Risk and security analytics
Explore our work in risk and security analytics, 1 of our areas of expertise in Operational Research and Logistics
People and organisations learn from failure more than from success. By analysing disasters, we can learn how to cope faster and make failures rarer and less costly.
We're experts in analysing risk and exploring how best to use past failures to improve the quality and resilience of a given operation. Today, governments and organisations around the world are using our research in this area to guide their decisions in risk analysis and security threats.
We use techniques for decision analysis, with an emphasis on applying advanced operational research techniques to cases of major failures and disasters. We're also developing innovative analytic approaches to address decisions about risk and security threats, focusing on decisions that must involve a group of people.
For example, in the aftermath of a serious accident, stakeholders focus on trying to understand the root cause. This makes it possible for us to ask questions not usually asked and gather data not usually gathered.
To detect potential security and risk threats, organisations must usually process large volumes of data – and the challenges to doing this effectively include the mass and variety of data, the nature of information, and time pressures to get things done.
And through our research, we're also helping minimise the impact that these challenges can cause – from inconsistent approaches to decision-making, to increased divergence from rules.
Our research covers the following topics
- Maritime disasters and oil and gas spills – We're learning from failures and techniques for decision analysis, applied to cases of major failures and disasters
- Nuclear power generation – We're identifying challenges that arise when nuclear energy facilities are brought into operation, with the aim to advise stakeholders on how to overcome these challenges
- Security threats – We're developing innovative analytic approaches to address errors in judgement and enable decision makers to better appreciate the value of security information
- Risk against cancer – We're developing algorithms that can guide robots to perform precise operations to target prostate cancer cells
Funding and collaborations
We collaborate with various European institutions in the field of risk analysis – for example, we've been funded to assess risk and hazards in the arctic polar circle. This enables us to investigate case studies and develop workshops for training in risk and reliability analysis.
Recent projects have received funding from major funding organisations including the European Social Research Council (ESRC), Centre of Risk Evidence and Security Threats (CREST), EU Interreg 2 Seas Programme, and EU Horizon 2020.
Methods and facilities
We're experts in machine learning and artificial intelligence, multiple criteria decision making, and root cause analysis modelling and assessment of vulnerabilities within a system. Our lab facilities are equipped with advanced software. We can use this software train people in diverse methods of risk and security decision analysis.
Projects and publications
Our researchers have professional industry experience and a track record in publishing findings in high impact journals and in writing books used for training and teaching. Our research is regularly published leading academic journals within the field, including the Journal of Safety Science, Journal of Engineering Failure Analysis, Journal of Expert Systems with Applications, and European Journal of Operational Research.
Recent project highlights
Developing analysis techniques and risk assessment concepts, and selecting appropriate response policies to enhance risk assessment and decision making in the Arctic Polar Circle
Developing machine learning techniques that can facilitate individual and group assessments of information relating to security threats
Developing an algorithm that can aid high precision robotic surgery to tackle prostate cancer
Discover our areas of expertise
Risk and security analytics is 1 of our 8 areas of expertise in Operational Research and Logistics. Explore the others below.
Decision and data analytics
Research in the design of decision support systems, and use of data analysis, to help people make better decisions through a better understanding of their data.
Exact and metaheuristic solution methods
Heuristic and metaheuristic techniques are powerful and flexible research methodologies that offer a faster way of solving complex logistical challenges.
Healthcare analytics
From nurse scheduling to infection and disease modelling, our research provides decision-makers in the healthcare sector with optimal strategies for treatment.
Multiple criteria decision aid
Approaching complex problems with conflicting criteria, or uncertain data, our research helps people make more informed decisions.
Transportation and maritime systems
Our research focuses on developing innovative optimisation models and decision support systems, to help improve the mobility of people, goods and services.
Optimisation modelling
As well as improving business efficiency, we're enabling people to make optimal decisions that can lead to practices with enhanced economic, environmental or social benefits.
Renewable energy and sustainability analytics
Modelling to answer a host of questions, from how to produce renewable energy more cheaply, to how the associated logistics can be sustainable.
Research groups
Centre for Operational Research and Logistics
We're using our expertise in analytics, system design, simulation, programming, and forecasting to help organisations around the world make better decisions.
Logistics Operational Research and Analytics Group
We're researching how we can apply quantitative methodologies to improve decision-making across a range of diverse fields of application.
Interested in a PhD in Operational Research & Logistics?
Browse our postgraduate research degrees – including PhDs and MPhils – at our Operational Research & Logistics postgraduate research degrees page.