Skip to content

About Prof Steve Wilkinson

Steve began studying Natural Sciences at Trinity College, Cambridge and ended up graduating in Chemical Engineering in 1992. He then went to the Centre for Process Systems Engineering at Imperial College, London where he was awarded a PhD in 1996 on 'Aggregate Formulations for Large-Scale Process Scheduling Problems'. This research was part-funded by Unilever Research and provided new techniques for solving large-scale supply chain problems which have since been incorporated into commercial software systems.

He then had a 3 year spell in the United States working as a Research Engineer for E. I. DuPont de Nemours in Wilmington, Delaware. During this time he applied techniques of mathematical optimization to improve productivity of flexible process plants operating in global supply chains. He continued this theme of work back in the UK working for with Prescient Systems and then Decision Engines Limited providing consultancy and software tools for complex business optimisation problems in the process industries.

Towards the end of this time academia beckoned and Steve became fascinated by the emerging field of systems biology and how engineering methods could be used to understand living cells enabling the design of new processes. He went to Manchester University in 2005 as a Pfizer funded Research Fellow working on `Dynamic Modelling of the p38 MAP Kinase Signalling Pathway´ with Professor Douglas Kell. This was followed by a BBSRC funded project on `The Systems Biology of Regulation´ with Professor Hans Westerhoff.

In September 2008 Steve was appointed as a lecturer in the Department of Chemical and Biological Engineering at the University of Sheffield and in September 2013 he became Head of Chemical Engineering at the University of Chester as a founding member of the new Faculty of Science and Engineering.

Teaching

Steve is passionate about working with colleagues from engineering and science to design and deliver problem based teaching with strong industrial involvement. All our teaching is based at the Thornton Science Park which is also home to a number of technology companies. Interdisciplinary teaching is a key theme, especially in areas where scientific principles meet engineering applications.

Module: SE4003 Mathematics for Scientists & Engineers

Research

Steve's research involves the use of computational modelling and optimisation in a variety of applications from the level of the cell to the level of the process flowsheet including:

  • Modelling and optimisation of bioprocess flowsheets
  • Integration of wastewater treatment and algal growth for biodiesel and biomethane
  • Cell models of signalling, gene expression and protein translation for biopharmaceuticals
  • Development of Sentero for simulation and analysis of biochemical networks
  • Solution of large optimisation problems for parameter estimation and control

Published Work

Selected publications:

Morgan, A. E., Mooney, K. M., Wilkinson, S. J., Pickles, N., & Mc Auley, M. T. (2016). Mathematically modelling the dynamics of cholesterol metabolism and ageing. Biosystems, 145, 19-32.

Al-Mashhadani, M. K., Wilkinson, S. J., & Zimmerman, W. B. (2016). Carbon dioxide rich microbubble acceleration of biogas production in anaerobic digestion. Chemical Engineering Science, 156, 24-35.

Al-Mashhadani, M. K., Wilkinson, S. J., & Zimmerman, W. B. (2015). Airlift bioreactor for biological applications with microbubble mediated transport processes. Chemical Engineering Science, 137, 243-253.

Pybus, L. P., Dean, G., West, N. R., Smith, A., Daramola, O., Field, R., Wilkinson, S. J. & James, D. C. (2013). Model-directed engineering of “difficult-to-express” monoclonal antibody production by Chinese hamster ovary cells Biotechnol Bioeng, (published online: 14 Nov 2013, DOI: 10.1002/bit.25116).

Liu, J., Mukherjee, J., Hawkes, J. J. and Wilkinson, S. J. (2013), Optimization of lipid production for algal biodiesel in nitrogen stressed cells of Dunaliella salina using FTIR analysis. J. Chem. Technol. Biotechnol..doi: 10.1002/jctb.4027

Kilner, J., Corfe, B. M., & Wilkinson, S. J. (2011). Modelling the microtubule: towards a better understanding of short-chain fatty acid molecular pharmacology..MolBiosyst, 7(4), 975-983.

Brown, M., He, F., & Wilkinson, S. J. (2010).Properties of the proximate parameter tuning regularization algorithm. Bulletin of Mathematical Biology, 72(3), 697-718.

Dimelow, R. J., & Wilkinson, S. J. (2009). Control of translation initiation: a model-based analysis from limited experimental data. J R Soc Interface, 6(30), 51-61.

Wilkinson, S. J., Benson, N., & Kell, D. B. (2008). Proximate parameter tuning for biochemical networks with uncertain kinetic parameters..MolBiosyst, 4(1), 74-97.

Wilkinson, S. J., Spasic, I., & Ellis, D. I. (2006).Genomes to systems 3. Metabolomics, 2(3), 165-170.

Wilkinson S. J. (2001), It’s all in the Timing, The Chemical Engineer, Issue 717, (March 2001).

Wilkinson S. J., Cortier A., Shah N. and Pantelides C. C. (1996), Integrated Production and Distribution Scheduling on a Europe-Wide Basis, Computers chem. Engng., 20, S1275-S1280.

Wilkinson S. J., Shah N. and Pantelides C. C. (1995), Aggregate Modelling of Multipurpose Plant Operation, Computers chem. Engng., 19, S583-S588.

Qualifications

MA (Cantab), MEng, PhD, DIC