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Owen Jones

Professor Owen Jones

Chair in Operational Research

School of Mathematics

+44 29225 10253
Abacws, Room 3.56, Senghennydd Road, Cathays, Cardiff, CF24 4AG
Available for postgraduate supervision


I am part of the Operational Research group in the School of Mathematics at Cardiff University. Operational research (OR) is a way of using analytical methods to help make better decisions. I am committed to developing the role of OR in the Environment, Energy & Sustainability. For example:

  • Sustainable water management
  • Optimal production and distribution of renewable energy (tidal, hydo, wind, etc.)
  • Risk quantification and disaster management (such as flood, drought and fire)
  • Biological modelling for population management and disease control

Operational research draws on a wide range of mathematical modelling and optimisation techniques, and seeks to balance economic, environmental and social objectives. My background is mostly in stochastic modelling and simulation, and I am particularly interested in likelihood free methods for fitting complex stochastic models to data.













Book sections

  • Jones, O., Robinson, A., Shield, M. and Sibley, J. 2017. The allocation of inspection resources. In: Robinson, A. P. et al. eds. Invasive Species: Risk Assessment and Management. UK: Cambridge University Press, pp. 1-16.




I am an applied mathematician with a background in data analytics, optimisation and simulation. Many of my projects involve assembling data from divers sources, using it to build simulation models, then using those models to inform management decisions. Previous collaborators include the Australian Department of Agriculture, Fisheries and Forestry (planning for the Post Entry Quarantine facility, a national infrastructure project); the Australian Office of Transport Security (improving security procedures in Australian airports); Rate Valuation Services (a financial services company);  McLaran International (the racing team); Merlin Power Systems (a feasibility study for an emergency response scheme for power generators in the UK); and National Air Traffic Systems (responsible for air traffic control in the UK).

My work makes use of a wide range of computational, analytical and mathematical techniques. I have taught graduate courses in machine learning and data mining, and I am the principal author of a best-selling text book on programming and simulation using the language R. Much of my current research concerns complex spatio-temporal environmental data, in particular problems of water runoff in catchment areas.

Current and Past Research Students

Thomas Poudevigne-Durance PhD: Generative Adversarial Networks for Rare Event Augmentation
Eferhonore Efe -Eyefa PhD: Simulation of Rainfall Events
Clement Twumasi PhD: In silico modelling of parasite dynamics
Lucy Henley PhD: Locating Bat Roosts using Diffusion Modelling
Nurudeen Oshinlaja PhD: Improving global estimates of groundwater storage variability by integrating models, in-situ observations, and remotely sensed data
Nooshin Mehrnegar PhD 2021: Bayesian integration of satellite geodetic data with models to separate land hydrology and surface deformation signals.
Nanda Aryal PhD 2018: Spatio-Temporal Rainfall Models.
Felicia Eng PhD 2016: Game-Theoretic Approaches to Natural Disaster Evacuation Modelling.
Adam Kowalewski PhD 2016: Volatility Homogenisation and Machine Learning for Time Series Forecasting.
Craig Mason MPhil 2016: Improved modelling of post fire hydro-geomorphic risks.
Geoffrey Decrouez PhD 2009: Generation of multifractal signals with underlying branching structure.
Wahib Arroum PhD 2008: Time-Changed Self-Similar processes: An Application To High Frequency Financial Data

Grants and consulting

2021 UKRO Interdisciplinary Funding Call: Discipline hopping for freshwater solutions
2021 CU Impact Fund: Digital solutions for bat protection during construction planning
2020 GCRF Catalyst project: Wastewater surveillance, from COVID19 to long term vision
2020 Ser Cymru: Wastewater Monitoring and Environmental Surveillance of SARS-Cov-2/COVID-19 Using Metaviromic Approaches
Cardiff University, Bangor University, Public Health Wales and Dŵr Cymru Welsh Water. Wales Environmental Wastewater Analysis & Surveillance for Health
EU Horizon2020 Grant: Translation of climate information into multilevel decision support for social adaptation, policy development and resilience to water scarcity in the Horn of Africa drylands
2019 KESS2: Generative Adversarial Networks for Rare Event Augmentation
2018 Royal Statistical Society Mardia Workshop Prize: funding for a sequence of workshops on extremal trends in weather (WET Weather)
2016 Australian Research Council Linkage Grant: Mitigating extreme water supply contamination in bushfire burned catchments
2015 Australian Federal Office of Transport Security: Report on Utility of Explosive Trace Detection Deployment Arrangements
2013 Australian Federal Department of Agriculture, Fisheries and Forestry: Risk Analysis for the new Post-Entry Quarantine Facility
2012 Rate Valuation Services: Multivariate Approaches to Breach Detection
2011 Bushfire Collaborative Research Centre Grant: Quantifying water quality risks following wildfire
2009 Norman Waterhouse Lawyers: Advice on a question of changing market share
2008 French-Australian Science and Technology Program International Science Linkage: Objective Risk Evaluation and Decision Making for Large Systems
2006 Melbourne University Grant: Brownian motion with a multifractal time-change
Australian Research Council Discovery Grant: Multifractal models in finance via the crossing tree
2005 Virgin Blue: Comments on Audit Sampling Dictionary
2004 Nuffield Foundation Grant: Modelling self-similar telecommunications data
2003 Merlin Power Systems: Modelling delivery of emergency generators
2002 McLaren International: Optimal settings for a race car
UK EPSRC Grant: Self-similar processes with embedded branching process
1999 UK National Air Traffic Systems: Analysis of Real-time Simulation Trials


Subjects Taught

Stochastic Operational Research Models
Stochastic Search and Optimisation
Risk, Hazard and Management


Owen Jones, Robert Maillardet, and Andrew Robinson.Introduction to Scientific Programming and Simulation Using R, Second Edition. The R Series, Chapman & Hall/CRC. 2014.

From the preface: “This book has two principal aims: to teach scientific programming and to introduce stochastic modelling. Stochastic modelling in particular, and mathematical modelling in general, are intimately linked to scientific programming because the numerical techniques of scientific programming enable the practical application of mathematical models to real-world problems. In the context of stochastic modelling, simulation is the numerical technique that enables us to analyse otherwise intractable models.

“Simulation is also the best way we know of developing statistical intuition.”