The Computer Engineering group of DIEI mainly works on the following areas:

Information Visualization. Here, the main goal is the creation of tools that allow politicians, scientists, analysts, and decision-makers to visually analyze data on a massive scale and leverage them with scientific knowledge. These tools mainly focus on the analysis of networked datasets, which characterize most of the information handled in application domains. In 2009 the group founded an academic spin-off to facilitate and boost the technology transfer of its research into real-world scenarios.

Graph Drawing. Algorithms for the automatic representation of graphs and networks are a basic ingredient for the design of visual analytics tools. The group works actively in this field; two of its members participate in the steering committee of the International Symposium on Graph Drawing, the main annual event in the area, and since 2006 they organize an international workshop to promote research in this context. Both theoretical and practical aspects of graph drawing are addressed by the Computer Engineering group at DIEI.

Computational Geometry. Many graph drawing problems have a strong correlation with problems arising in computational geometry. Geometric graphs and proximity are classical topics studied in the group. In 2012, the group coordinated the program and the organizing committees of the 28th European Workshop on Computational Geometry.

Algorithm Engineering. Designing efficient algorithms and data structures is one of the crucial activities of automatic graph drawing and information visualization research. In this direction, the group has developed several software libraries and systems, some of them in cooperation with other national and international institutes, such as the University Roma Tre, the University of Ljubljana, and the University of Passau. The expertise of the group in algorithm design has been one of the key-factor in several national and European projects.

Information Retrieval and Data Mining. The use of visual analytics to support information retrieval and data mining has received an increasing attention in the last decade. A visual search clustering engine and an interactive environment for financial crime detection are among the most recent and successful systems developed by the group to this aim. Some members of the group wrote a chapter titled "Graph Visualization and Data Mining", in the book "Mining Graph Data - Ed. D. Cook and L. Holder, 2007".