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Durham University

Email and Telephone Directory

Staff Profile

Jonathan Cumming, PhD Durham University

Director of SMCU, Assistant Professor, Statistics in the Department of Mathematical Sciences
Telephone: +44 (0) 191 33 43124
Room number: CM306

Contact Jonathan Cumming (email at

Research Groups

Department of Mathematical Sciences

  • Probability & Statistics: Statistics
  • Probability and Statistics

Research Interests

  • Statistics
  • Applied Statistics
  • Uncertainty Analysis
  • Statistical Computation
  • Variable Selection

Selected Publications

Chapter in book

  • Cumming, J. A. & Goldstein, M. (2010). Bayes linear Uncertainty Analysis for Oil Reservoirs Based on Multiscale Computer Experiments. In The Oxford Handbook of Applied Bayesian Analysis. O'Hagan, A. & West, M. Oxford: Oxford University Press. 241-270.

Journal Article

  • Goldie, Stuart J., Bush, Scott, Cumming, Jonathan A. & Coleman, Karl S. (2020). Statistical Approach to Raman Analysis of Graphene-Related Materials: Implications for Quality Control. ACS Applied Nano Materials 3(11): 11229-11239.
  • Vernon, I. R., Jackson, S. E. & Cumming, J. A. (2019). Known Boundary Emulation of Complex Computer Models. SIAM/ASA Journal on Uncertainty Quantification 7(3): 838-876.
  • Cumming, J. A., Wooff, D. A., Whittle, T. & Gringarten, A. C. (2014). Multiwell Deconvolution. SPE Reservoir Evaluation and Engineering 17(04): 457-465.
  • Cumming, J. A. & Goldstein, M. (2009). Small Sample Bayesian Designs for Complex High-Dimensional Models Based on Information Gained Using Fast Approximations. Technometrics 51(4): 377-388.
  • Cumming, J. A. & Wooff, D. A. (2007). Dimension reduction via principal variables. Computational Statistics & Data Analysis 52(1): 550-565.

Conference Paper

  • Cumming, J A, Botsas, T, Jermyn, I H & Gringarten, A C (2020), Assessing the Non-Uniqueness of a Well Test Interpretation Model Using a Bayesian Approach, SPE Virtual Europec 2020. Society of Petroleum Engineers, SPE-200617-MS.
  • Aluko, Lekan, Cumming, Jonathan & Gringarten, Alain (2020), Using Deconvolution to Estimate Unknown Well Production from Scarce Wellhead Pressure Data, SPE Annual Technical Conference and Exhibition. Virtual.
  • Cumming, J A, Jaffrezic, V, Whittle, T & Gringarten, A C (2019), Constrained Least-Squares Multiwell Deconvolution, SPE Western Regional Meeting. San Jose, California, USA, Society of Petroleum Engineers.
  • Jaffrezic, V., Razminia, K., Cumming, J. A. & Gringarten, A. C. (2019), Field Applications of Constrained Multiwell Deconvolution, SPE Europec featured at 81st EAGE Conference and Exhibition. London, UK.
  • Tung, Y, Virues, C, Cumming, J A & Gringarten, A C (2016), Multiwell Deconvolution for Shale Gas, SPE Europec featured at 78th EAGE Conference and Exhibition. Vienna, Austria, SPE.
  • Thornton, E J, Mazloom, J, Gringarten, A C & Cumming, J A (2015), Application of Multiple Well Deconvolution Method in a North Sea Field, EUROPEC 2015. Madrid, Spain, Society of Petroleum Engineers, Madrid.
  • Cumming, J A, Wooff, D A, Whittle, T, Crossman, R J & Gringarten, A C (2013), Assessing the Non-Uniqueness of the Well Test Interpretation Model Using Deconvolution, 75th EAGE Annual Conference & Exhibition, 10–13 June 2013. London, United Kingdom, Society of Petroleum Engineers, London, 1-24.
  • Cumming, J A, Wooff, D A, Whittle, T & Gringarten, A C (2013), Multiple Well Deconvolution, 2013 SPE Annual Technical Conference & Exhibition. New Orleans, USA, Society of Petroleum Engineers, New Orleans LA.

Doctoral Thesis

  • Cumming, J A (2006). Clinical Decision Support. Department of Mathematical Sciences. Durham University. PhD.


  • Cumming, J. A., Riseth, A. & Williams, J. (2016). Understanding the accuracy of pre-symptomatic diagnosis of sepsis. Department of Mathematical Sciences. Durham, European Study Group in Industry 116 (ESGI 116).

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