Home LIAAD Projects MAESTRA (news article)
Document Actions

MAESTRA (news article)

Learning from Massive, Incompletely annotated, and Structured Data

INESC TEC’s Laboratory of Artificial Intelligence and Decision Support (LIAAD) is participating in the European project MAESTRA (Learning from Massive, Incompletely annotated, and Structured Data), where the goal is to develop tools and methods for predictive learning tasks. The MAESTRA started in February 2014 and the LIAAD team includes João Gama, João Mendes Moreira, Carlos Ferreira, Alexandre Carvalho, among others.

Predictive modelling methods should be capable of dealing with large sets of complex and structured data generated by non-stationary processes and with a high degree of uncertainty. “We will develop the foundations (concepts and fundamentals) for the approaches, as well as the methodology (algorithm design and implementation)”, stresses João Gama, adding that the team “will also demonstrate the potential and the usefulness of the methods in problems occurring in different areas (molecular biology, sensor networks, multimedia, and social networks).”


The Maestra is a collaborative project of the Seventh Framework-Programme (FP7) in the area of information and communication technologies. Other than INESC TEC, the project involves the Institut Jozef Stefan (Slovenia), the SS Cyril and Methodius University (Macedonia), the Universita Degli Studi di Bari “Aldo Moro” (Italy) and the Ruder Boskovic Institute (Croatia). The duration of the project is 36 months.



LIAAD +351 22 209 4000