Prof. Krioukov is the Director of the DK-Lab at the Network Science Institute at Northeastern University. DK-Lab research deals mostly with theory and fundamentals of complex networks. Research topics of particular interest to the lab are latent network geometry, maximum-entropy random graph ensembles and random geometric graphs, causal sets, navigation in networks, and fundamentals of network dynamics. While research in the lab mainly focuses on theoretical aspects of network science, these theoretical results are often applied to real-world network data to gain new knowledge and insights about the data.
Highlights of recent DK-Lab research with application flavor include:
- Prediction of missing and future links in real networks using their latent hyperbolic geometry
- Design of optimal, as efficient as theoretically possible, routing for Internet-like communication networks, known as hyperbolic routing, which is currently being tested as a foundation of routing in future Internet architectures such as Named Data Networking
- Demonstration that the spatiostructural organization of the human brain is nearly as needed for optimal routing of information between different parts of the brain
- Discovery that the large-scale structure and dynamics of our accelerating universe represented as a growing quantum-gravity network (a causal set), are asymptotically identical to the structure and dynamics of many complex networks such as the brain or the Internet
- Demonstration that scale-free degree distributions, strong clustering, and community structure, observed in many real-world networks, naturally emerge from their latent non-Euclidean geometries
- Identification of a systematic series of properties for network analysis, akin to the Fourier or Taylor series in mathematical analysis, to quantify randomness in real networks, and to tell if a particular structural property of a given real network may or may not be related to any functions of the network