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Richard Williams supervises 2 postgraduate research students. If these students have produced research profiles, these are listed below:

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Dr Richard Williams

Senior Lecturer

Richard Williams

The Management School



Tel: +44 1524 592214

PhD supervision

Dr Williams is always interested in PhD students who have research interests around computational modelling and simulation of complex real-world systems. His expertise is within agent-based modelling and simulation of complex biological and social systems, however he is also interested in modelling and simulation techniques broadly. At present, he has three main research interests: 1) computational modelling and simulation of complex systems (including digital twinning) in order to allow us to use simulation-based experimentation to answer novel questions of the real-world; 2) using existing computational models to enable us to develop novel statistical and software engineering techniques to ensure that computational models, especially agent-based models, are fit-for-purpose; and 3) using Natural Computing to provide biological metaphors for novel functionality within computational modelling and computational intelligence (e.g., Artificial Immune Systems, Artificial Neural Networks, Evolutionary Algorithms, etc). Although he is an expert in agent-based modelling and simulation, he is also comfortable in supervising PhD students who would like to use alternative modelling paradigms, e.g. Differential Equations, System Dynamics, Discrete Event Simulation, etc. If you are interested in pursuing a PhD with Dr Williams, then please get in touch via email to discuss the computational paradigm(s) and the domain (i.e. case study, business process, epidemiological system) that you are interested in.


Dr Richard Alun Williams PhD (York), FRSA, CITP CEng FBCS, SMIEEE, PMP, SFHEA

Dr Williams is a member of the Department of Management Science and actively involved in two of its research groups: Health Systems Research Group, and the Simulation and Stochastic Modelling Research Group. In addition, he is a member of: the multidisciplinary Data Science Institute (DSI); the Centre for Technological Futures (CTF); and the Lancaster Intelligent, Robotic and Autonomous Systems Centre (LIRA). Dr Williams' research revolves around the broad theme of Complex Systems Science. At present, he has particular interests in two main areas around: Modelling and Simulation of Complex Organisational Systems, and Project Management as a Complex System.

Currently focused around Complexity in Engineering and Technology Project Management, because:

The implementation and management of large engineering and technology projects often becomes the preserve of external service providers. For example, some of the larger software engineering projects consist of hundreds of customer and third-party team members, who may be located across multiple geographies, and time zones. It has been argued that the increasing size and complexity of these technology projects, leads them to exhibit the behaviours and traits of complex systems.

Without a clear understanding of the emergent behaviours of large engineering and technology projects, it is difficult to predict the likelihood of successful implementation. To investigate these emergent behaviours and project complexity, I am utilising a number of OR techniques, including Qualitative Data Analysis, Social Network Analysis, Agent-Based Modelling and Simulation, along with Cybernetics and various Systems Thinking approaches.

Dr Williams is a Member of the Department's Engagement Strategic Team. He has previously been the Early Career Representative on the University Research Committee (2014-15); the Director of Part I Undergraduate Studies in Management Science (2015-16); a Member of the Department's Undergraduate Teaching Steering Committee (2013-2020); a Member of the Department's Research & Enterprise Steering Committee (2017-18); Director of Business Analytics and Consultancy degree and the Director of Part II UG Studies within the Department of Management Science (2018-2020); a Member of the Faculty Research Ethics Committee (2016-2019); and a Member of the Pendle College Advisor Team (2014-2024).

Dr Williams has academic qualifications within the fields of Biochemistry (BSc Wales, MPhil Cambridge), Computational Biology (MRes York), Computer Science (MSc Kent), Computational Immunology (PhD York), and Higher Education (PGCertAP Lancaster). In addition he has a number of professional certifications and registrations, including: Chartered Professional Fellow and Chartered Engineer of the British Computer Society (CITP CEng FBCS), Project Management Professional of the Project Management Institute (PMP), Senior Member of the Institute of Electrical and Electronics Engineers (SMIEEE), Fellow of the Royal Society of Arts (FRSA), and Senior Fellow of the Higher Education Academy (SFHEA).

Career Details

  • 2019 +           Senior Lecturer in Management Science, Department of Management Science, Lancaster University
  • 2015 - 2019    Lecturer in Management Science, Department of Management Science, Lancaster University
  • 2013 - 2015    SAMS-ESRC-UKCES Management and Business Development Fellow, Department of Management Science, Lancaster University
  • 2004 - 2009    Project Manager (Consultant), Oracle Corporation UK Ltd
  • 2001 - 2004    Applications Consultant (Programmer), Oracle Corporation UK Ltd
  • 1999 - 2000    Associate Consultant, Cambridge Professional Development Ltd

PhD Supervisions Completed

Dr Fred J. Ingram - Awarded 2020 - "An Agent-Based Classroom Lessons Model and Simulation" - Currently a Research Fellow at the University of Huddersfield

Dr Nicola Platt - Awarded 2023 - "Understanding cross-boundary information flow for care coordination: The case of an alcohol care pathway" - Currently a Research Associate at the University of Central Lancashire

Dr Abdulrahman Aldogiher - Awarded 2023 - "Effects of Saudi Arabian Culture on IS-Facilitated Change Processes in Healthcare"

Dr Drupad Parmar - Awarded 2023 - "Input Uncertainty and Data Collection Problems in Stochastic Simulation"

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