Saccotelli Leonardo

Institute for Earth System Predictions
Global Coastal Ocean Division

Via Marco Biagi 5 – 73100 Lecce, Italy

+39 0832 1902411

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Leonardo Saccotelli earned a bachelor’s degree in Computer Science and Technology for the Development of Software from University of Bari. His thesis, titled “Machine Learning for Climate Change Application to Cetacean Abundance Studies” explored the use of different machine learning methods to estimate the abundance of cetaceans within the context of climate change. From 2021 he’s attending a master’s degree in Artificial Intelligence from University of Bari.

Since April 2021 he has been actively engaged in the field of machine learning and artificial intelligence, specifically focusing on environmental and remote sensing data.

Since March 2022 he’s working at Ocean Predictions and Applications Division of Centro Euro-Mediterraneo sui Cambiamenti Climatici (CMCC) Foundation in Lecce, Italy. Currently, his main researcher is focused on developing Machine Learning and Deep Learning solutions to predict the salt-wedge intrusion length and the net river release at the estuary mouth.

His main skills are based on artificial intelligence and machine learning, as well as software engineering and development of complex software systems.

ULTIME PUBBLICAZIONI
Habitat suitability modeling of loggerhead sea turtles in the Central-Eastern Mediterranean Sea: a machine learning approach using satellite tracking data
Advancing estuarine box modeling: A novel hybrid machine learning and physics-based approach
Enhancing estuary salinity prediction: A Machine Learning and Deep Learning based approach
Environmental variables and machine learning models to predict cetacean abundance in the Central-eastern Mediterranean Sea
Machine Learning to predict cetacean behaviour using social and environmental features
Estuary salinity prediction using a Support Vector Machine based approach: a case study of the Po di Goro estuary
Vedi tutti gli articoli & papers di Saccotelli Leonardo