Ed Cohen is a lecturer in the Statistics Section of the Department of Mathematics. His research interests lie broadly in the areas of statistical signal and image processing with focus on: multivariate time series, multivariate point processes, wavelet analysis of time series, wavelet analysis of point processes, complex valued time series and nonstationarity.
Motivated by applications in the natural sciences his recent work focuses on applications in fluorescence microscopy with ongoing collaboration including the Ward-Ober lab at Texas A&M, the Experimental Biophysics & Nanotechnology group at King's College London and the Quantitative and Nanobiophysics Lab at UCL.
Ed currently teaches M345S08 Time Series, and has previously taught M34S7 Statistical Pattern Recognition, M5MS07 Nonparametric Smoothing and Wavelets and M5MS08 Multivariate Analysis
et al., 2019, Resolution limit of image analysis algorithms, Nature Communications, Vol:10, ISSN:2041-1723
et al., A hidden Markov model approach to characterizing the photo-switching behavior of fluorophores, Annals of Applied Statistics, ISSN:1932-6157
et al., 2017, 3D Bayesian cluster analysis of super-resolution data reveals LAT recruitment to the T cell synapse, Scientific Reports, Vol:7, ISSN:2045-2322
Cohen EAK, Ober RJ, 2013, Analysis of point based image registration errors with applications in single molecule microscopy, IEEE Transactions on Signal Processing, Vol:61, ISSN:1053-587X, Pages:6291-6306
Cohen EAK, Walden AT, 2010, A Statistical Study of Temporally Smoothed Wavelet Coherence, IEEE Transactions on Signal Processing, Vol:58, ISSN:1053-587X, Pages:2964-2973