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
Fowler A, Heard NA, 2012, On two-way Bayesian agglomerative clustering of gene expression data, Statistical Analysis and Data Mining, Vol:5, ISSN:1932-1864, Pages:463-476
Heard NA, 2011, Iterative Reclassification in Agglomerative Clustering, Journal of Computational and Graphical Statistics, Vol:20, ISSN:1061-8600, Pages:920-936
et al., 2010, BAYESIAN ANOMALY DETECTION METHODS FOR SOCIAL NETWORKS, Annals of Applied Statistics, Vol:4, ISSN:1932-6157, Pages:645-662
et al., 2009, Dissecting the fission yeast regulatory network reveals phase-specific control elements of its cell cycle, BMC Systems Biology, Vol:3, ISSN:1752-0509