I am currently Head of Department of Management Science in Strathclyde Business School. My area of research is Risk Analysis and Decision Making under uncertainty. I focus on working at the interface between research and practice, trying to ensure that academic research impacts businesses and society. 

I helped to co-found two industry-facing research units: the Risk Consortium in 2009 and the Centre for Informed Decision Analytics (IDeA) in 2018. The Risk Consortium was established to provide a platform for industry partners to share problems, solutions and cutting-edge techniques for quantitative risk analysis and reliability modelling and to bridge the gap between industry and research. IDeA is a dedicated industry facing unit for the Department of Management Science that escalates current activity, enhances research output, impact and grant proposals, and enhances our teaching portfolio.

My research has been published in 3* and 4* journals (Association of Business Schools list) and I am responsible for supervising and managing the output of 5 KE staff, one postdoc researcher and 5 PhD students. I have experience teaching on a wide range of courses; both to students and practitioners. I am on the editorial board of the IMechE Journal of Risk and Reliability, on the Board of Directors for the European Safety and Reliability Data Association, and I am a Fellow of the Operational Research Society.

My research interests focus on modifying and applying Management Science methods to solve industrial problems. 

My main area of research is in Reliability, Availability and Maintainability (RAM) modelling. To date, I have developed tools for modelling reliability during procurement, diagnostic and prognostic modelling, maintenance scheduling and degradation modelling.

I am also interested in using both statistical and machine learning models to analyse complex datasets. Examples of work to date include prognostic modelling of offshore SCADA data from wind turbines, forecasting offshore wind speeds and wave heights, and modelling performance of athletes.  

I have a broad interest in a wide range of mathematical models to support decision making. For example, I am interested in developing methods for modelling and assessing dependencies between uncertain quantities for use in decision models and have developed models using techniques such as Bayesian Networks and Bayes linear. I have used discrete event simulation to model maintenance schedules and logistic operations. I also have interest in optimisation models such as multi-objective optimisation and rolling optimisation.

Future areas of study will focus on big data and reliability, degradation and maintenance, load sharing, asset management and residual life. 

• Reliability, Availability and Maintainability modelling
• Expert Judgement
• Analytics
• Quantitative Modelling for Decision Making 

I have experience applying these methods and models to real world problems such as those found in industry and engineering. I have worked extensively in the following sectors: power generation (coal, onshore and offshore wind, nuclear); utilities (water, transportation, Oil and Gas); and military (aerospace, electronics, land vehicles)

My teaching portfolio focuses on teaching risk management and decision making tools to postgraduate or postexperience students. For example, I regularly contribute to the MBA Analytical Support for Decision Making module, with experience teaching in Switerland, Dubai, Abu Dhabi, Bahrain and Madrid. I teach Risk Analysis and Management to Engineering postgraduate students and Management Science methods to the Wind Energy Centre for Doctoral Training students. I also teach on industry facing courses with SSE and Ibderdrola.