Statistical Science


Professor Valerie Isham

PositionEmeritus Professor of Probability and Statistics
ThemesStochastic Modelling and Time Series,  Biostatistics

* @ucl.ac.uk

Biographical Details

Valerie Isham…

Valerie has a PhD in Statistics from the University of London (Imperial College) for a thesis on multidimensional point processes. She joined UCL in 1978 and has been a professor since 1992, becoming an Emeritus Professor in 2018 . She was Head of Department from 1996-2002 and again from 2010-2011, and was President of the Royal Statistical Society in 2011 and 2012. Currently she chairs the Scientific Steering Committee of the Isaac Newton Institute for Mathematical Sciences in Cambridge, and the Biometrika Board of Trustees. She is a member of Council of the Bernoulli Society and is the London and New Zealand Mathematics Societies Forder Lecturer for 2018.

Research Interests

Applied probability: broadly, the development and application of stochastic models, including i) the generic development of models for point processes and determination of their properties; ii) development of models for spatial and spatio-temporal processes arising in the physical sciences, and especially in hydrology (eg soil moisture and precipitation); iii) models for applications in the life and medical sciences, focussing particularly on population processes, epidemics and the transmission dynamics of infection and information; iv) models for random networks and for the dynamics of processes evolving on them.

Selected publications

  • Buckingham-Jeffery, E., Isham, V. and House, T. (2018) Gaussian process approximations for fast inference from infectious disease data. Maths Biosciences 301, 111-120 [https://doi.org/10.1016/j.mbs.2018.02.003, open access].
  • Bottomley, C., Isham, V., Vivas-Martinez, S., Kuesel, A.C., Attah,S.K., Opoku, N.O., Lustigman, S., Walker, M. and Basáñez, M-G. (2016) Modelling Neglected Tropical Diseases diagnostics: the sensitivity of skin snips for Onchocerca volvulus in near elimination and surveillance settings. Parasites and Vectors, 9:343 [https://doi.org/10.1186/s13071-016-1605-3].
  • Heesterbeek, H., Anderson, R.M., Andreasen, V., Bansal, S., De Angelis, D., Dye, C., Eames, K.T.D., Edmunds, W.J., Frost, S.D.W., Funk, S., Hollingsworth, T.D., House, T., Isham, V., Klepac, P., Lessler, J., Lloyd-Smith, J.O., Metcalf, C.J.E., Mollison, D., Pellis, L., Pulliam, J.R.C., Roberts, M.G., Viboud, C. and Isaac Newton Institute IDD Collaboration (2015) Modeling infectious disease dynamics in the complex landscape of global health. Science 347 no. 6227 [https://doi.org/10.1126/science.aaa4339].
  • Kaczmarska, J., Isham, V. and Northrop, P.J. (2015) Local Generalised Method of Moments: An application to point process-based rainfall models. Environmetrics, 26, 312–325 [https://doi.org/10.1002/env.2338].
  • Kaczmarska, J., Isham, V. and Onof, C.J. (2014) Point Process Models for fine-resolution rainfall. Hydrological Sciences Journal 59, 1972-1991. 
  • Ball, F., Britton, T., House, T., Isham, V., Mollison, D., Pellis, L. and Scalia-Tomba, G. (2014) Seven challenges for metapopulation models of epidemics, including household models. Epidemics 10, 63–67.
  • Pellis, L., Ball, F., Bansal, S., Eames, K., House, T., Isham, V. and Trapman, P. (2014) Eight challenges for network epidemic models. Epidemics 10, 58–62.
  • Riley, S., Eames, K., Isham, V., Mollison, D. and Trapman, P. (2014) Five challenges for spatial epidemic models. Epidemics 10, 68–71.
  • Hollingsworth, D., Pulliam, J., Funk, S., Truscott, J., Isham, V. and Lloyd, A. (2014) Seven challenges for modelling indirect transmission: vector-borne diseases, macroparasites and neglected tropical diseases. Epidemics 10, 16–20.