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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.
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https://plus.dataskeptic.com
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472472 ratings
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.
-------------------------------
Want to listen ad-free? Try our Graphs Course? Join Data Skeptic+ for $5 / month of $50 / year
https://plus.dataskeptic.com
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