Emblematic projects

The heterogeneity of data sources and formats, as well as the distribution and massiveness they have reached, are just some of the elements that hamper the efficient and intelligent extraction of information.

Currently, the areas of data management, data analysis and machine learning are experiencing a challenging increasement in the amount of requirements of high complexity. But, along with the increment of the needs in this field, the number and variety of potential solutions proposed have also grown.

Our institute is working in parallel research lines, aiming to analyze and fully understand these emerging requirements, to detect the common elements they share and to extract from these variables potential cross-cutting solutions.

Once we have a clear vision of the requirements shared by these highly demanding and complex scenarios, we will work to establish the theoretical foundations that foster the development of languages capable of integrating data management with the analysis of data and tasks of machine learning, and having also the ability to be scalable and verifiable.

Directors of the Emblematic Project
Pablo Barceló
Aidan Hogan

Research Team
Leopoldo Bertossi
Claudio Gutiérrez
Éric Tanter
Renzo Angles
Federico Olmedo
Jorge Pérez
Carlos Buil
Gonzalo Navarro
Domagoj Vgroc
Juan Reutter
Cristián Riveros
Jorge Baier
Marcelo Arenas
Tomás Díaz
Sebastián Ferrada
Bernardo Subercaseux
Nelson Higuera
Pilar Jadue
Juan Navarro