Francesco Immorlano received his Bachelor of Science in Information Technology Engineering at the University of Salento in October 2017. He obtained his Master of Science in Computer Engineering with honors at the University of Salento in April 2020, presenting a thesis in High Performance Computing entitled “The use of Machine Learning for Detection and Tracking of Tropical Cyclones” that has been developed in collaboration with the Advanced Scientific Computing (ASC) division of the Euro-Mediterranean Center on Climate Change (CMCC) Foundation.
In November 2020, he entered a Ph.D. program in “Engineering of Complex Systems” at the Department of Engineering for Innovation of the University of Salento, researching at the intersection between artificial intelligence and climate change. Since May 2020, he has been collaborating with the Exascale Machine Learning for Climate Change (EMLC2) research unit at the ASC division of the CMCC Foundation.
His main research interests are focused on Machine Learning and Deep Learning algorithms with a specific application to the climate change domain. In particular, he is studying the exploitation of Deep Learning models for Tropical Cyclones forecasting and for other Climate Science use cases, like Climate Downscaling.
- End-to-End Workflows for Climate Science: Integrating HPC Simulations, Big Data Processing, and Machine Learning
- An ensemble machine learning approach for tropical cyclone localization and tracking from ERA5 reanalysis data
- An Artificial Neural Network-based approach for predicting the COVID-19 daily effective reproduction number Rt in Italy
- MSG-GAN-SD: A Multi-Scale Gradients GAN for Statistical Downscaling of 2-Meter Temperature over the EURO-CORDEX Domain