Dr James Nelson

Position Senior Lecturer
Phone (external) +44 (0)20 7679 1875
Phone (internal) 41875
Email(*) j.nelson
Personal webpage http://www.homepages.ucl.ac.uk/~ucakjdb/
Themes Stochastic Modelling and Time Series

* @ucl.ac.uk

Biographical Details

James Nelson

James Nelson joined the Department of Statistical Science as a Lecturer in 2010 and became Senior Lecturer in 2013. 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).

Research Interests

Multiresolution analysis; random fields; spatial models; statistical machine learning; statistical signal and image processing. Examples: Markov random fields; wavelet/Riesz basis and packet construction and pursuit/optimisation; sparsity and other regularisation with applications to detection and classification; weak self-similar random fields; support vector machine kernel construction and hyper-parameter estimation; generalised cardinal series and sampling theory; robust, regularised Hurst parameter estimation for texture and volatility models.


  • Hojjat Akhondi-Asl (time series and regularisation)
  • Chunli Guo (compressive sensing for beamforming)
  • Alfredo Kalaitzis [now at Tata Consultancy Services] sparse methods for anomaly detection
  • Vladimir Krylov [now at University of Genoa]

    • stochastic geometry for image analysis
    • semi-supervised anomaly detection
  • Diego Tomassi [funded visit from National University of the Littoral] (wavelet shrinkage using adaptive structured sparsity constraints)

Research Students

  • Alex Gibberd (sparsity on graphs and statistical machine learning on networks)
  • Maria Toomik (multiresolution analysis and regularisation approaches to highly structured data)
  • Jean-Baptiste Regli (computational statistics and spatial models)
  • Nikolaos Tsipinakis (regularity and information filtering approaches to uncertainty management)
  • Johannes Happenhofer (the lasso and multiresolution analysis)
  • 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)


  • Please feel free to get in touch if you are a prospective research student, visiting researcher, industrial partner, or would like to collaborate on a project.

Selected publications

  • Nelson, J. D. B. (2015) "Enhanced B-wavelets via mixed, composite packets" IEEE Transactions on Signal Processing, 63(12):3191-3203
  • Tomassi, D. R., Milone, D. H., and Nelson, J. D. B. (2015) "Wavelet shrinkage using adaptive structured sparsity constraints". Signal Processing, 106:73-87
  • Nelson, J. D. B. (2014) "On the equivalence between a minimal codomain cardinality Riesz basis, a system of Hadamard-Sylvester operators, and a class of sparse, binary optimisation problems". IEEE Transactions on Signal Processing, 62(20):5270-5281
  • Gibberd, A. J. and Nelson, J. D. B. (2014) "High dimensional changepoint detection with a dynamic graphical lasso". IEEE International Conference on Acoustics, Speech, and Signal Processing 

  • Nelson, J. D. B. (2013) "Fused Lasso and rotation invariant autoregressive models for texture classification". Pattern Recognition Letters 34(16):2166-2172 
  • 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

More publications, with preprints, code, and opportunities, etc can be found here

See also my Google Scholar and Google Sites pages and the Centre for Computational Statistics and Machine Learning site.