Criminal Networks

In this episode we talk with Justin Wang Ngai Yeung, a PhD candidate at the Network Science Institute at Northeastern University in London, who explores how network science helps uncover criminal networks.

Justin is also a member of the organizing committee of the satellite conference dealing with criminal networks at the network science conference in The Netherlands in June 2025.

Listeners will learn how graph-based models assist law enforcement in analyzing missing data, identifying key figures in criminal organizations, and improving intervention strategies.

Key insights include the challenges of incomplete and inaccurate data in criminal network analysis, how law enforcement agencies use network dismantling techniques to disrupt organized crime, and the role of machine learning in predicting hidden connections within illicit networks.

Guest

Justin Wang Ngai Yeung: Justin Wang Ngai Yeung is a PhD candidate in Network Science at the Network Science Institute, Northeastern University (London). Using network science, data science and physics, his work focuses on characterizing, modelling and inferring complex human interactions in light of evolving socio-technical systems, both online and offline. Justin obtained his MSc in Social Data Science at the Oxford Internet Institute and was a visiting research intern at the Max Planck Institute for Human Development. Justin's work has appeared in various journals and conferences, including AI & Society, Conference on Complex Systems and International Communication Association (ICA) Conference.