Authors
Zhe Chen, Luca Laport, Erjia Meng, Zhefu Qin, Diego Velázquez
Sponsor
Rel8ted, Ryan Hilimoniuk
Instructor
Professor Ajay Anand
Abstract
Modern supply chains face growing risks from geopolitical instability, financial uncertainty, and supplier concentration. Our project aims to identify hidden vulnerabilities and improve supply chain resilience using data science. We analyzed global shipment records, clustered suppliers by risk, and mapped trade networks to expose critical dependencies. Our results reveal overreliance on high-risk regions and firms, especially between China and the U.S. By integrating network analysis and machine learning, we offer a scalable framework to support data-driven risk mitigation and sourcing strategies.
