Babis' main research interest lies in data-driven algorithmics and applications. Specifically, he is interested in the theoretical foundations of data science,and in applications involving data-driven discovery. Application domains Babis is interested in include social networks, the World Wide Web and healthcare.

1. Big data analytics

   1. Methods, efficient algorithms, theory and implementations to analyze large datasets

   2. Single-pass streaming algorithms for real-time analytics

2. Graphs and networks

   1. Theory: Graph theory, random graphs and graph algorithms

   2. Applications: Mining real-world datasets, including the Web graph, social networks and biological datasets

3. Pattern theory

   1. Efficient optimization techniques

   2. Machine learning and data mining

   3. Bayesian probability theory