Staff Profile

Overview

I am a Chemical Engineer, with a PhD in Chemical Process Modelling and Control. My teaching, research and industrial experience is in the area Process Systems Analysis, although during my career I have taught a broad spectrum of Chemical Engineering subjects. I am a member of the Process Intensification group, focussing on the development of Advanced Modelling, Estimation and Control technologies.

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For over twenty years I have researched in the area of Process Systems Modelling and Control. My research skill set involves a comprehensive knowledge of Chemical Engineering Processes and the development of Advanced Process Control and Inferential Measurement technologies.

Current Work

• Investigation of control and on-line optimisation opportunities of a waste-water treatment plant
• Smart filtration technologies for UK green energy production (KTP)
• Development of a novel hybrid grey box framework for adaptive design, optimisation and control of drinking water membrane filtration technology for non-interconnected remote areas (Newton Fund)

Recent Papers

• Cummings, T., Adamson, R., Silcock, A. and Willis, MJ (2017) Retrospective and predictive optimal scheduling of nitrogen liquefier units and the effect of renewable generation, Applied Energy, 208, 158 - 170
• Adamson, R., Hobbs, M., Silcock, A. and Willis, MJ (2017) Steady-state optimisation of a multiple cryogenic air separation unit and compressor plant, Applied Energy 189, 221-232
• Willis, M.J and von Stosch, M. (2017) L0-constrained regression using mixed integer linear programming, Chemometrics and Intelligent Laboratory Systems 165, 29-37
• Adamson, R., Hobbs, M., Silcock, A. and Willis, MJ (2017)  Integrated real-time production scheduling of a multiple cryogenic air separation unit and compressor plant, Computers & Chemical Engineering.
• Willis, M.J. and von Stosch, M. (2017) Simultaneous parameter identification and discrimination of the nonparametric structure of hybrid semi-parametric models, Computers & Chemical Engineering 104, 366-376
• von Stosch, M. and Willis, M.J. (2016) Intensified design of experiments for upstream bioreactors, Engineering in Life Sciences
• Willis, MJ. and von Stosch, M. (2016) Inference of chemical reaction networks using mixed integer linear programming, Computers & Chemical Engineering 90, 31-43

Teaching

I teach Undergraduate (UG) and Postgraduate (MSc) students fundamental and advanced aspects of Chemical Engineering specifically in the area of Process Systems Engineering. I teach at BEng, MEng and MSc level with class sizes ranging from five to one hundred and fifty students with mixed ability with a diverse range of student backgrounds. I have lectured/taught the following subjects, Material and Energy Balances (Stage 1), Heat Transfer (Stage 1), Reactor Engineering (Stage 2), Process Control (Stage 2, 3, 4 and MSc), Optimisation (Stage 4 and MSc), Computing techniques (Stage 1), Modelling and Simulation (MSc), Heat Exchanger Design (Stage 2), Design of Heat Exchange Networks (Stage 2). I also supervise UG Design Projects (Stage 4) as well as student research projects (Stage 4 and MSc).

I am currently Degree Programme Director for our BEng / MEng Chemical Engineering degrees, both in the UK and Singapore.

I am Chair of the Board of Studies (Chemical Engineering), Chair of the Undergraduate Examination Board (Chemical Engineering), Member of the Personal Extenuating Circumstances (PEC) Committee, Member of the Undergraduate Staff-Student Committee.

• Willis MJ, vonStosch M. Inference of chemical reaction networks using mixed integer linear programming. Computers and Chemical Engineering 2016, 90, 31-43.
• Searson DP, Willis MJ, Wright A. Reverse Engineering Chemical Reaction Networks from Time Series Data. In: Dehmer, M., Varmuza, K., Bonchev, D, ed. Statistical Modelling of Molecular Descriptors in QSAR/QSPR. Weinheim, Germany: Wiley-VCH Verlag GmbH, 2012, pp.327-348.
• Hii C, Searson DP, Willis MJ. Evolving toxicity models using multigene symbolic regression and multiple objectives. International Journal of Machine Learning and Computing 2011, 1(1), 30-35.
• Searson DP, Leahy DE, Willis MJ. Predicting the toxicity of chemical compounds using GPTIPS: a free genetic programming toolbox for MATLAB. In: Ao, S-I., Castillo, O., Huang, X, ed. Intelligent Control and Computer Engineering. Netherlands: Springer, 2011, pp.83-93.
• Gao Y, Kipling K, Glassey J, Willis M, Montague G, Zhou YH, Titchener-Hooker NJ. Application of Agent-Based System for Bioprocess Description and Process Improvement. Biotechnology Progress 2010, 26(3), 706-716.
• Searson DP, Leahy DE, Willis MJ. GPTIPS: An Open Source Genetic Programming Toolbox For Multigene Symbolic Regression. In: International MultiConference of Engineers and Computer Scientists 2010 (IMECS). 2010, Kowloon, Hong Kong: Newswood Ltd.
• Morrison GA, Searson DP, Willis MJ. Using genetic programming to evolve a team of data classifiers. World Academy of Science, Engineering and Technology 2010, (72), 261-264.
• Worth R, Novakovic K, Willis MJ, Wright AR, Grace J. The Importance of Mass Transfer in Gas-Liquid Reactions. Chemspeed publications, 2009. Available at: http://www.chemspeed.com/remositoryfunc-startdown/109/remositoryfunc-startdown/109.
• Novakovic K, Willis MJ, Wright AR, Grace J. Utilising high throughput technologies for determination of the reaction mechanism of the L-proline catalysed aldol reaction. Chemspeed publications, 2009. Available at: http://www.chemspeed.com/remositoryfunc-startdown/427/remositoryfunc-startdown/427.
• Novakovic K, Willis MJ, Wright AR, Grace J. Utilising high throughput technologies for the determination of the reaction mechanism of the L-proline catalysed aldol reaction. Chemspeed publications, 2009. Available at: http://www.chemspeed.com/remositoryfunc-startdown/430/remositoryfunc-startdown/430.
• Novakovic K, Willis MJ, Wright AR. Effect of gas-liquid mass transfer rates on the palladium catalysed phenylacetylene oxidative carbonylation reaction. In: AIChE Annual Meeting. 2008, Philadelphia, USA.
• Worth R, Novakovic K, Willis MJ, Wright AR. Are high throughput technologies useable for engineering scalability?. In: AIChE Annual Meeting. 2008, Philadelphia, Pennsylvania, USA.
• Burnham SC, Searson DP, Willis MJ, Wright AR. Inference of chemical reaction networks. Chemical Engineering Science 2008, 63(4), 862-873.
• Grosjean C, Novakovic K, Scott SK, Whiting A, Willis MJ, Wright AR. Product identification and distribution from the oscillatory versus non-oscillatory palladium(II) iodide-catalysed oxidative carbonylation of phenylacetylene. Journal of Molecular Catalysis A: Chemical 2008, 284(1-2), 33-39.
• Novakovic K, Grosjean C, Scott SK, Whiting A, Willis MJ, Wright AR. The influence of oscillations on product selectivity during the palladium-catalysed phenylacetylene oxidative carbonylation reaction. Physical Chemistry Chemical Physics 2008, 10(5), 749-753.
• Todd H, Novakovic K, Willis MJ, Wright AR. Towards predicting catalyst performance in reactive distillation systems. In: AIChE Annual Meeting. 2008, Philadelphia, USA.
• Mukherjee A, Searson DP, Willis MJ, Scott SK. Two-dimensional simple proportional feedback control of a chaotic reaction system. Physical Review E: Statistical, Nonlinear, and Soft Matter Physics 2008, 77(4), 046215.
• Novakovic K, Mukherjee A, Willis MJ, Wright AR, Scott SK. Using perturbation experiments to study the dynamic behaviour of the palladium-catalysed phenylacetylene oxidative carbonylation. In: Gordon Research Conference on Oscillations and Dynamic Instabilities in Chemical Systems. 2008, Colby College, Waterville.
• Novakovic K, Willis MJ, Wright AR. Utilising high throughput technologies for the determination of the reaction network of the ʟ-proline catalysed aldol reaction. Clean Technologies and Environmental Policy 2008, 10(2), 155-163.
• Novakovic K, Grosjean C, Scott SK, Whiting A, Willis MJ, Wright AR. Achieving pH and Qr oscillations in a palladium-catalysed phenylacetylene oxidative carbonylation reaction using an automated reactor system. Chemical Physics Letters 2007, 435(1-3), 142-147.
• English PJ, Searson DP, Willis MJ, Wright AR. Automated inference of chemical reaction networks. In: 6th European Congress of Chemical Engineering (ECCE 6). 2007, Copenhagen, Denmark.
• Mukherjee A, Searson DP, Willis MJ. Characterisation of the dynamic behaviour of Briggs-Rauscher reaction in a fed-batch reactor. In: The Annual Meeting of the American Institute of Chemical Engineers (AIChE). 2007, Salt Lake City, Utah.
• Searson DP, Willis MJ, Montague GA. Co-evolution of non-linear PLS model components. Journal of Chemometrics 2007, 21(12), 592-603.
• Mukherjee A, Searson DP, Willis MJ, Wright AR. Control of a chaotic autocatalytic reaction in a continuous stirred tank reactor. In: 6th European Congress of Chemical Engineering (ECCE 6). 2007, Copenhagen, Denmark.
• Burnham SC, Novakovic K, Searson DP, Willis MJ, Wright AR. Deduction of reaction mechanism using data from a robotic workstation. In: National Symposium on Chemical Reaction Engineering (Nascre-2). 2007, Houston, Texas.
• Worth R, Novakovic K, Willis MJ, Wright AR. Engineering Scalability-Extending High Throughput Technologies to Chemical Process Development. In: National Symposium on Chemical Reaction Engineering (Nascre-2) 2007. 2007, Houston, Texas.
• Burnham SC, Novakovic K, Willis MJ, Wright AR. Identifying Chemical Reaction Network Models. In: European Congress of Chemical Engineering (ECCE6). 2007, Copenhagen, Denmark.
• Searson DP, Willis MJ, Horne SJ, Wright AR. Inference of chemical reaction networks using hybrid s-system models. Chemical Product and Process Modeling 2007, 2(1).
• Novakovic K, Willis MJ, Wright AR. Reaction network determination using calibration free analytical data. In: European Congress of Chemical Engineering (ECCE6). 2007, Copenhagen, Denmark.
• Novakovic K, Willis MJ, Wright AR. Towards the elucidation of a chemical reaction network for the palladium-catalysed phenylacetylene oxidative carbonylation reaction. In: European Congress of Chemical Engineering (ECCE6). 2007, Copenhagen, Denmark.
• Mukherjee A, Scott SK, Searson DP, Willis MJ, Wright AR. Control of a chaotic autocatalytic reaction system. In: European Conference on Complex Systems (ECCS '06). 2006, Said Business School, Oxford, UK.
• Novakovic K, Grosjean C, Schutz T, Willis MJ, Wright A, Whiting A. Enhancing process development using high throughput technologies a case study using an L-proline catalysed aldol reaction. In: 17th International Congress of Chemical and Process Engineering (CHISA). 2006, Prague, Czech Republic: CSCHI.
• Novakovic K, Willis MJ, Wright AR. High throughput technologies and reaction network determination. In: Molecular Engineering Industrial Advisory Board. 2006, Gateshead, UK.
• Searson DP, Burnham SC, Willis MJ, Wright AR. Identification of chemical reaction mechanism from batch process data. In: Proceedings of the 17th IASTED International Conference on Modelling and Simulation. 2006, Montreal, Quebec, Canada: ACTA Press.
• Horne SJ, Searson DP, Willis MJ, Wright AR. Modelling of chemical processes using S-systems. In: 11th APCChe Congress. 2006, Kuala Lumpur, Malaysia.
• Searson, D. P., Willis, M. J., Home, S., Wright, A. R. S-systems and evolutionary algorithms for the inference of chemical reaction networks from fed-batch reactor experiments. In: CHISA 2006: 17th International Congress of Chemical and Process Engineering. 2006, Prague, Czech Republic: Czech Society of Chemical Engineering.
• Burnham, S. C., Searson, D. P., Willis, M. J., Wright, A. R. Towards the automated deduction of chemical reaction mechanism. In: CHISA 2006: 17th International Congress of Chemical and Process Engineering. 2006, Prague, Czech Republic: Czech Society of Chemical Engineering.
• Burnham SC, Searson DP, Willis MJ, Wright AR. Towards the automated elucidation of chemical reaction mechanism from batch reactor experiments. In: AIChe Process Development Symposium. 2006, Palm Springs, USA.
• Wright AR, Willis MJ. The effect of reaction kinetics on the performance of reactive distillation. In: Kinetics in Action. 2004, Leeds, UK.
• Hinchliffe M, Montague G, Willis M, Burke A. Correlating polymer resin and end-use properties to molecular-weight distribution. AIChE Journal 2003, 49(10), 2609-2618.
• Hinchliffe MP, Willis MJ. Dynamic systems modelling using genetic programming. Computers and Chemical Engineering 2003, 27(12), 1841-1854.
• Hinchliffe M, Montague G, Willis M, Burke A. Hybrid Approach to Modeling an Industrial Polyethylene Process. AIChE Journal 2003, 49(12), 3127-3137.
• Lau S, Willis MJ, Montague GA, Glassey J. Predictive scheduling of a bioprocess plant. In: Proceedings of the IASTED International Conference on Modelling, Simulation and Optimatization. 2003, Banff, Alberta, Canada: IASTED.
• Montague GA, Glassey J, Willis MJ, Smith R, Wiggins G, Key A. Advanced control methods for French fry quality improvement. Computing & Control Engineering Journal 2002, 13(1), 26-32.
• Lennox B, Kipling K, Glassey J, Montague G, Willis M, Hiden H. Automated production support for the bioprocess industry. Biotechnology Progress 2002, 18(2), 269-275.
• Tham MT, Montague GA, Glassey J, Willis MJ. Practical inferential estimation using artificial neural networks. Measurement and Control 2002, 35(1), 5-9.
• Luangpaiboon P, Metcalfe AV, Rowlands RJ, Tham MT, Willis MJ. Comparison of Methods for Optimising a Chemical Process. In: Conf. Statistics in Action 2000. 2000, Uni. Newcastle.
• McKay B, Willis M, Searson D, Montague G. Nonlinear continuum regression: an evolutionary approach. Transactions of the Institute of Measurement and Control 2000, 22(2), 125-140.
• Tham MT, Brodie KA, Willis MJ. A robust tuning procedure for adaptive inferential control. International Journal of Adaptive Control and Signal Processing 1999, 13(2), 85-103.
• Brodie KA, Tham MT, Willis MJ. A robust tuning procedure for adaptive inferential control. International Journal of Adaptive Control and Signal Processing 1999, 13(2), 85-103.
• McKay B, Willis MJ, Searson DP, Montague GA. Non-linear continuum regression using genetic programming. In: 1st Genetic and Evolutionary Computation Conference (GECCO). 1999, Orlando, Florida: Morgan Kaufmann.
• Hiden HG, Willis MJ, Tham MT, Montague GA. Non-linear principal components analysis using genetic programming. Computers and Chemical Engineering 1999, 23(3), 413-425.
• Searson DP, Montague GA, Willis MJ. Chemical process controller design using genetic programming. In: 3rd Annual Conference on Genetic Programming. 1998, Madison, Wisconsin: Morgan Kaufmann.
• Searson DP, Montague GA, Willis MJ. Evolutionary design of process controllers. In: UKACC International Conference on Control. 1998, Swansea, UK: IEE Conference Publications.
• Willis MJ, BRYDON D, CILLIERS J J. Classifying pilot-plant distillation column faults using neural networks. Control Engineering Practice, 5(10), 1373-1384 1997.
• Willis MJ, McKAY B, BARTON G . Steady-state modelling of chemical process systems using genetic programming. Computers and Chemical Engineering, 21, 981-996 1997.
• Tham MT, MITCHELL A, WILLIS M J, BITAR S S. Inferential estimation of viscosity index on a lubricant production plant. Control Engineering Practice, 4(12), 1659-1667 1996.
• Adamson R, Hobbs M, Silcock A, Willis MJ. Steady-state optimisation of a multiple cryogenic air separation unit and compressor plant. Applied Energy 2017, 189, 221-232.
• von Stosch M, Willis M. Intensified design of experiments for upstream bioreactors. Engineering in Life Sciences 2017, 17(11), 1173-1184.
• Grisales Diaz VH, Willis M. Kinetic modelling and simulation of batch, continuous and cell-recycling fermentations for acetone-butanol-ethanol production using Clostridium saccharoperbutylacetonicum N1-4. Biochemical Engineering Journal 2018, 137, 30-39.
• Grisales Diaz VH, Prado-Rubio OA, Willis MJ, von Stosch M. Dynamic hybrid model for ultrafiltration membrane processes. In: 27th European Symposium on Computer Aided Process Engineering. 2017, Barcelona, Spain: Elsevier.
• von Stosch M, Zhang J, Willis M. Hybrid neural network modelling for process monitoring and control. In: Artificial Neural Networks in Chemical Engineering. New York: Nova Science Publishers, Inc, 2017, pp.205-228.
• Adamson R, Hobbs M, Silcock A, Willis MJ. Integrated real-time production scheduling of a multiple cryogenic air separation unit and compressor plant. Computers and Chemical Engineering 2017, 104, 25-37.
• Willis MJ, von-Stosch M. L0-constrained regression using mixed integer linear programming. Chemometrics and intelligent laboratory systems 2017, 165, 29-37.
• Cummings T, Adamson R, Sugden A, Willis MJ. Retrospective and predictive optimal scheduling of nitrogen liquefier units and the effect of renewable generation. Applied Energy 2017, 208, 158-170.
• Willis MJ, von Stosch M. Simultaneous parameter identification and discrimination of the nonparametric structure of hybrid semi-parametric models. Computers and Chemical Engineering 2017, 104, 366-376.