Author Archives: lucr

Explore multilayer networks in Virtual Reality

Click for a video demo of MNET-VR

Click for a video demo of MNET-VR

Multilayer networks are an increasingly popular way to model complex relations between various types of entities and they have been applied to a large number of real-world data sets. Their intrinsic complexity makes the visualization of this type of network extremely challenging and still an open research area. To help the visual exploration of complex multilayer network structures, today we are releasing MNET-VR. MNET-VR is the output of a research project carried on with Leonard Maxim and supported by the Digital Design Department. MNET-VR explores the potential of Virtual Reality to visualize this type of network structure.

MNET-VR offers basic functions to visualize and filter multilayer network structures. MNET-VR does not offer, at this stage, the possibility to manipulate the network layout. A proper 3D layout of the network can be obtained through the R package multinet. While its primary goal is to explore multilayer networks, MNET-VR can also be used to visualize single layer networks using igraph and multinet. The export of of the files for visualization is done through two simple R functions that we make available on the website. MNET-VR is designed for Oculus Rift/Oculus Quest with Link.

Obaida Hanteer’s PhD defense “A Practical and Critical Look at the Problem of Community Discovery in Multilayer Networks”.

On June 11th, virtually in front of the Examination Committee – headed by Barbara Plank (IT University of Copenhagen) and with members Vito Latora (Queen Mary University of London) and Luca Aiello (Nokia Bell Labs) – Obaida Hanteer successfully defended his PhD.
Well done!

Obaida’s research took first a practical approach to community detection in the context of multilayer networks (mainly working with social media data [link, link]) and then, it stepped back and looked with a critical eye at the tools and the (often implicit) assumptions made by multilayer community detection methods [link, link]. His research, as acknowledged by the committee, was brave – in challenging the status quo and the assumptions of many well-established methods – and compelling helping us remembering the importance of asking questions about the tools and the methods we use.

After his experience at ITU Obaida accepted another interdisciplinary challenge by joining the Novo Nordisk Foundation – Center for Basic Metabolic Research at the University of Copenhagen where he’ll be working on applying multi-layer networks concepts to the interactions of human’s gut microbiome. We wish Obaida all the best for his future career!