I am a Ph.D. student in Data Science at Scuola Normale Superiore in Italy and my thesis is on “Measuring well-being through the eyes of the news”. I have also an MSc in Behavioural Economics from Erasmus University Rotterdam (2016) and a BSc in Economics from Athens University of Economics and Business (2014). Before starting my Ph.D., I worked as a trainee for the European Commission at Joint Research Centre in Italy, and at Sapienza University of Rome, as well as at Booking.com digital industry in the Netherlands.
Giovanni Mauro was born in 1995 in Catanzaro (CZ). He holds a BSc in Computer Science from University of Pisa (during which he won a one-year Erasmus+ grant at Universidad Autónoma de Madrid) and a MSc in Data Science from Universitat Politècnica de Catalunya – BarcelonaTech.
Before joining the PhD in Artificial Intelligence he worked as Data Engineer and cooperated with KDD-lab at ISTI-CNR for projects regarding Sport Analytics and Human Mobility Analysis.
Currently, his main research interests are the development of algorithms for understanding and predicting human mobility flows and trajectories, as well as the study of the segregation mechanism that takes place in a city. Besides that he is a Research Associate at ISTI-CNR and collaborates with the Networks Research Unit at IMT Lucca.
Soccer, tennis, sea, journeys and motorcycling are his main passions.
I am a first year PhD student in Economics at the Paris School of Economics supervised by Professor Hillel Rapoport. My research focuses on studying migration through the lens of big data. As such, I have worked on academic migration using MAKG data and utilising the fall of the Iron Curtain as a natural experiment to establish the causal relationship between academic networks and their migration decisions. Additionally, I am working on an assimilation index of Syrian refugees in Turkey using CDRs and Twitter data. Lastly, which probably wouldn’t be addressed with big data, is that I am very interested in post-Arab Spring migration flows, particularly those of Tunisians to Italy and assessing specific policies put in place as a reflex to this influx. All in all, I am interested in all things related to migration and refugees. Prior to joining the PhD, I have graduated from MRes in Analysis and Policy in Economics at PSE and from BSc in Economics from University of Sheffield, where I was awarded the Knoop Economics Award. I have worked as a RA previously for Immigration Policy Lab, CoronaNet, Institute of Economic Affairs and GLOSS Research Scheme.
Matteo Bohm was born in Rome (Italy) in 1994. He graduated in Statistics, Economics and Society in 2016 at Sapienza University of Rome, where he also took his Master degree in Statistics and Decision Sciences in 2019.
He is currently a Ph.D fellow in Data Science at Sapienza, and a visiting fellow at the Knowledge Discovery and Data Mining Laboratory (KDD) at ISTI – CNR, in Pisa (Italy).
His research interests are on spatial data and models to study human mobility and migration, in particular when environment and climate factors are involved.
Laura Pollacci is currently a postdoctoral researcher at the Knowledge Discovery and Data Mining Laboratory (KDDLab), a joint research group of the Information Science and Technology Institute of the National Research Council (CNR) in Pisa and the University of Pisa. Born in Viareggio (LU) in Italy on 28th April 1988, she studied arts and graphics at the Liceo Artistico Passaglia of Lucca in the Experimental and Visual Ambiental course. In 2015 and 2014, she graduated cum laude in Digital Humanities (MS and BS) at the University of Pisa. Both theses have been developed in the Computational Linguistics area at CoLingLab (Computational Linguistic Laboratory). She received a Ph.D. in Computer Science with a thesis on the conjunct usage of Big Data and Sentiment Analysis for the study of Human Migration in the same institution. Her research interests lie in the area of Social Network Analysis and Visual Analytics for Social Mining, Human Migration, and Sentiment Analysis.
M.S. in Sport Science for Health at University of Milan 2013, Ph.D. in Integrate Biomedical Research at University of Milan 2017; Researcher at Department of Computer Science at University of Pisa since March 2018. His research focuses on the physiological response analysis in both sport and health sciences in particular to assess the injury risk of soccer players and assessing the heart rate responses to external stimulus such as sleep, physical activity and psychological status. He also works on combining psychophysiological data for the forecast of people well-being.
I’m a Ph.D. student in Data Science at Scuola Normale Superiore in Pisa, Italy. My research focus is on explainable AI for sequential data, in particular on interpreting black-box models for univariate and multivariate time series. In 2017, I received my B.S. degree in Economics and Management at the University of Padua, Italy, and in 2020 my M.S. degree in Data Science at the University of Pisa, Italy.
Guidotti, R., Monreale, A., Spinnato, F., Pedreschi, D., & Giannotti, F. (2020, October). Explaining any time series classifier. In 2020 IEEE Second International Conference on Cognitive Machine Intelligence (CogMI) (pp. 167-176). IEEE.
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I’m a Computer Engineer and a Ph.D. student in Data Science at the Department of Computer, Control and Management Engineering (DIAG) of Sapienza University of Rome. I am currently teaching assistant (TA) for the Data Mining course. My Ph.D. advisor is Aris Anagnostopoulos and my co-advisors are Simone Scardapane and Paolo Tieri. My research interests are in the field of AI for medicine, mainly focusing on deep learning in bioinformatics.