The Sigproc group holds a regular seminar series.
We are interested in all aspects of Statistics, Signal Processing, Control (stochastic), Communications and the integration of these. If you would like
to give a seminar, please contact me.
5R12 Stochastic Processes and Optimisation Methods (Markov chains component)
Methodology Monte Carlo methods (Particle Filters, Markov Chain Monte Carlo) for computation and its application to Bayesian inference, Maximum Likelihood, Stochastic Optimal control (e.g. Markov Decision Processes). Other interests include Distributed algorithms for inference, Stochastic approximation, Reinforcement Learning
Multi-target tracking, Sensor networks for condition monitoring, Gaming (e.g. Cheat Detection in online gaming, inferring player strategies), Signal processing for single molecule fluorescence microscopy
Rutherford Appleton Laboratory: Unraveling the supra-molecular rules in signal receptor networks, jointly with Dr. M. Hobson, 2009-2014.
One of the aims is to develop and implement state-of-the
art Bayesian methods for the analysis of biological data sets
originating from hybrid multidimensional single molecule methods and fluorescence lifetime
imaging microscopy on Graphical Processing Units to exploit the parallel processing architecture.