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My research spans a wide range of topics, mainly in the areas of computer vision, structural pattern recognition and quantum algorithms.

Graphs and Networks

Social NetworkMy main research interest is in algorithms and methods for handling large quantities of data in the form of graphs or networks. This area of research is both practical and highly interdisciplinary. I have applied these methods to problems in chemoinformatics, bioinformatics and finance, for example in the prediction of the properties of chemical compounds, high level classification of RNA molecules, understanding financial interactions and discovering similarities in protein interaction networks.

  • Graph features from paths, walks and spectral graph theory
  • Graph kernels
  • The statistical modelling of graph datasets
  • Graph complexity and entropy
  • Graph Matching
Ye C, Wilson RC, Comin C, F. Costa L and Hancock ER (2014), "Approximate von Neumann entropy for directed graphs", Physical Review E., 5, 2014. Vol. 89(5) American Physical Society. [DOI]
Aziz F, Wilson RC and Hancock ER (2013), "Backtrackless Walks on a Graph", IEEE Transactions on Neural Networks and Learning Systems. Vol. 24(6), pp. 977-989. IEEE Computational Intelligence Society. [DOI]
Xiao B, Hancock ER and Wilson RC (2009), 
"A generative model for graph matching and embedding", Computer Vision and Image Understanding., 7, 2009. Vol. 113(7), pp. 777-789. Academic Press Inc. [DOI]
Luo B, Wilson RC and Hancock ER (2006), "A spectral approach to learning structural variations in graphs", Pattern Recognition., 6, 2006. Vol. 39(6), pp. 1188-1198. Elsevier Limited. [DOI]
Rocha J, Segura J, Wilson RichardC and Dasgupta S (2009), "Flexible structural protein alignment by a sequence of local transformations", Bioinformatics., 7, 2009. Vol. 25(13), pp. 1625-1631. [DOI]

Computer Vision

Telescope In the area of computer vision, I have worked on a variety of topics, including 3D shape modelling and recognition, super-resolution reconstruction of face images, the fusion of shape-from-shading and stereo, plenoptic imaging systems and visual inspection.

Wilson RC and Hancock ER, "Plenoptic Imaging for Seeing Through Turbulence", S+SSPR 2018.
Frederico A Limberger, Richard C Wilson, "Curvature-based spectral signatures for non-rigid shape retrieval", Computer Vision and Image Understanding 2018.
Arnaud Dessein, William AP Smith, Richard C Wilson, Edwin R Hancock, "Example-Based Modeling of Facial Texture From Deficient Data", ICCV 2015.
TSF Haines, RC Wilson "Belief propagation with directional statistics for solving the shape-from-shading problem", European Conference on Computer Vision, 780-791 2008.

Quantum Algorithms

I also carry out some research in the area of quantum algorithms, particularly those applied to graph-based problems or computer vision. I have studied the quantum walk in the context of distinguishing graphs, and quantum representations of images.

Zhang Y, Lu K, Xu K, Gao Y and Wilson RC (2015), "Local feature point extraction for quantum images", Quantum Information Processing. Springer New York.

Nicosia V, Machida T, Hancock ER, Wilson RC, Konno N, Latora V and Severini S (2014), "Co-evolution of networks and quantum dynamics: a generalization of preferential attachment", Journal of Statistical Mechanics: Theory and Experiment. IOP Publishing Ltd..

Ren P, Aleksic T, Emms D, Wilson RC and Hancock ER (2011), "Quantum walks, Ihara zeta functions and cospectrality in regular graphs", Quantum Information Processing., 6, 2011. Vol. 10(3), pp. 405-417. Springer New York.

Emms D, Wilson RC and Hancock ER (2009), "Graph matching using the interference of continuous-time quantum walks", Pattern Recognition., 5, 2009. Vol. 42(5), pp. 985-1002. Elsevier Limited.