Dr James Nelson
+44 (0)20 7679 1875
|Themes||Stochastic Modelling and Time Series|
James Nelson joined the Department of Statistical Science as a lecturer in 2010. After a
PhD in applied harmonic analysis from the Mathematics Department at Anglia
Polytechnic University (1998-2001), he held post-doc positions in: the Applied
Mathematics and Computing Group at the University of Cranfield (2001-2004); the
Information: Signals, Images, and Systems Research Group at the University of
Southampton (2004-2006); and the Signal Processing and Communications Laboratory at
the University of Cambridge (2006-2010).
Wavelet analysis, random fields, and machine learning for statistical signal and image processing. In particular: wavelet/Riesz basis construction and sparsity with applications to detection and classification; Markov random fields; weak self-similar random fields; multiresolution analysis for machine learning, support vector machine kernel construction and hyper-parameter estimation for pattern recognition; generalised sampling theory; Hurst index estimation for texture and volatility models.
Applications: defence, life sciences, crime & security, and computational finance.
- statistical image analysis for mammography
- anomaly detection and semi-supervised learning methods for underwater acoustics
- Diego Tomassi (sparse regularisation & random fields)
- James Le Roux (sparsity and multiresolution analysis for volatility analysis and high frequency financial computing; with Prof. Sofia Olhede)
- Alex Gibberd (statistical signal processing and machine learning for network traffic anomaly detection)
- Nabanita Basu (computer vision and machine learning for blood spatter analysis; 1st supervisor Dr. Ruth Morgan, Department of Security and Crime Science)
- Christian Niedworok (automated cell detection algorithms in 2-photon microscopy of whole brain images; 1st supervisor Prof. Troy Margrie, MRC National Institute for Medical Research)
- To be announced (temporal statistical models of banknote ageing; 1st supervisor Prof. Mark Girolami)
- Nelson, J. D. B. and Kingsbury, N. G. (2012) Fractal dimension, wavelet shrinkage, and anomaly detection for mine hunting. IET Signal Processing Journal.
- Nelson, J. D. B. and Kingsbury, N. G. (2011) Enhanced shift and scale tolerance for rotation invariant polar matching with dual-tree wavelets. IEEE Transactions on Image Processing, 20(3): 814-821.
- Nelson, J. D. B. and Kingsbury, N. G. (2010) Fractal dimension based sand ripple suppression for mine hunting with sidescan sonar. Institute of Acoustics International Conference on Synthetic Aperture Sonar and Synthetic Aperture Radar.
- Nelson, J. D. B., Damper, R. I., Gunn, S. R. and Guo, B. (2009) A signal theory approach to support vector classification: the Sinc kernel. Neural Networks, 22 (1): 49-57.
- Guo, B., Gunn, S. R., Damper, R. I. and Nelson, J. D. B. (2008) "A fast separability-based feature selection method for highdimensional remotely-sensed image classification". Pattern Recognition 41 (8): 1670-1679
Nelson, J. D. B. (2005) A wavelet filter enhancement scheme with a fast integral B-wavelet transform and pyramidal multi-B wavelet algorithm, Journal of Applied & Computational Harmonic Analysis, 18(3): 234-251.
More publications, with preprints, can be found here
See also my Google Scholar and Google Sites pages and the Centre for Computational Statistics and Machine Learning site.
Page last modified on 12 mar 13 13:39