In October 2015, Marco obtained an Undergraduate Degree, cum Laude, in Ingegneria dell’Informazione at the University of Salento, with a degree thesis in Systems Theory titled: “Principal Component Analysis (PCA) and Structural Properties of Linear Systems”. In January 2018 he obtained the Master’s degree, cum Laude, in Computer Engineering at the University of Salento, with a degree thesis in High Performance Computing titled: “Advanced approaches to improve performance of numerical models on new HPC systems”, concerning the analysis and optimization of sequential models, focusing at their uses in parallel contexts.

Since March 2018 he has been working with the Advanced Scientific Computing (ASC) division of the CMCC. His research activities involved climate models optimization, in particular the NEMO ocean model (Nucleus for European Modelling of the Ocean). He studied sequential analysis and optimization techniques. He also collaborated with the SDM (Scientific Data Management) division of the CMCC for the analysis and the optimization of the Ophidia data analytics framework. Now he is studying the use of Neural Networks as a tool for climatological and meteorological forecasts and their use in NEMO, in downscaling models, etc.
He has experience with the design, development and optimization of Machine Learning and Deep Learning algorithms and architectures.
His skills include also a good knowledge of the high performance computing architectures, optimal knowledge of programming languages for scientific and general purposes.
Since December 2022 he is working with the Supercomputing Center (SCC) division of the CMCC. Main activities are Linux programming and administration skills, as well as supercomputing hardware and networking knowledge and management. In particular, he has written and optimized several C/Bash programs, daemons and scripts, and gained a high confidence in using IBM Spectrum Scale’s administration and management utilities.
He loves cats and technology.