Name: Shirley Yvonne COLEMAN
Website: https://www.ncl.ac.uk/maths-physics/people/profile/shirleycoleman.html
Education history
PhD “Statistics, computer graphics and morphometry in 3 dimensional reconstruction of serial sections” from Newcastle University, 1986
MSc Statistics, BSc Mathematics 1st class from Newcastle University, 1980, 1975
Employment history
Technical Director and Principal Statistician (Senior Lecturer/ Associate Professor) in the Industrial Statistics Research Unit (ISRU) in School of Mathematics, Statistics and Physics (MS&P) at Newcastle University. 1990 to present.
Visiting Professor, Faculty of Economics, Ljubljana University, Slovenia, 2008-19
Associate Professor, Wroclaw University of Technology, Poland in Centre for Advanced Manufacturing Technology, 2003, concurrent with ISRU
Lecturer in Hong Kong University Statistics Department, assistant lecturer in Education department and Hong Kong Polytechnic from 1986-1990.
Senior quantitative analyst at Baring Securities (Hong Kong) 1989-1990
Academic supervisor/ lead academic for Innovate UK funded knowledge transfer partnerships (KTP) concerned with statistical analysis of company data and business analytics for improved competitiveness and performance (including 7 KTPs from 2014 to 2021). Academic supervisor for Master’s projects in Maths/Stats/Data Science degrees and set-up advisor to Centre for Doctoral Training in Cloud Computing for Big Data.
Technical Director of NU Solve involved with ongoing engagement with business and industry in MS&P; including predictive analytics, pipeline fault detection and sizing; adaptive DoE, multivariate analysis and modelling in process industries.
Previously principal analyst for EU funded Real Finance survey and Principal investigator in ERDF, ESF and framework FP5 and 6 data science research projects in manufacturing, design and six sigma (quality improvement through statistics).
Academic statistical consultant in Newcastle for over 20 years with major involvement in business and organisations locally, nationally and internationally. External examiner for MSc in Data Science at Plymouth University and associate colleges in Singapore and Malaysia (2018 to present).
Membership of professional bodies
Chartered Statistician since 1993 and Chartered Scientist. Fellow of Royal Statistical Society. Elected member of International Statistics Institute, founder member, past President 2004/5 and current Council member of European Network of Business and Industrial Statistics. Fellow of the Institute of Maths and its Applications
Professional Development
Royal Statistical Society Council 2020 – present and 2005/9. RSS Professional Affairs Committee 2010/12. Professional Development Committee & Statistics User Executive.
2020 Chair RSS Quality Improvement Section, Obituaries Commissioning and Discussion Meetings.
Esteem
Coleman, SY (2014), “Faster fault finding in National Grid” REF 2014 Impact case study rated 3-4*
http://results.ref.ac.uk/Submissions/Impact/1963
Impact case study on big data analytics for SMEs submitted for REF in 2021.
Invited presenter and author of books and academic papers in data science.
PhD Supervision
Wilson, DJ. On the relationship between governance and economic growth. PhD, Newcastle University. Passed 2006.
Member of the PhD evaluation committee for Uroš Kosanović in the University of Ljubljana. “Use of modern machine learning methods for modelling consumer shopping habits in brick and mortar retail stores”. 2021.
Currently co-supervising:
“Digital marketing”. PhD with NUBS. Due 2021
“Big data analytics in shipping”. PhD with School of Engineering. Due 2022.
“Kansei in education”. DEd with Education. Due 2025.
PhD Examining in UK
Camargo, F. Calibrating Scales for Affective Responses to Design Elements Using Rasch Measurement Theory. Leeds University. Passed 2013.
PhD examining international
International evaluator for the PhD thesis of Fabio Centofanti in the University of Naples Federico II. “Statistical Methodologies of Functional Data Analysis for Industrial Applications”. Passed in 2021.
Chair of the decision meeting of the grading committee for the PhD defence of Francesca Capaci, Lulea University of Technology, Sweden. “Adapting Experimental and Monitoring Methods for Continuous Processes under Feedback Control Challenges, Examples, and Tool”. Passed 2019.
External examiner for Alexandre Gentner, ENSAM, Paris. “Emotional design and user experience”. Passed 2014.
External examiner for Lluís Marco Almagro, Universitat Politecnica de Catalunya, Barcelona. “Statistical Methods in Kansei Engineering Studies”. Passed 2011.
External examiner for Gianfranco Genta, Politecnico di Torino, Turin. “Methods for uncertainty evaluation in measurement”. Passed 2010.
MPhil supervision
“Mining and monetising data”. Passed 2017.
“Statistical and machine learning methods for decision support in Social Housing”. Passed 2019.
Publications showcasing data science in SMEs
Walker, D, M.Ruane, J. Bacardit and Coleman, SY (2021). Insight from Data Analytics in a Facilities Management Company. QREI. DOI: 10.1002/qre.2994
Coleman SY (2021). “Data excellence in SMEs through engagement in university partnerships”. Chapter in book: Big Data in Small Business: Data-driven Growth in Small and Medium-sized Enterprises. Eds: Lindgreen,A, Ritter,T, Pedersen,CL, Ringberg,T. Edward Elgar. In press.
Vicario, G and Coleman, S (2020), “A Review of Data Science in Business and Industry and a Future View”, Applied Stochastic Models in Business and Industry, 36(1), pp 6-18, 43-48. https://onlinelibrary.wiley.com/toc/15264025/2020/36/1
Smith, WS, Coleman, S, Bacardit, J, Coxon, S. (2019). Insight from data analytics with an automotive aftermarket SME. Qual Reliab Engng Int.; 35: 1396– 1407. https://doi.org/10.1002/qre.2529
Capezza C, Coleman, SY, Lepore A, Palumbo B, Vitiello L. (2019). “Ship fuel consumption monitoring and fault detection via partial least squares and control charts of navigation data”. Transportation Research Part D: Transport and Environment, 67, 375-387.
Coleman S.Y. (2019). Data Science in Industry 4.0. In: Faragó I., Izsák F., Simon P. (eds) Progress in Industrial Mathematics at ECMI 2018. Mathematics in Industry, vol 30, pp 559-566. Springer Nature Switzerland. https://doi.org/10.1007/978-3-030-27550-1_72
Herron, C and Coleman S (2018), “Making way for ultra-low-emission vehicles”, Focus, June 2018, pp 48-49, www.ciltuk.org.uk.
Ahlemeyer-Stubbe, A and S.Y. Coleman (2018), Monetising data – how to uplift your business, Wiley, London; ISBN: 978-1-119-12513-6
Pritchett, RM, Coleman, SY, Campbell, J and Pabary, S (2018), “Understanding the patient base: an introduction to data analytics in dental practice”. Dental Update, 45, 236-46.
Coleman, S.Y and Kenett, R.S (2017), “The Information Quality Framework for Evaluating Data Science Programs” chapter in Encyclopaedia with Semantic Computing and Robotic Intelligence, 1(1) 1730001 (14 pages) © World Scientific Publishing Company
Coleman, SY (2016), “Data mining Opportunities for Small and Medium Enterprises with Official Statistics in the UK”, Journal of Official Statistics, 32(4), 849-866.
Coleman, SY, Göb, R, Manco, G, Pievatolo, A, Tort-Martorell, X, Reis, M (2016), “How Can SMEs Benefit from Big Data? Challenges and a Path Forward”, Journal of Quality and Reliability Engineering International, http://onlinelibrary.wiley.com/doi/10.1002/qre.2008/full
Ahlemeyer-Stubbe, A and S.Y. Coleman, (2014), A Practical Guide to Data Mining in Business and Industry, Wiley, London.