Dr Richard Williams

Biography

Associate Professor in Computational Modelling of Complex Systems within the Institute of Engineering, Computing, and Advanced Manufacturing. Previously spent 12 years in the Department of Management Science, at Lancaster University Management School. First career as IT Consultant and Project Manager with Oracle Corporation UK Ltd.

Current research revolves around the broad area of Complex Systems Science, with particular focus on agent-based modelling and simulation of biological and social systems.

Teaching expertise revolves around Information Systems, Software Engineering, Software Project Management, and Natural Computing.

Qualifications and memberships

Academic qualifications include PGCert (Lancaster) in Academic Practice, PhD (York) in Computer Science, MPhil (Cantab) in Plant Biochemistry, MRes (York) in Computational Biology, MSc (Kent) in Computer Science, and BSc (Wales) in Biochemistry.

Professional registrations include Chartered Engineer, Chartered IT Professional and Fellow of the British Computer Society (CITP CEng FBCS), Senior Member of the Institute of Electrical and Electronics Engineers (SMIEEE), Project Management Professional (PMP Retired), Senior Fellow of the Higher Education Academy (SFHEA), and Fellow of the Royal Society for the Encouragement of Arts, Manufactures and Commerce (FRSA).

Academic and research interests

Research revolves around Complex Systems Science, with emphasis on the broad theme of Computational Intelligence and Computational Modelling of Complex Dynamical Systems to further our understanding of their complex emergent behaviours.

Within this area, current research projects relate to

1) Socio-Technical Complexity of Software, Technology and Engineering Project Management;

2) Computational Biology, with specific expertise in agent-based modelling and simulation of the Nuclear Factor-kappaB Signalling Pathway; 

3) Computational Social Science using Inspiration from Biology. This latter, interdisciplinary area intersects Social Science, Computer Science and Life Sciences, taking inspiration from the Immune System to design and develop functionality within machine learning and other types of computational algorithms.

Publications

For a full list of publications please visit Google Scholar: ‪‬ https://scholar.google.com/citations?user=6XpoURwAAAAJ&hl=en 

Selected publications:

Williams, R.A. (2025), Towards an Agent-Based Model using a Hybrid Conceptual Modelling Approach: a case study of relationship conflict within large enterprise system implementations, Journal of Simulation, 19(2), 166-178

Williams, R.A. (2024), A Systematic Literature Review of Hybrid Conceptual Modeling, In: M. Fakhimi and N. Mustafee (Ed), Hybrid Modeling and Simulation: Conceptualizations, Methods, and Applications, 47-72, Springer Nature Lin, F., Evans, R., Kharel, R., and

Williams, R.A. (2022), Competitive Intelligence and Product Innovation: The Role of Open-Mindedness and Inter-Functional Coordination in Chinese IT SMEs, IEEE Transactions on Engineering Management, 62(2), 314-328

Fayoumi, A., and Williams, R.A. (2021), An Integrated Socio-Technical Enterprise Modelling: A Scenario of Healthcare System Analysis and Design, Journal of Industrial Information Integration, 23, 100221

Williams, R.A. (2021), User Experiences using FLAME: A Case Study Modelling Conflict in Large Enterprise System Implementations, Simulation Modelling Practice and Theory, 106, 102196

Williams, R.A. (2020), Cybernetics of Conflict within Large Technology and Software Engineering Programmes, IEEE Access, 8, 94994-95018

Williams, R.A. (2019), Conflict Propagation within Large Technology and Software Engineering Programmes: A Multi-Partner Enterprise System Implementation as case Study, IEEE Access, 7, 167696-167713

Williams, R.A. (2018), Lessons Learned on Development and Application of Agent-Based Models of Complex Dynamical Systems, Simulation Modelling Practice & Theory, 83C, 201-212

Conferences

Regular presenter at National and International Conferences focused on Simulation, Operational Research, Computational Intelligence, and Artificial Life.

View staff directory