Federico Siciliano
TEACHING
Algorithmic Methods of Data Mining — Sc.M. in Data Science
Sapienza University of Rome
2024 - CURRENT - Rome, Italy
EDUCATION AND TRAINING
PhD in Data Science — EQF Level 8
Sapienza University of Rome
11/2020 - 31/01/2024 - Rome, Italy
Master’s Degree in Data Science — EQF Level 7
Sapienza University of Rome
09/2017 - 25/10/2019 - Rome, Italy
Master thesis:
Title: Forecasting of SYM-H index using Recurrent and Convolutional Neural Networks: A neural network approach to the prediction of magnetospheric response to interplanetary magnetic field changes
Abstract: Extensive analysis of various types of neural networks (both Recurrent and Convolutional) and combination of hyper-parameters, in order to provide a warning in a useful time for geomagnetic storms. The neural network was capable of predicting the SYMH index at a distance of one hour with an accuracy of more than 90% (in terms of R2), exhibiting excellent behaviour especially in the storm phase.
Thesis advisor: Prof. Stefano Leonardi
External Advisor: Dr. Giuseppe Consolini (INAF - Italian National Institute of Astrophysics)
Bachelor’s Degree in Management Statistics — EQF Level 6
Sapienza University of Rome
09/2014 - 18/07/2017 - Rome, Italy
Bachelor Thesis:
Title: Takenoko, a low-cost playtesting methodology
Abstract: Study of a board game (Takenoko), using online comments and reviews to focus attention on the problems already detected by players, and adoption of a particular method of play-testing: a software able to simulate the mechanics of the game in question and an Artificial Intelligence capable of playing it, thus realizing a greater number of simulations than can be achieved using real people and reducing (almost to zero) the cost of the procedure
Thesis advisor: Prof. Paolo Giulio Franciosa
WORK EXPERIENCE
Scholarship Contract for Research Activities
Sapienza, Dipartimento di Ingegneria Informatica, Automatica e Gestionale
05/2020 - 10/2020 - Rome, Italy
Design of the Diabetology Project database and preparation of the experimentation platform for machine learning algorithms
Analysis and implementation of adaptive planning systems
Neural Networks, Recommender Systems, Information Retrieval