Skip to content

School of CEEES | Glenn Department of Civil Engineering

Risk Engineering and System Analytics

Accessing Risks

Risk Engineering and System Analytics is an emerging field of civil engineering that is primarily concerned with the modeling, management, and mitigation of risks. This field of engineering is rapidly growing and interdisciplinary because it requires an understanding of structural engineering, natural catastrophe modeling, human error, data, business risk, supply chain, and other domains to effectively model and manage risk profiles for complex clients.

Male and female walk through manufacturing area with tablet.
Two people looking at digital screen of figures and graphs.

Risk Focus Areas

Risk Modeling

The development of quantitative models to estimate a variety of risks related to physical structures, natural catastrophes, and human error.


Risk Mitigation and Management

The use of data-driven models to develop robust plans to address an individual or intersection or risks for a client, region, or sector.


Supply Chain and Business Risk

The application of engineering modeling techniques to identify risks related to supply chains and business risks. For example, the implications of how a natural disaster would impact infrastructure.


Data Analytics

Data collection, processing, and analysis with the goal to estimate, mitigate, manage, or better understand risk.

Graduate Studies

The demand for knowledgeable risk engineers in the workforce is significant. A Master of Engineering degree in Risk Engineering and System Analytics prepares students to address various risks using data and validated models. This area of specialization provides a foundation for those individuals intending to pursue careers as risk managers, risk engineers, underwriters, researchers, or data scientists. The Masters of Engineering in Risk Engineering and System Analytics degree through the Glenn Department of Civil Engineering is an online program for working engineering professionals.

Apply | Graduate
Woman using tablet to view data.