for Direction of Arrival (DoA) estimation, improving how underwater vehicles localize acoustic sources. His most-cited paper, “Detection and classification of man-made objects for the autonomy of underwater robots” (2023), has garnered 4 citations, while his 2024 work on deep learning strategies is already gaining traction. Gentili’s research bridges computer vision, acoustics, and robotics, addressing key challenges in underwater autonomy. His comparative analyses of sensors and neural network architectures provide practical insights for deploying intelligent systems in complex, unstructured marine environments.
Research Focus
Key Achievements
Top Papers
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