Dr Richard Williams FRSA

Lecturer

Research Overview

I am a member of the Department of Management Science and actively involved in three of its research groups: Information Systems Research Group, Health Systems Research Group, and Simulation and Stochastic Modelling Research Group. In addition, I am an Affiliate Member of the multidisciplinary Data Science Institute. My research revolves around the broad theme of Complex Systems Analysis. At present, I have particular interest in two main areas around: Operational Research of Health and Illness, using both hard and soft OR approaches; and Computational Social Systems, where emphasis is currently applied to the use of computational, mathematical and statistical approaches to understand how to harness the complexity that arises in large multi-vendor Enterprise Systems implementations.

Lessons learned on development and application of agent-based models of complex dynamical systems
Williams, R.A. 11/11/2017 In: Simulation Modelling Practice and Theory.
Journal article

Investigating IKK Dynamics in the NF-κB Signalling Pathway using X-Machines
Williams, R.A., Timmis, J., Qwarnstrom, E.E. 5/06/2017 In: Proceedings of the 2017 IEEE Congress on Evolutionary Computation. IEEE p. 249-256. 8 p. ISBN: 9781509046027. Electronic ISBN: 9781509046003.
Conference contribution

Interprofessional spanning and maintaining boundaries when supporting potential embryo donors to stem cell research
Machin, L.L., Williams, R.A. 04/2017 In: Journal of Interprofessional Care. 31, 3, p. 342-350. 9 p.
Journal article

Rosen's (M,R) system as an X-machine
Palmer, M.L., Williams, R.A., Gatherer, D. 7/11/2016 In: Journal of Theoretical Biology. 408, p. 97-104. 8 p.
Journal article

Statistical techniques complement UML when developing domain models of complex dynamical biosystems
Williams, R.A., Timmis, J., Qwarnstrom, E.E. 29/08/2016 In: PLoS ONE. 11, 8, 27 p.
Journal article

Rosen's (M,R) system in Unified Modelling Language
Zhang, L., Williams, R., Gatherer, D. 01/2016 In: BioSystems. 139, p. 29-36. 8 p.
Journal article

Towards a platform model of the IL-1 stimulated NF-kB signalling pathway using communicating stream X-machines
Williams, R.A., Timmis, J., Qwarnstrom, E.E. 20/07/2015 In: CosMoS 2015. Frome : Luniver Press p. 107-110. 4 p.
Paper

The rise in computational systems biology approaches for understanding NF-κB signaling dynamics
Williams, R., Timmis, J., Qwarnstrom, E.E. 14/07/2015 In: Science Signaling. 8, 385, 2 p.
Journal article

Modelling conflict within the social networks of large multi-vendor software projects using communicating stream x-machines
Williams, R. 07/2015 In: Proceedings of the European Conference on Artificial Life. Cambridge, Mass. : MIT Press p. 79. 1 p. Electronic ISBN: 9780262330275.
Conference contribution

Computational models of the NF-κB signalling pathway
Williams, R., Timmis, J., Qwarnstrom, E.E. 29/09/2014 In: Computation. 2, 4, p. 131-158. 28 p.
Journal article

An agent-based model of the IL-1 stimulated nuclear factor-kappa B signalling pathway
Williams, R. 09/2014 University of York. 323 p.
Doctoral Thesis

Determining disease interventions strategies using spatially resolved simulations
Read, M., Andrews, P., Timmis, J., Williams, R., Greaves, R., Sheng, H., Coles, M., Kumar, V. 14/11/2013 In: PLoS ONE. 8, 11, 14 p.
Journal article

In silico investigation into dendritic cell regulation of CD8Treg mediated killing of Th1 cells in murine experimental autoimmune encephalomyelitis
Williams, R., Greaves, R., Read, M., Timmis, J., Andrews, P.S., Kumar, V. 04/2013 In: BMC Bioinformatics. 14, suppl. 6, 9 p.
Journal article

Spinning plates and juggling balls: project managing your PhD
Williams, R. 5/03/2013 In: EMBO Reports. 14, 4, p. 305-309. 5 p.
Journal article

Blurring the boundaries
Williams, R. 1/09/2011 In: ITNOW. 53, 5, p. 16-17. 2 p.
Journal article

In silico investigation into CD8Treg mediated recovery in murine experimental autoimmune encephalomyelitis
Williams, R., Read, M., Timmis, J., Andrews, P.S., Kumar, V. 2011 In: Artificial Immune Systems. New York : Springer p. 51-54. 4 p. ISBN: 9783642223709.
Chapter