Riccardo Satta
Riccardo Satta
![]() | Department of Electrical and Electronic Engineering, Pad. B University of Cagliari Piazza d'Armi 09123 Cagliari |
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![]() | +39 070 675 5817 |
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![]() | +39 070 675 5782 |
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![]() | riccardo.satta(at)diee.unica.it |
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![]() | http://www.flickr.com/photos/endemico - http://stileonline.altervista.org |
Curriculum Vitae
Riccardo Satta received the M.Sc. degree with honors in Electronic Engineering in Oct. 2007, from the University of Cagliari, Italy. His thesis work, "Methods and Algorithms for Image-based Spam Filtering", was awarded by the Clusit association as one of the most innovative italian thesis works on Information Security of the year 2007 (link, in italian). Basing on this work, later he developed Image Spam Lab, a tool for evaluating image spam filtering algorithms.
After his graduation, he did an intership at the Ambient Intelligence Lab (AmiLab) of the Sardinia DistrICT, where he worked on automatic image categorization techniques, and image spam filtering methods. He still collaborates with the AmILab on these topics. From March 2008 to Feb. 2009 he worked as Software Engineer at SardegnaIT srl. Since March 2009 he is a permanent official at the Directorate-General for General Affairs and Information Society of the Autonomous Region of Sardinia. He is involved in definition, planning, implementation and management of local administration's IT projects, mainly focusing on e-government and e-inclusion projects.
In March 2010 he joined the Pattern Recognition and Applications Group as a PhD student. He is member of the Group of Italian Researchers in Pattern Recognition (GIRPR), affiliated to the International Association for Pattern Recognition (IAPR).
LinkedIn page: http://it.linkedin.com/pub/riccardo-satta/9/A4B/4BA
Research Interests
His research activities are focused on pattern recognition and computer vision techniques for security issues and multimedia document categorisation:
- people re-identification and retrieval in multiple-camera video surveillance scenarios;
- filtering tecniques for image-based spam;
- automatic categorisation of personal photos.




