Curriculum
Salvatore Carta received a PhD in Electronics and Computer Science from the University of Cagliari in 2003. In 2005 joined Department of Mathematics and Computer Science of the University of Cagliari as Assistant Professor. In 2006 and 2007 he visited the Swiss Federal Institute of Technology as invited Professor, hosted by Laboratoire des Systèmes Intégrés – LSI.
Since 2014 he is Associate Professor in Computer Science at the University of Cagliari.
In the first part of his career the research activity of Salvatore Carta focused on architectures, software and tools for embedded and portable computing, with particular emphasis on Software infrastructures, algorithms and applications for multiprocessor-system-on-chip, low power real-time scheduling algorithms, and Networks-on-Chip.
The current research activities of Salvatore Carta are focused in the following fields:
- Clustering algorithms, social media analysis, and text mining for behavioral pattern identification and recommendation in group of users and in single users;
- AI algorithms for credit scoring, fraud detection and intrusion detection;
- AI algorithms for financial forecasting and robo-trading;
- E-coaching and AI algorithms and platforms for healthy lifestyles.
He is author of about 90 papers in these research fields with about 1000 citations:
https://www.scopus.com/authid/detail.uri?authorId=7004254388,
Salvatore Carta is co-founder of the Trustworthy Computational Societies Research Group and of Artificial Intelligence and Big Data Groups at the Mathematics and Computer Science Department of the University of Cagliari.
In 2008 he was co-founder and, till july 2017, CEO of Xorovo Srl, spin off of University of Cagliari. Xorovo joined Applix group in 2012, and was acquired in 2017 by the multinational professional services firm Ernst & Young (doing business as EY).
He is also co-founder of two more spin offs of the University of Cagliari: Everywhere Sport Srl (www.u4fit.com) operating on the e-coaching market, and Visioscientiae Srl, operating on the robo-trading market.
