My research interests are focused on various aspects of machine learning, computational mathematics, and signal processing:
Kernel Machine. Investigating kernel machine as a common representation for various machine learning algorithms including MLPs, RBFs, Gaussian processes, support vector machines and wavelets. Also looking at the construction of new kernel functions which can be used to cope with the discrete structure in pattern such as object shape structure etc.
Bayesian, probabilistic and statistical methods in machine learning (with Dr. S.R. Gunn and Prof. C.J. Harris, Southampton). Investigating the role of prior knowledge in kernel machine learning algorithms and adaptive variational algorithms.
Data fusion . General interest in the application of data fusion to improve the performance of learning for both regression and classification algorithms.
Wavelet and Multiscale Analysis. Currently my main interest is in developing multiscale/multilevel and adaptive solutions to machine learning. This work has applications in neural networks, support vector machines and pattern recognition.
Shape modelling, estimation and recognition (with Dr. D.M. Shi, Singapore). This research is investigating novel methods for modelling Shapes in images and developing recognition algorithms.
I am keen to recruit more PhD students to work with me in the fields of Machine Learning and Artificial Intelligence.
If you would like to do a PhD in this school or collaborate with me then please contact me. A list of possible PhD titles/themes is available here. For your convenience, I created FAQs on PhD Admission and Scholarships Applications.
Please refer to Research Higher Degrees Office's Website for more details about PhD program and the information about the available scholarship at the University