Monreale Anna

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Anna Monreale is an assistant professor at the Computer Science Department of the University of Pisa and a member of the Knowledge Discovery and Data Mining Laboratory (KDD-Lab), a joint research group with the Information Science and Technology Institute of the National Research Council in Pisa. She has been a visiting student at Department of Computer Science of the Stevens Institute of Technology (Hoboken, NewJersey, USA) (2010). Her research interests include big data analytics, social networks and the privacy issues raising in mining these kinds of social and human sensitive data. In particular, she is interested in the evaluation of privacy risks during analytical processes and in the design of privacy-by-design technologies in the era of big data. She earned her Ph.D. in computer science from the University of Pisa in June 2011 and her dissertation was about privacy-by-design in data mining.
Topics: 
Privacy by Design in Data Analytics
Multidimensional Social Network
Discrimination in Knowledge Discovery
Spatio-temporal mining
Data Mining
2014 Privacy by Design Ambassador
2014 ISTI-CNR Young++ Researcher Award
2010 Visiting Student at Department of Computer Science of the Stevens Institute of Technology, Hoboken, NewJersey, USA
2013 Visiting Scientist at People in Motion Lab of the University of New Brunswick, Fredericton, Canada
- Program Co-Chair of the 1st International Workshop on Dynamics in Networks (In conjunction with ASONAM 2015), August 25th, 2015 (DyNo 2015)
- Program Co-Chair o f the 4th International Symposium on Modelling and Knowledge Management applications: Systems and Domains (In conjunction with SEFM 2015) September 8, 2015 (MoKMaSD 2015)
- Program Co-Chair o f the 3rd International Symposium on Modelling and Knowledge Management applications: Systems and Domains (In conjunction with SEFM 2014) September 2, 2014 (MoKMaSD 2014)
- Program Co-Chair of the 1st International Workshop on Privacy and Security for Moving Object (In conjunction with MDM 2013) June 3, 2013 (PriSMO 2013)
- Program Co-Chair of the 1st International Workshop on Privacy in Social Data (In conjunction with ICDM 2012) December 10, 2012 (PinSoDa 2012)
- Program Commitee ACM Conference on Information and Knowledge Management (CIKM 2012)
- Program Commitee First Workshop on Analysing Complex NEtworks 2010 (ACNE 2010).
- Member of the Editorial Board of The Privacy Observatory Magazine
- Membro dell’Editorial Board del Journal Transactions on Data Privacy
2004 Bachelor Degree in Computer Science at University of Pisa with 110/110 cum laude.
2007 Master Degree in Computer Science at University of Pisa with 110/110 cum laude. Thesis: "Interpretazione Astratta per il pi-calcolo"
2011 Ph.D. in Computer Science at University of Pisa. Thesis: "Privacy by Design in Data Mining"

"Those who fall in love with practice without science are like a sailor who enters a ship without a helm or a compass, and who never can be certain whither he is going." Leonardo Da Vinci

Position
Assistant Professor
Affiliation
Department of Computer Science, University of Pisa (DI-UNIPI)
Room
372
Phone
+39 050 221 3119
Fax
+39 050 315 2040
Email
Homepage
Google Scholar
Anna Monreale on Google Scholar
DBLP
Anna Monreale on DBLP
Scopus
Anna Monreale on Scopus
ArnetMiner
Anna Monreale on ArnetMiner

Publications

2016

Pages

Blog

MyWay, a prediction system which exploits the individual systematic behaviors modeled by mobility profiles to predict human movements.

Mining a large number of datasets recording human activities for making sense of individual data is the key enabler of a new wave of personalized knowledge-based services.

ISTI News June 2017

On the second issue of the ISTI News newsletter you'll find a description of the new Ph.D.

Intervista ad Anna Monreale a margine del forum di Abiformazione su "I Big Data per l'industria bancaria e finanziaria", 25 e 26 Ottobre 2016, Roma

Anna Monreale all'evento BigDataTech ha descritto un progetto di ricerca nel contesto retail che mostra un nuovo approccio per la gestione dei dati personali basato su un modello di tipo user-centric.