Our research focuses on graphs and their multiple applications: from integrating graph databases to program comprehension or from finding subgraphs efficiently to the Web of Data.

While graph analytics is not a likely replacement for the standard relational databases that many companies will stick with for many years to come, the value of graphs for a particular set of ...

Many of us thought linear algebra and graph structures were concepts we'd never again have to deal with after high school. However, these concepts underpin a variety of transactions, from Internet ...

Scalable Graph Algorithms for Bioinformatics using Structure, Parameterization and Dynamic Updates, ERC Consolidator Grant, 9/2025-8/2030 Sequencing technologies have developed to be cheap and ...

GraphLab, a Seattle-based startup trying to make machine learning more accessible, has raised an $18.5 million series B round of venture capital and has changed its name to Dato. The company has now ...

Seattle startup GraphLab claims it is building the “fastest machine-learning analytics engine for graph datasets”, based on the popular open-source distributed graph computation framework with the ...

Our research is focused on graph algorithms, from both a theoretical perspective, and a practical perspective motivated by real-world problems in Bioinformatics, such as genome sequencing technologies ...