John Quigley


  • United Kingdom

Accepting PhD Students

1995 …2022
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Personal profile

Personal Statement

John is an Industrial Statistician with expertise in developing and applying statistical and stochastic methods to build decision support models. In particular, he has extensive experience in developing models for reliability growth analysis.  For example, with his colleague Professor Walls, they were actively leading activities in the DTI/aerospace industry funded project, Reliability Enhancement Methodology and Modelling (REMM) which was awarded the Simms Prize by the Royal Aeronautical Society.  He has been involved in consultancy and applied research projects for reliability growth with, for example, Aero-Engine Controls, Rolls Royce, Irving Aerospace, BAE SYSTEMS and the MOD. The model developed as part of the REMM project is included in the industry standard for reliability growth analysis methods, BS/IEC 61164 as well as contributing to the Strathclyde Business Schools impact cases for the Research Enhancement Framework.

Beyond defence, John has experience of developing decision support models for asset management for energy utilities (e.g. Scottish Power, SSE), water utilities (KTP with Scottish Water) and critical infrastructure (e.g. anchorage condition assessment of Forth Road Bridge).  Wider modelling has been in support of risk analysis (e.g. supplier risk analysis with Rolls Royce as part on a major ongoing EPSRC research project, risk of train derailments with Railway Safety and Standards Board). 

John has worked with the European Food Safety Agency (EFSA) training staff for elicitation and quantification of expert uncertainty as well as leading the COST Working Group on Processes and Procedures for eliciting expert judgment.  The COST project resulted in the book Elicitation: The Science and Art of Structuring Judgement.

John is an Associate of the Society of Actuaries, a Chartered Statistician, and a member of the Safety and Reliability Society.  He has a Bachelor of Mathematics in Actuarial Science from the University of Waterloo, Canada and a PhD in Management Science from the University of Strathclyde. 

Teaching Interests

John provides specialist teaching for a number of programmes at various levels.  These have included teaching Management Science at all levels of undergraduate and postgraduate as well as Executive Education.  The postgraduate programmes for which he teaches include MSc in Operational Research and Business Analysis & Consulting as well as MBA.  Together with Professor Scholarios from the department of Human Resouce Management, he developed the Research Methods training module for all research students in the Strathclyde Business School.  John has taught in 10 different international centres across Europe, the Middle East and South East Asia, as well as Executive Education in Canada. 


John is committed to making effective use of technology to support teaching and learning.  He has been involved in managing, developing and teaching on pedagogically successful online and distance courses, as well as investigating the effectiveness of using virtual reality environments to support teaching.    

Education/Academic qualification


Bachelor of Mathematics, University of Waterloo


  • Uncertainty
  • Statistics
  • big data analytics
  • decision making
  • Bayesian Networks
  • expert judgement

Fingerprint Dive into the research topics where John Quigley is active. These topic labels come from the works of this person. Together they form a unique fingerprint.

  • 2 Similar Profiles
Reliability Growth Mathematics
Risk management Engineering & Materials Science
Supply chains Engineering & Materials Science
Bayesian networks Engineering & Materials Science
Elicitation Mathematics
Expert Judgment Mathematics
Empirical Bayes Mathematics
Aerospace industry Engineering & Materials Science

Network Recent external collaboration on country level. Dive into details by clicking on the dots.

Projects 2004 2022

Research Output 1995 2019

Mapping conditional scenarios for knowledge structuring in (tail) dependence elicitation

Werner, C., Bedford, T. & Quigley, J., 29 Nov 2019, (Accepted/In press) In : Journal of Operational Research Society.

Research output: Contribution to journalArticle

Risk analysis
Decision theory
Tail dependence
4 Downloads (Pure)

Quantifying the benefit of SHM: can the VoI be negative?

Verzobio, A., Bolognani, D., Zonta, D. & Quigley, J., 27 Mar 2019, 13th Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2019. Lynch, J. P., Huang, H., Sohn, H. & Wang, K-W. (eds.). Bellingham, WA, USA, Vol. 10970. 8 p. 109701I

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

Open Access
Value of Information
structural health monitoring
Structural health monitoring
Health Monitoring


Data for: "A Probabilistic Design Reuse Index for Engineering Designs"

Purves, D. (Creator), Corney, J. (Creator), Quigley, J. (Creator), Annamalai Vasantha, G. V. (Creator), Sherlock, A. (Creator), Stuart, S. (Creator), University of Strathclyde, 15 Jan 2020



A conceptual model of trust in emergency evacuation : evidence from Indonesian volcano eruptions

Author: Hilya Mudrika Arini, H., 1 Dec 2017

Supervisor: Bedford, T. (Supervisor) & Quigley, J. (Supervisor)

Student thesis: Doctoral Thesis


KTP Award with Scottish Water

John Quigley (Recipient), 2010

Prize: Prize (including medals and awards)


Activities 2008 2011

Risk Governance

John Quigley (Organiser)

Activity: Participating in or organising an event typesTo be assigned

Workshops on Mathematical Methods in Reliability

John Quigley (Organiser)

Activity: Participating in or organising an event typesOrganiser of special symposia


International standards and working practices of UK Aerospace & Defence industry changed by reliability growth modelling

Lesley Walls (Participant), John Quigley (Participant)

Impact: Impact - for External PortalEconomic and commerce, Professional practice, training and standards