Maria Luisa Sapino

Address: Ufficio 2B
Dipartimento di Informatica - Università degli Studi di Torino
Corso Svizzera 185 (recommended entrance: Via Pessinetto 12), 10149 Torino, Italy icona mappa
Phone number: +39 011 6706745   Fax: +39 011 751603
Office hours: Canceled from 1/10 2014 to 10/9/2015 (Sabbatical leave)


icona biografiaShort Bio

Maria Luisa Sapino got her MS and PhD degrees in Computer Science at the University of Torino. Since 2007 she is Full Professor at the University of Torino and Adjunct Professor at the Ira A Fulton School of Computing, Informatics, Decision Systems Engineering (CIDSE) at the Arizona State University. Her initial contributions to computer science were in the area of logic programming and artificial intelligence, specifically in the semantics of negation in logic programming, and in the abductive extensions of logic programs. Since mid-90s she has been applying these techniques to the challenges associated with database access control, and with heterogeneous and multimedia data management. In particular, she developed novel techniques and algorithms for similarity based information retrieval, content based image retrieval, web accessibility for users who are visually impaired. She also focused on temporal and synchronization aspects of distributed multimedia presentations in the presence of resource constraints and on the modeling and investigation of various aspects of ambient intelligence systems. Her major research interests are currently in the area of Heterogeneous and Multimedia Data management, with strong emphasis on tackling the so called "Big Data challenges", including aspects related to the development of efficient techniques for tensor based big data analysis, and on various aspects related to indexing, classification and querying of (possibly multivariate) time series. Maria Luisa Sapino is active in multiple interdisciplinary projects, in which different domains and disciplines, apparently far from each other (such as Building Energy Consumption Analysis and Study of the Infectious Disease Propagation) can benefit from "smart data oriented" fundamental technological innovations.

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