Nick Heard is Reader in Statistics in the Department of Mathematics at Imperial College. His research interests center around computational Bayesian infererence, clustering and changepoint analysis, with a focus on application to large dynamic networks, such as computer networks or social networks, and bioinformatics problems.
Dr Nick Heard's personal web page can be found at http://stats.ma.ic.ac.uk/~naheard
Heard N, Rubin-Delanchy P, 2018, Choosing between methods of combining p-values, Biometrika, Vol:105, ISSN:0006-3444, Pages:239-246
Bolton AD, Heard NA, 2018, Malware Family Discovery Using Reversible Jump MCMC Sampling of Regimes, Journal of the American Statistical Association, Vol:113, ISSN:0162-1459, Pages:1490-1502
, 2018, Meta-Analysis of Mid-p-Values: Some New Results based on the Convex Order, Journal of the American Statistical Association, ISSN:0162-1459
Heard NA, Turcotte MJM, 2017, Adaptive Sequential Monte Carlo for Multiple Changepoint Analysis, Journal of Computational and Graphical Statistics, Vol:26, ISSN:1061-8600, Pages:414-423