Andrea has master in computer science and a phd in information engineering. Since 2011 is a researched at Istituto di Scienza e Tecnologie dell'Informazione "A. Faedo", which is part of the National Research Council (CNR). His research is in Human Language Technologies area, with a focus on Text Classification, Information Extraction and Sentiment Analysis.
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.
The module aims to introduce ethical and legal notions of privacy, anonymity, transparency and discrimination, also referring the Directives and Regulations of the European Union and their ongoing evolution. Tho module will show Privacy-by-Design models and technologies that are useful to protect the users' rights and that allow the analysis of Big Data without harming the right to the protection of personal data, to transparency and to a fair treatment.
The objective of the module is to align the competences of the students in computer science and base, in particular about databases, structured data analysis and programming languages.
I am an Associate Professor of Management at the Scuola Superiore Sant'Anna in Pisa. I am also Research Fellow with the Berkeley Roundtable on the International Economy (BRIE), University of California – Berkeley and Social Innovation Fellow with the Meridian International Center of Washington, DC. I am currently the Italian Representative on the SMEs & Access to Finance Programme Committee, for Horizon 2020, with the European Commission.
Andrea Piccaluga is the Director of the Institute of Management at Scuola Superiore Sant'Anna (www.sssup.it), where he is Professor of Innovation Management. He is also President of Netval (www.netval.it), the Italian network of University Technology Transfer Offices.
The course presents the main elements for understanding financial markets, their structure, and technological infrastructure. Specifically, the course provides a background on basic empirical modeling of financial time series, from low to ultrahigh frequency, identifying the key data science aspects including data storage, latency, high dimensional inference, etc. It also covers semantic analysis of texts from news feed and social networks for financial forecasting.
Daniele Fadda, born in Milan on 10.05.81. He graduated at Density Design LAB at the School of Design - Politecnico di Milano. He is now a freelance designer coordinating projects about promotion and territorial storytelling for the municipality of Pisa and Città della Pieve (PG). He worked on the visual representation of complex systems, data visualization, especially regarding the transport infrastructures and he collaborated with several architects as communication consultant. In the spare time, he works as graphic designer for the monthly press Seconda Cronaca.
Salvatore Trani got his master degree at the Computer Science Department of the University of Pisa in 2013. He then started a collaboration with the Istituto di Scienza e Tecnologie dell'Informazione (ISTI) "A. Faedo" of the Consiglio Nazionale delle Ricerche (CNR) in Pisa. The collaboration continued also during his PhD course at the PhD school of Computer Science of the University of Pisa. In 2016 he submitted his PhD thesis titled "Improving Efficiency and Effectiveness of Document Understanding in Web Search". Currently he is a research fellow at ISTI-CNR.
Riccardo Guidotti was born in 1988 in Pitigliano (GR) Italy. He graduated cum laude in Computer Science in 2013, at University of Pisa. He discussed hi thesis on Mobility Ranking: Human Mobility Analysis using Ranking Measures. He started the Ph.D. in Computer Science at the School for Graduate Studies "Galileo Galilei", (University of Pisa) in November 2013. He is currently a member of Knowledge Discovery and Delivery Laboratory. His interests regard Individual Data Mining, Mobility Data Analysis, Economic Data Analysis and Complex Network Analysis.
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