Imperial College London

Professor Nick Heard

Faculty of Natural SciencesDepartment of Mathematics

Chair in Statistics
 
 
 
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Contact

 

+44 (0)20 7594 1490n.heard Website

 
 
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Location

 

543Huxley BuildingSouth Kensington Campus

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Summary

 

Summary

Nick Heard is Chair 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.

Prof Nick Heard's personal web page can be found at http://stats.ma.ic.ac.uk/~naheard

Selected Publications

Journal Articles

Hallgren KL, Heard NA, Turcotte MJM, 2023, Changepoint detection on a graph of time series, Bayesian Analysis, Vol:-, ISSN:1936-0975, Pages:1-28

Sanna Passino F, Heard N, 2022, Latent structure blockmodels for Bayesian spectral graph clustering, Statistics and Computing, Vol:32, ISSN:0960-3174

Sanna Passino F, Heard NA, Rubin-Delanchy P, 2021, Spectral clustering on spherical coordinates under the degree-corrected stochastic blockmodel, Technometrics, Vol:64, ISSN:0040-1706, Pages:346-357

Heard NA, 2021, Standardized partial sums and products of p-values, Journal of Computational and Graphical Statistics, Vol:31, ISSN:1061-8600, Pages:563-573

Sanna Passino F, Turcotte MJM, Heard NA, 2021, Graph link prediction in computer networks using Poisson matrix factorisation, Annals of Applied Statistics, Vol:16, ISSN:1932-6157, Pages:1313-1332

Sanna Passino F, Heard N, 2020, Bayesian estimation of the latent dimension and communities in stochastic blockmodels, Statistics and Computing, Vol:30, ISSN:0960-3174, Pages:1291-1307

Price-Williams M, Heard N, 2020, Nonparametric self-exciting models for computer network traffic, Statistics and Computing, Vol:30, ISSN:0960-3174, Pages:209-220

Metelli S, Heard N, 2019, On Bayesian new edge prediction and anomaly detection in computer networks, Annals of Applied Statistics, Vol:13, ISSN:1932-6157, Pages:2586-2610

Bolton A, Heard N, 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

Heard N, Rubin-Delanchy P, 2018, Choosing between methods of combining p-values, Biometrika, Vol:105, ISSN:0006-3444, Pages:239-246

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

Books

Heard N, 2021, An Introduction to Bayesian Inference, Methods and Computation, Springer, ISBN:9783030828073

More Publications