After extreme events, a community’s socio-economic recovery depends on the recovery of its infrastructure systems, such as power and water distribution systems, transportation networks, communications systems, and critical buildings. We need to build resilient infrastructure systems to support the national economy and wellbeing of citizens, resist extreme events, and ensure their capacity to rapidly recover to full service afterwards. The PRAISys (Probabilistic Resilience Assessment of Interdependent Systems) platform will perform post-event resilience analysis of communities by addressing stochastic interdependencies among infrastructure systems in a probabilistic way.

CatModeling applied to floods

Flood is the most common event that leads to significant property damage. The CatModeling approach is an effective scientific paradigm to assess expected losses and plan accordingly. In this research, state-of-the-art CatModeling techniques will be used for comprehensively investigating the the resilience and risk of engineering structures under flood hazards. Supported with cutting-edge experimental and computational resources, this research will provide a new insight into the accurate and efficient flood loss estimation and prevention.

CatModeling applied to zoonoses

With the ability to fast spread, coonoses are huge threat to the the world. CatModeling can help investigate and mitigate the spread of zoonoses.

We designed and implemented a pipeline to analyze Ebola data using regression and machine learning techniques. Our results and conclusions are relevant to identify the regions in Sierra Leone at risk of EVD spillover and, consequently, to design and implement policies for an effective deployment of resources (e.g., drug supplies) and other preventative measures (e.g., educational campaigns).

Modeling the financial aspects of extreme events

This research includes modeling the financial impact of extreme events, their impact on insurance, as well as developing strategies for companies in the insurance sector to optimally play their role under these circumstances. Understanding risk is the first step for insurance providers to be better prepared when an extreme event happens and to be able to provide the adequate response to the people and businesses impacted. Mathematical tools from risk valuation and financial markets modeling will play an important role in this research.