During my Bachelor program, I developed a good knowledge on Remote Sensing (RS) working on multi-temporal and multi-sensor (Copernicus Sentinel-1 and Sentinel-2) images for monitoring landslides interesting some areas of South Italy.
I also developed a Python project on the Machine Learning (ML) analysis of the “Glioma grading clinical and mutation features” Dataset. The Glioma cancer is based on World Health Organization (WHO) classification and the study has been motivated by the fact that clinical and mutational molecular factors are crucial for the grading process, and especially for those countries where neuro-oncology communities and health systems are weaker. ML analysis helped to identify the 20 most frequently mutated genes and their mutation to determine the degree of disease progression.
I am thrilled to spend this period in the ESA phi-lab for developing prototype programs (in Python) for handling and processing in situ data acquired from ESA IoT air quality devices (the so-called Air Quality Platform – AQP) and from the official ARPA stations, and to correlate them with the EO satellite data (e.g. Sentinel-5P). Advanced techniques including ML and Deep Learning will be investigated to propose joint IoT/EO fusion products. I really hope to be able to apply this study on air pollutants for the safety of our monument heritage and its preservation. Which place better than the phi-lab to do that?
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