Lazio

I have a multidisciplinary work and educational background. I received my master's degree in Management, with a specialization in quantitative methods for business management, from the University of Rome Tor Vergata. I have worked at multinational companies in both the insurance and medical sectors. I chose to attend this master's program to pursue a new career path.

I earned a bachelor's degree in physics in Rome, with a specialization in statistical mechanics. During my master's degree I had the opportunity to delve into concepts such as Neural Networks, Stochastic Processes and Complex Systems, acquiring theoretical knowledge underlying many ML algorithms. Passionate about programming and quantitative analysis, I found in Data Science the meeting point between these two worlds, and I decided to enroll in this master in Big Data to follow my dream of working in this field. In my spare time, I like to go hiking in the mountains.

I graduated in Physics at the Sapienza University of Rome. During my dissertation I started to be interested in research activity with the study of economic and technological bipartite networks. Subsequently I have been employed as Solution Developer working on different projects. I then decided to enroll in the Master in Big Data Analytics & Social Mining due to my growing interest in the world of Machine Learning and Big Data.

After completing a Master's Degree in Biomedical Engineering at the University of Pisa, I worked as an R&D Engineer in a biomedical company-university spin-off contributing to the European Horizon2020 Endoo-EU project. In this innovative and stimulating context, my curiosity towards Data Science's world was born. Later, as an SQA Engineer for a multinational company, I continued to inform myself about Data Science and its infinite application possibilities with the aim of transforming my personal interest into a real job opportunity. Hence the decision to enroll in the Master in Big Data Analytics & Social Mining.

I graduated in philosophy in November 2018 at the University of Roma Tre with a thesis on the role of probability in the interpretation of Quantum Mechanics. My interests in philosophy have always been at the limits of the physical and mathematical sciences. In particular, I have been interested in probability theory, interpretation of physical theories, logic and philosophy of logic. After these years of studying philosophy, I decided to deepen the quantitative aspect of my interests. In particular, I have tried to build a good base of analysis and geometry and I have further deepened some aspects of mathematical logic. During this period I discovered the world of Big Data and Machine Learning and so I decided to enroll in the master offered by the University of Pisa, where I am learning its methods. The construction of predictive models and the use of other techniques learned are now my passion. My desire is to work in a company in the sector to deal with Data Science full time.

Born in Rome in 1994. I studied Modern Literature at the University of Tor Vergata and I graduated in Modern Philology at La Sapienza (University of Rome) discussing a degree thesis on Robots in West literature. Always interested in the relationship between technological and humanistic skills, I decided to enroll in the master in Big Data Analytics and Social Mining to get 360-degress training and skill. LinkedIn: linkedin.com/in/gianluca-sperduti-b14364164

Tina Martino is currently covering the role of Head of Value Proposition in Octo Telematics, a leading company in insurance telematics and smart mobility services. After graduating in Information Sciences, he worked at Telecom Italia as Telco networks designer and vertical product marketing specialist. After she specialized in infomobility solutions, holding various technical and commercial roles mainly in Viasat, an Italian company, and then in Siemens where she managed “end to end” Internet of things projects in different application contexts (home, industrial automation, connected cars). Her special focus on continuous innovation and the search for new perspectives to look at everyday life have characterized her professional path.

He is from Rome and he holds a Bachelor’s degree in Biology and a Post graduate Master’s degree in Biological Oceanography and Marine Biology. The experience and the knowledge he gained in the scientific and IT field both during the internship and doing research for his thesis project at ISPRA (Istituto Superiore per la Protezione e la Ricerca Ambientale), led him to comprehend how important it is, for a scientific team, to have a professional figure skilful at elaborating and interpreting data. Therefore, he decided to enrol in the Big Data & Social Mining Specialization Course at the University of Pisa, setting the goal of acquiring the typical Data Scientist skills in order to employ them in scientific research, as well as in its decisional process, focusing on their application in the environmental field.

Luisa Bonanome is 27 years old, she was born in Rome and, in 2016, she graduated in "Psychology applied to the contexts of health, labor and legal law" at the University La Sapienza of Rome. After completing her studies, she undertook a compulsory post-graduate internship at Culture srl: a research and communication company founded by Dr. Felicia Pelagalli, an expert in human digital transformation, data analysis and business consulting. Stimulated by this experience, she has decided to continue in this area by enrolling in the Master, to direct her professional skills in data analysis and to be introduced to those new approaches and tools that are proving fundamental to encourage changings towards, what is today called, a Data Driven culture.

Bachelor's Degree in Physics, Master's Degree in Statistics for Information Systems and Master's Degree in Technological Innovation and Design for Urban Systems. During the Master's degree thesis I developed a geomarketing analysis aimed at creating a ranking of points of sale through the creation of a composite indicator able to describe the level of competitiveness. The economic potential has been evaluated in terms of purchasing capacity of the resident population in the catchment areas of each point of sale and of the specific characteristics, both of the point of sale itself and of the urban context interior of which was located. The information related to each of the territorial areas has been reconstructed based on the results of the Population Census for census sections and the type of land. Finally the registration to the Tim Big Data Challenge 2015 which gave me the opportunity to work with the data relating to the telephone cells.