Machine Learning for Complex Networks


Our research addresses foundations of algorithmic and statistical data analysis. In many of our works, we model and analyze large data sets from a graph or network perspective. We also develop new data science techniques for complex relational data, and apply them in the context of software engineering, information system and computational social science. Our approach is quantitative, data-driven and interdisciplinary, combining methods from computer science, mathematics and physics.