Summary

A summary of my work and experience is contained in the recording of my invited talk to the London Mathematical Society in March 2021

Dr Shirley Coleman | LMS Women in Mathematics Day 2021 - YouTube

Background

https://blogs.ncl.ac.uk/shirleycoleman/

Areas of expertise

Applied Statistics specialising in business, industry and data analytics in SMEs. My invited talk to the Australian Statistical Society in March 2019 includes examples of my work.

https://vimeo.com/ssavic/20190319-coleman

Impact case study

http://impact.ref.ac.uk/CaseStudies/CaseStudy.aspx?Id=21204

Roles and Responsibilities

Technical Director of NU Solve, previously Industrial Statistics Research Unit
Visiting Professor, University of Ljubljana, 2009-2020

Professional

Council member of European Network of Business and Industrial Statistics, Fellow of IMA, Elected member of ISI,     Chartered Statistician, Chair of Royal Statistical Society Quality Improvement Section. Honorary Officer on RSS Council for Discussion Meetings.

QIS Video

Qualifications

PhD "Statistics, computer graphics and morphometry in 3-dimensional reconstruction of serial sections of glomeruli" , Newcastle 1986

MSc Statistics, Newcastle 1981
BSc Mathematical Sciences (1st class), Newcastle 1975

Previous Positions

Associate Professor Wroclaw University of Technology, Poland, 2003
Statistics Lecturer Hong Kong University
Senior Quantitative Analyst, Baring Securities Hong Kong
Senior Engineer, British Gas

Languages

French, Cantonese

Research Interests

Statistical modelling, problem solving, data presentation, business statistics, communicating statistics

http://blogs.sas.com/content/jmp/2013/05/31/celebrating-statistics-with-professor-shirley-coleman

Other Expertise

Research methods, quantitative methods, data mining, machine learning

Current Work

Knowledge Transfer Partnerships (KTP) with Engie and Royston Marine. Previously with Orchard Software Systems, Rain Data, ADL Smartcare and Enzen Global.

Applications of statistics in business and industry, data mining methods in utilities, investigating patterns in multivariate data, Lean Six Sigma, Statistical Process Control, analysis of Parkinson Disease research.

Future Research

Data science applications in business and industry, data analytics, modelling and prediction

Postgraduate Supervision

Supervisor for MPhil "Statistical and machine learning methods for decision support in social housing" October 2019

Supervisor for MPhil "Mining and monetisation of health and social care interventions" October 2017

Supervisor for PhD "Developing data analytic algorithms to measure vessel performance and control emissions" from December 2014

External examiner for PhD at Lulea, Sweden, "Adapting continuous processes under feedback control", Sept 2019

External examiner for PhD at ENSAM, Paris, "Definition and representation of user experience intentions in the early phase of the industrial design process: a focus on the kansei process", 2014

External examiner for PhD at Leeds University, "Calibrating scales for affective responses to design elements using Rasch Measurement Theory", 2013

Hosting visiting Professor from Hedmark University College, Norway studying "SEM and PLS in survey data", 2016 

External examiner for PhD "Statistical methods in Kansei Engineering studies" at University Politecnica de Catalunya, 2011

Hosting Visiting Fellow from University of Milano Bicocca studying "Sequence analysis", 2011

Hosting Visiting Fellow from University Politecnica de Catalunya studying "Modelling of Utilities data" , 2011

External examiner for PhD "Methods for uncertainty evaluation in measurement" presented by G. Genta, Turin, 2010

Hosting Visiting Fellow from University of Palermo studying Kansei Engineering, 2008

Supervising PhD "On the relationship between governance and economic growth" completed 2005

Esteem Indicators

Visiting professor, Faculty of Economics, University of Ljubljana;
RSS Business and Industry Section, CStat and CSci accreditation; discussion meeting committee; co-chair RSS conference, Newcastle, 2013
ENBIS Council, Chair of UK-ENBIS, Co-chair of Statistics in Practice special interest group, webinar co-ordinator, chair ENBIS conference, Ljubljana, 2012

Reviewer for Wiley, Springer, TQM, IJLSS, J.Wine Research, IJQRM, QTQM and others

Funding

Innovate UK £132K from April 2017 -

2 year KTP project with Orchard Software Systems Limited to develop a data analytical capability to enable the development of software solutions to better predict arrears, repairs, empty properties (voids) and other issues in relation to social housing. 

2 year KTP project with Rain Data Limited to embed a data analytical expertise within Rain Data to improve their service offering to their customers.  This will lead to an enhanced parts recommendation in the automotive after-market leading to an improved service to customers.

Innovate UK £132K from August 2014 -

2 year KTP project with Enzen Global Limited to develop analytical skills applicable to gas flow data to improve the efficiency of gas distribution at minimum cost to the system. 

Innovate UK £132K from October 2014 -

2 year KTP project with ADL Smartcare Limited to exploit existing big data arising from decision making, by appropriate mining, monetisation and marketing and to extend company offering from public to new markets including the private sector.

Innovate UK £132K from December 2014 -
2 year KTP project with Royston Limited to use statistical and data mining techniques to facilitate the further development and enhancement of the 'Enginei' monitoring system.

Predicting Cognitive Profiles in Parkinson’s Disease: A Multimodal Approach. Michael J Fox Foundation: 1st Nov 2011-31st Oct 2013 (£80,707) (Lead Applicant: Burn DJ, with Rochester L, Baker M, Coleman S). Predicting Dementia in Parkinson’s disease: A genotypic and phenotypic study (ICICLE-PD). Parkinson’s Disease Society REF J0802, UK: June 2009 – May 2014, (£1,184,209) (Burn DJ, Barker RA, Brooks DJ, O’Brien JT, McKeith IG, Chinnery PF, Owen AM, Brayne CEG, Robbins T, Sawcer S, Coleman S).

£30,000 statistical support for utilities planning, 2011

£85,000 data mining support for National Grid 2009
£99,044 KTP September 2006

External examiner - University of Plymouth

MSc Data Science and Business Analytics

Postgraduate Teaching

NBS8268 Quantitative Methods for Business Research for MSc in Advanced International Business Management

NBS8269 Research Methods (Dual Award) for MSc in Advanced International Business Management and Marketing

• Coleman SY. Big data in and for small business: data excellence in SMEs through engagement in university partnerships. In: Adam Lindgreen, Thomas Ritter, Carsten Lund Pedersen, and Torsten Ringberg, ed. Big Data in Small Business: Data-driven Growth in Small and Medium-sized Enterprises. Cheltenham, UK: Edward Elgar, 2021, pp.129-145.
• Walker D, Ruane M, Bacardit J, Coleman S. Insight from data analytics in a facilities management company. Quality and Reliability Engineering International 2021, Epub ahead of print.
• Moat G, Coleman S. Survival Analysis and Predictive Maintenance Models for non-sensored Assets in Facilities Management. In: IEEE International Conference on Big Data (Big Data). 2022, Orlando, Florida, USA: IEEE.
• Vicario G, Coleman S. A Review of Data Science in Business and Industry and a Future View. Applied Stochastic Models in Business and Industry 2020, 36(1), 6-18, 43-48.
• Coulson E, Coleman S, Papagiannidis S, Yannopoulou N. Design of Experiments for Business Improvement in SME Marketing Strategies. In: European Network of Business and Industrial Statistics (ENBIS-20). 2020, Online: ENBIS.
• Coleman SY. Discussion of “Experiences with big data: Accounts from a data scientist’s perspective”. Quality Engineering 2020, 32(4), 558-559.
• Coleman SY, Ahlemeyer-stubbe A. Monetizing Industry 4.0 and IoT Data for Marketing and Sales. In: Kenett,RS, ed. Wiley Statsref: Statistics Reference Online. Online: John Wiley & Sons, Ltd, 2020.
• Coleman SY, Ahlemeyer-Stubbe A. Monetizing Industry 4.0 and IoT data for Marketing and Sales - Data Collected from Connected Cars. In: Wiley Statsref: Statistics Reference Online. John Wiley & Sons, Ltd, 2020.
• Coleman SY, Ahlemeyer-Stubbe A. Monetizing Industry 4.0 and IoT data for Marketing and Sales - Data Collected from Processes in Smart Factories. In: Wiley Statsref: Statistics Reference Online. John Wiley & Sons, Ltd, 2020.
• Coleman SY, Ahlemeyer-Stubbe A. Monetizing Industry 4.0 and IoT data for Marketing and Sales - Data Collected from Smart Homes and Wearables. In: Wiley Statsref: Statistics Reference Online. John Wiley & Sons, Ltd, 2020.
• Vicario G, Coleman S. Rejoinder to the discussion of “A review of data science in business and industry and a future view by G. Vicario and S. Coleman”. Applied Stochastic Models in Business and Industry 2020, 36(1), 43-48.
• Coulson E, Papagiannidis S, Coleman S, Yannopoulou N. An Exploration into the Effects of Digital Co-branding within B2B E-Commerce: An Action Research Case Study within the B2B Marine Engineering Industry. In: 19th International Conference on Electronic Business (ICEB 2019). 2019, Newcastle upon Tyne: Association of Information Systems.
• Coulson E, Coleman S, Yannopoulou N, Papagiannidis S. Business insight and support from analysis of digital marketing data in an SME. In: European Network for Business and Industrial Statistics (ENBIS-19). 2019, Budapest, Hungary: ENBIS.
• Coleman SY. Data Science in Industry 4.0. In: Faragó, I; Izsák, F; Simon, P, ed. Progress in Industrial Mathematics at ECMI 2018. Mathematics in Industry. Switzerland: Springer Nature, 2019, pp.559-566.
• Smith WS, Coleman S, Bacardit J, Coxon S. Insight from data analytics with an automotive aftermarket SME. Quality and Reliability Engineering International 2019, 35(5), 1396-1407.
• Capezza C, Coleman SY, Lepore A, Palumbo B, Vitiello L. Ship fuel consumption monitoring and fault detection via partial least squares and control charts of navigation data. Transportation Research Part D: Transport and Environment 2019, 67, 375-387.
• Yabsley W, Coleman SY. Using data analytics for business decisions in the UK energy sector: a case study integrating gas demand with weather data. International Journal of Oil, Gas and Coal Technology 2019, 21(1), 109-129.
• Coleman S. Analysing activities in a classroom – Remembrances of John Aitchison in Hong Kong with applications to a Service Provider. Austrian Journal of Statistics 2018, 47(5), 47-52.
• Smith W, Coleman S, Bacardit J, Coxon S. How data can change the automotive aftermarket. Focus 2018, (October), 30-32.
• Herron C, Coleman SY. How to determine the number of rapid chargers for a given volume of electric vehicles. Focus 2018, (June), 48-49.
• Ahlemeyer-Stubbe A, Coleman SY. Monetising Data: How to Uplift Your Business. John Wiley and Sons Ltd, 2018.
• Pritchett R, Coleman S, Campbell J, Pabary S. Understanding our patient base: An introduction to data analytics in dental practice. Dental Update 2018, 45(3), 236-246.
• Zaman I, Pazouki K, Norman R, Younessi S, Coleman S. Challenges and Opportunities of Big Data Analytics for Upcoming Regulations and Future Transformation of the Shipping Industry. Procedia Engineering 2017, 194, 537-544.
• Morris R, Lord S, Lawson RA, Coleman S, Galna B, Duncan GW, Khoo TK, Yarnall AJ, Burn DJ, Rochester L. Gait Rather Than Cognition Predicts Decline in Specific Cognitive Domains in Early Parkinson’s Disease. Journal of Gerontology: Series A 2017, 72(12), 1656-1662.
• Lord S, Galna B, Yarnall AJ, Coleman S, Burn D, Rochester L. Have we been overestimating fall rates in Parkinson's disease?. Movement Disorders 2017, 32(5), 803-804.
• Lord S, Galna B, Yarnall AJ, Morris R, Coleman S, Burn D, Rochester L. Natural history of falls in an incident cohort of Parkinson’s disease: early evolution, risk and protective features. Journal of Neurology 2017, 264(11), 2268-2276.
• Coleman SY, Kenett RS. The Information Quality Framework for Evaluating Data Science Programs. In: Encyclopedia with semantic computing and robotic intelligence. World Scientific Publishing Company, 2017, pp.1730001.
• Yarnall AJ, Lashley T, Ling H, Lees AJ, Coleman SY, O'Sullivan SS, Compta Y, Revesz T, Burn DJ. Apomorphine: A potential modifier of amyloid deposition in Parkinson's disease?. Movement Disorders 2016, 31(5), 668-675.
• Coleman S. Data mining Opportunities for Small and Medium Enterprises with Official Statistics in the UK. Journal of Official Statistics 2016, 32(4), 849-865.
• Coleman SY, Gob R, Manco G, Pievatoli A, Tort-Martorell X, Reis MS. How can SMEs benefit from big data? Challenges and a path forward. Quality and Reliability Engineering International 2016, 32(6), 2151-2164.
• Lord S, Galna B, Yarnall AY, Coleman S, Burn D, Rochester L. Predicting first fall in newly diagnosed Parkinson's disease: Insights from a fall-naïve cohort. Movement Disorders 2016, 31(12), 1829-1836.
• Del Din S, Godfrey A, Coleman S, Galna B, Lord S, Rochester L. Time-dependent changes in postural control in early Parkinson's disease: what are we missing?. Medical & Biological Engineering & Computing 2016, 54(2), 401-410.
• Zaman I, Pazouki K, Norman RA, Younessi S, Coleman S. Utilising real-time ship data to save fuel consumption and reduce carbon emission. In: Shipping in Changing Climates Conference. 2016, Newcastle upon Tyne, UK.
• Zaman IM, Pazouki K, Coleman S, Norman RA, Younessi S. Performance Monitoring and Automatic Operating Mode Detection Based on the Statistical Analysis of Ship Data. In: International Conference on Energy Efficient Ships. 2015, Rotterdam, The Netherlands: Royal Institution of Naval Architects.
• Ahlemeyer-Stubbe A, Coleman S. A Practical Guide to Data Mining for Business and Industry. London: Wiley, 2014.
• Yarnall AJ, Breen DP, Duncan GW, Khoo TK, Coleman SY, Firbank MJ, Nombela C, Winder-Rhodes S, Evans JR, Rowe JB, Mollenhauer B, Kruse N, Hudson G, Chinnery PF, O'Brien JT, Robbins TW, Wesnes K, Brooks DJ, Barker RA, Burn DJ, ICICLE-PD Study Group. Characterizing mild cognitive impairment in incident Parkinson disease The ICICLE-PD Study. Neurology 2014, 82(4), 308-316.
• Lord S, Galna B, Coleman S, Yarnall A, Burn D, Rochester L. Cognition and gait show a selective pattern of association dominated by phenotype in incident Parkinson's disease. Frontiers in Aging Neuroscience 2014, 6, 249.
• Duncan GW, Khoo TK, Yarnall AJ, O'Brien JT, Coleman SY, Brooks DJ, Barker RA, Burn DJ. Health-related quality of life in early Parkinson's disease: The impact of nonmotor symptoms. Movement Disorders 2014, 29(2), 195-202.
• McCollin C, Coleman SY. Historical Published Maintenance Data: What Can It Tell Us About Reliability Modelling?. Quality and Reliability Engineering International 2014, 30(3), 381-395.
• Duncan GW, Khoo TK, Coleman SY, Brayne CE, Yarnall AJ, O'Brien JT, Barker RA, Burn DJ. The Incidence of Parkinson's Disease in the North East of England. Age and Ageing 2014, 43(2), 257-263.
• Lord S, Galna B, Verghese J, Coleman S, Burn D, Rochester L. Independent Domains of Gait in Older Adults and Associated Motor and Nonmotor Attributes: Validation of a Factor Analysis Approach. Journals of Gerontology Series A: Biological Sciences & Medical Sciences 2013, 68(7), 820-827.
• Lord S, Galna B, Coleman S, Burn D, Rochester L. Mild Depressive Symptoms Are Associated with Gait Impairment in Early Parkinson's Disease. Movement Disorders 2013, 28(5), 634-639.
• Coleman SY. Statistical thinking in the quality movement +/-25 years. The TQM Journal 2013, 26(6), 597-605.
• Khoo TK, Yarnall AJ, Duncan GW, Coleman S, O'Brien JT, Brooks DJ, Barker RA, Burn DJ. The spectrum of nonmotor symptoms in early Parkinson disease. Neurology 2013, 80(3), 276-281.
• Nwabineli NJ, Mittal S, Russell M, Coleman S. Long-term results of urinary stress incontinence treated with mid-urethral tape as a standalone operation or in combination with pelvic floor reconstruction. Journal of Obstetrics and Gynaecology 2012, 32(8), 773-777.
• Coleman SY. Six sigma in health care. In: Faltin, F; Kenett, R; Ruggeri, F, ed. Statistical methods in healthcare. Wiley-Blackwell Publishing Ltd, 2012. In Press.
• Monness E, Coleman SY. A short note on Variograms and Correlograms. Norway: Hedmark University College, 2011.
• Antony J, Coleman S, Montgomery D, Anderson M, Silvestrini R. Design of Experiments for Non-Manufacturing Processes: Benefits, Challenges and Some Examples. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture 2011, 225(11), 2078-2087.
• Coleman SY. Never mind the quality. Public Sector Executive 2009, 8(1), 33.
• Coleman SY. Six Sigma: an opportunity for statistics and for statisticians. Significance 2008, 5(2), 94-96.
• Coleman SY, Greenfield T, Stewardson DS, Montgomery D, ed. Statistical Practice in Business and Industry. Chichester: Wiley, 2008.
• Coleman SY. Kaizen. In: Kenett, R; Ruggeri, F; Faltin, F, ed. Encyclopaedia of Statistics in Quality and Reliability. Oxford, UK: Wiley, 2007, pp.887-890.
• Yi G, Coleman SY, Ren Q. CUSUM Method in predicting regime shifts and its performance in different stock markets. Journal of Applied Statistics 2006, 33(7), 647-661.
• Monness E, Coleman SY. LISREL: An alternative to MANOVA and Principal Components in designed experiments when the response is multidimensional. Quality and Reliability Engineering International 2006, 22(2), 213-224.
• Coleman S, Douglas A. Where next for ISO 9000 companies?. TQM Magazine 2003, 15(2), 88-92.
• Stewardson DJ, Hicks C, Pongcharoen P, Coleman SY, Braiden PM. Overcoming complexity via statistical thinking: optimising genetic algorithms for use in complex scheduling problems via designed experiments. In: Tackling Industrial Complexity: The Ideas That Make a Difference. 2002, Cambridge, UK: University of Cambridge.
• Linsley MJ, Pearce KF, Stewardson DJ, Coleman SY. The Introduction of Quality Tools to Reduce Product Reject Rates in an SME. In: Manufacturing Information Systems: Proceedings of the Fifth SMESME International Conference - Stimulating Manufacturing Excellence in Small and Medium Enterprises. 2002, Danbury, UK: Earlybrave Publications Ltd.
• Bruce D, Coleman SY. Improving communication via quantitative management. Journal of Applied Statistics 2001, 28(3-4), 335-341.
• Chambers PRG, Piggott JL, Coleman SY. SPC - a team effort for process improvement across four Area Control Centres. Journal of Applied Statistics 2001, 28(3-4), 307-324.
• Coleman SY, Gordon A, Chambers PR. SPC - making it work for the gas transportation business. Journal of Applied Statistics 2001, 28(3-4), 343-351.
• Coleman SY, Arunakumar G, Foldvary F, Feltham R. SPC as a tool for creating a successful business measurement framework. Journal of Applied Statistics 2001, 28(3-4), 325-334.
• Stewardson D, Coleman S. Using the Summed Rank Cusum for monitoring environmental data from industrial processes. Journal of Applied Statistics 2001, 28(3-4), 469-484.
• TOOLAN PG, COLEMAN SY. MUSIC-THERAPY, A DESCRIPTION OF PROCESS - ENGAGEMENT AND AVOIDANCE IN 5 PEOPLE WITH LEARNING-DISABILITIES. JOURNAL OF INTELLECTUAL DISABILITY RESEARCH 1994, 38, 433-444.
• COLEMAN SY, SHIEL RS, EVANS DA. THE EFFECTS OF WEATHER AND NUTRITION ON THE YIELD OF HAY FROM PALACE LEAS MEADOW HAY PLOTS, AT COCKLE PARK EXPERIMENTAL FARM, OVER THE PERIOD FROM 1897 TO 1980. GRASS AND FORAGE SCIENCE 1987, 42(4), 353-358.
• COLEMAN SY, COX TF. THE PROBABILITY OF HITTING A SYNAPSE - AN ADDENDUM. APPLIED STATISTICS-JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES C 1987, 36(1), 92-93.
• MORLEY AR, COLEMAN SY, APPLETON DR, BARNES WSF. 3-DIMENSIONAL RECONSTRUCTION AND SIMULATED RESECTIONING OF CRESCENTIC RENAL CORPUSCLES FROM SERIAL SECTIONS USING COMPUTER-GRAPHICS. In: JOURNAL OF PATHOLOGY. 1985.