Our research examines how disruptions propagate across interconnected infrastructure, supply chains, and economies, and how these cascading effects develop into systemic risks. We focus on climate risk, infrastructure and supply-chain vulnerability, and the wider economic and social consequences of disruption.
We combine AI methods with social science to understand these processes and support better decisions. Our work seeks to help governments and businesses anticipate emerging risks, assess consequences across interconnected systems, and develop more effective strategies for resilience and risk management.
We aim to build lasting research infrastructure rather than produce isolated outputs. Publications, reports, datasets, models, tools, case studies, and collaboration networks are developed as connected and reusable resources that support cumulative research, practical application, and long-term capability building.
Principles
- We start from real risk scenarios and clearly defined decision needs, ensuring that our research remains practically meaningful.
- Evidence, data, methods, and models should be interpretable, traceable, reproducible, and open to scrutiny.
- Research outputs should connect with one another and remain reusable, allowing knowledge, tools, and capabilities to accumulate over time.
- Partnerships should lead to shared projects, concrete outputs, and lasting research capability.