Professor Bernard Silverman
Emeritus Professor of Statistics
FRS (PhD, ScD Camb) FAcSS
Following academic posts at Bath, Bristol and Oxford, I was full-time Chief Scientific Advisor to the Home Office form 2010 to 2017. I am now freelance, with a number of different roles including research, charity trusteeship, consultancy, and advice to the Government.
My early research was in smoothing methods, density estimation and nonparametric regression as well as in a variety of other areas in theoretical, computational and applied statistics. More recently, I have focused on two main areas. The first is Functional Data Analysis, which encompasses the notion of statistical problems where the data are functions or images rather than the scalars or vectors of conventional statistics. In two books (joint with Jim Ramsay of McGill University) and a number of papers I explored various aspects of this topic, which is not just a collection of problems but is also an overall way of thinking about this area in which we have no more than scratched the surface. The second is the utilisation of possible sparsity in parameter spaces of high dimension. Such parameter spaces occur particularly in wavelet methods in statistics, but the methods developed are of much wider applicability. My work in this area has been mostly in collaboration with Iain Johnstone (Stanford), and includes both theoretical results exploring various aspects of empirical Bayes, and other, approaches to the general adaptivity problem.
My main current research interest is into human trafficking and modern slavery, building on work I did with the Home Office into estimating the scale of modern slavery in the UK.
Selected recent publications
J. O. Ramsay and B. W. Silverman (2005). Functional Data Analysis, Second Edition. New York: Springer.
I. M. Johnstone and B. W. Silverman (2005). Empirical Bayes selection of wavelet thresholds. Annals of Statistics, 33, 1700-1752.
M. Jansen, G. P. Nason and B. W. Silverman (2009). Multiscale methods for data on graphs and irregular multidimensional situations. Journal of the Royal Statistical Society, Series B, 71, 97–125.
G. Claeskens, L. Slaets and B. W. Silverman (2010). A multiresolution approach to time warping achieved by a Bayesian prior-posterior transfer fitting strategy. Journal of the Royal Statistical Society, Series B, 72, 673–694.
K. Bales, O. Hesketh and B. W. Silverman (2015). Modern slavery in the UK: How many victims? Significance, 12.3, 16-21.