Summary
Ed Cohen is a Reader (Associate Professor) in Statistics in the Department of Mathematics. His research interests lie broadly in statistical methodology for analysing signals and images. Particular areas of focus include: multivariate event and count processes, network processes, change point detection and online estimation. He also develops methodology for the quantitative analysis of biological imaging data with interests including spatial statistics and clustering.
Motivated by applications in engineering and the natural sciences, his collaborators include a diverse set of academic and industry collaborators, from the life sciences to cyber security.
Ed is an investigator and a project lead on the EPSRC Network Stochastic Processes and Time Series (NeST) Programme, and Joint Director of the EPSRC Centre for Doctoral Training in Statistics and Machine Learning (StatML) at Imperial and Oxford. He is an Associate Editor of Statistics and Computing and Biological Imaging, and Vice-Chair of the Emerging Applications Section of the Royal Statistical Society.
Selected Publications
Journal Articles
Ward S, Battey H, Cohen E, 2023, Nonparametric estimation of the intensity function of a spatial point process on a Riemannian manifold, Biometrika, Vol:110, ISSN:0006-3444, Pages:1009-1021
Nieves D, Pike J, Levet F, et al., 2023, A framework for evaluating the performance of SMLM cluster analysis algorithms, Nature Methods, ISSN:1548-7091
Shlomovich L, Cohen E, Adams N, 2022, A parameter estimation method for multivariate binned Hawkes processes, Statistics and Computing, Vol:32, ISSN:0960-3174
Cohen E, Gibberd A, 2022, Wavelet spectra for multivariate point processes, Biometrika, Vol:109, ISSN:0006-3444, Pages:837-851
Shlomovich L, Cohen E, Adams N, et al., 2022, Parameter estimation of binned Hawkes processes, Journal of Computational and Graphical Statistics, Vol:31, ISSN:1061-8600, Pages:990-1000
Patel L, David W, Owen D, et al., 2021, Blinking statistics and molecular counting in direct stochastic reconstruction microscopy (dSTORM), Bioinformatics, Vol:37, ISSN:1367-4803, Pages:2730-2737
Boland MA, Cohen EAK, Flaxman SR, et al., 2021, Improving axial resolution in Structured Illumination Microscopy using deep learning, Royal Society of London. Philosophical Transactions A. Mathematical, Physical and Engineering Sciences, Vol:379, ISSN:1364-503X
Ward S, Cohen E, Adams N, 2021, Testing for complete spatial randomness on three dimensional bounded convex shapes, Spatial Statistics, Vol:41, ISSN:2211-6753
Patel L, Cohen E, Ober R, et al., 2019, A hidden Markov model approach to characterizing the photo-switching behavior of fluorophores, Annals of Applied Statistics, Vol:13, ISSN:1932-6157, Pages:1397-1429
Cohen E, Abraham A, Ramakrishnan S, et al., 2019, Resolution limit of image analysis algorithms, Nature Communications, Vol:10, ISSN:2041-1723