Senior Lecturer in Statistics
Department of Mathematics
Royal Holloway, University of London
Egham, Surrey, TW20 0EX, The United Kingdom
Tel: +44 1784 276528
Research interests: probability theory and stochastic processes
Current research topics:
I am interested in supervising a PhD project related to my current research topics
and would be happy to receive applications from PhD candidates.
Example of PhD project:
"Long term behaviour of interacting birth-and-death processes."
A single birth-and-death process on the set of non-negative integers is a classical probabilistic model for the size of a population. This is a continuous time Markov chain (CTMC) which evolves as follows. When the process is at state k, it can jump either to state k+1 (this transition is interpreted as birth event), or to state k-1, if k>0 (this transition is interpreted as death event). These transitions occur with state-dependent rates. The project concerns the long term behaviour of a class of Markov processes that can be interpreted as a system of birth-and-death processes, whose components evolve subject to a certain interaction (interacting birth-and-death processes). Originally interacting birth-and-death processes were motivated by modelling competition between populations. In this case they are also known as competition processes. Another class of interecating birth-and-death processes is provided by growth processes motivated by cooperative sequential adsorption (CSA). In CSA duffusing particles can get adsorbed by a material surface, when they hit the latter. The main peculiarity of CSA is that the adsorbed particles can change the adsorption properties of the material in a sense that they either attract, or repulse other particles. The growth process is a system of pure birth processes, where components evolve subject to a CSA type interaction. For example, the components of the growth process can either accelerate, or slow down the growth of each other. In the discrete time setting such a growth process can be regarded as an interacting urn model. The latter is closely related to the generalised Polya urn model. The long term behaviour of a single birth-and-death process is well known. Given a set of transition rates one can, in principle, determine whether the corresponding Markov chain is recurrent or transient and compute various characteristics of the process. Interaction with others can significantly affect the long term behaviour of the process. In general, the long term behaviour of interacting birth-and-death processes is largerly unknown. Studying this behaviour requires a solid background in probability and stochastic processes. A PhD student will learn and apply various probabilistic techniques. For example, this includes the Lyapunov function method (based on the martingale theory) widely used for studying Markov processes.
Recent publications and preprints (for my other publications see mathscinet.ams.org or pure.royalholloway.ac.uk )