Born and raised in Viareggio, Tuscany, Roberto Pellungrini is a PhD student in Computer Science at the University of Pisa. His main research interests concern ethical aspects related to Data Science, in particular regarding Privacy issues. Before winning the PhD scholarship, he attained a Master Degree in Business Informatics with a thesis on Assessing Privacy Risk and Quality in Human Mobility Data.
He graduated cum laude in 2016 in Computer Science at the University of Pisa (Italy), then he started in the same year the PhD in Computer Science at the same university. Roberto is currently a PhD student and a member of the High Performance Computing laboratory (HPC Lab) at the ISTI "A. Faedo" institute of CNR (Pisa). His main research interests are Information Retrieval, Machine Learning and Web Mining.
Alejandro Moreo Fernández received a PhD in Computer Sciences and Information Technologies from the University of Granada in 2013. He is a Postdoctoral Fellow at Istituto di Scienza e Tecnologie dell'Informazione ``A. Faedo'', which is part of the National Research Council (CNR). His research interests include deep learning and representation learning, with particular focus on imbalanced text classification, multilingual text classification, and cross-domain and cross-lingual sentiment classification.
The internship period is 500 hours, 20 CFU, that single student or a small group of students have to spend in one of the companies and institutions partner of the master, working on an agreed project and under the supervision of a team of tutors composed by the teachers of the master and the management companies.
The module si composed by several Seminars on experiences and case- and use-studies of Big Data analytics and Social Mining from the SoBigData.eu labs and from the companies and institutions that are partners in the Master.
This course introduces students to the theories, concepts and measures of Social Network Analysis (SNA), that is aimed at characterizing the structure of large-scale Online Social Networks (OSNs). The course presents both classroom teaching to introduce theoretical concepts, and hands-on computer work to apply the theory on real large-scale datasets obtained from OSNs like Facebook and Twitter.
This module introduces the main methods of analysis and mining of opinions and personal evaluations for users based on Big Data generated on the web or other sources. Emphasis will be put on text mining method applied to text originated on social media. Lessons will be supported by case studies developed in the SoBigData.eu lab.
Motivated and highly passionate about Management of Innovation and Data Science, since 2016 I am a PhD student in Innovation Management at Sant'Anna School of Advanced Studies. I graduated cum laude in Economics and Sciences of Public Government MSc. from University of Calabria, and gained by MBA in Business Administration and Services Innovation from Sant'Anna School of Advanced Studies in 2015.
The course presents the main web data analysis techniques. By using the query log of a real search engine as a case study, students are guided in the development of a set of methodologies for data analysis aimed at creating the knowledge base for building a recommendation system. Then, the course discusses how the same information can be used to optimize the ranking in Web services. To this regard, the course introduces the learning to rank techniques aimed at estimating the relevance of objects with respect to specific user information needs.
Giovanni Comandè (LLM Harvard Law School USA, Ph.D. Scuola Superiore Sant’Anna) is Full Professor of Private comparative law at Scuola Superiore Sant’Anna where he also studied as ordinary student.
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