Statistical and probabilistic modelling for the sciences

Much of our work involves the design of models for interpreting data collected by colleagues working in different parts of the University and with collaborators working in Industry. Models are constructed that encode fundamental scientific understanding in a way that is analytically and/or computationally tractable. In this way we help scientists explore the implications of their theories and their experiments. 

The Statistics and Probability group at York are contributing to projects with biologists looking at plant circadian rhythms (see for example a current BBSRC-funded project on ‘Novel strategies for efficient selection of lines with synchronised development’) and at the behaviour of disease-causing parasites. Currently, several of us are collaborating with colleagues in the Department of Computer Science on projects involving the design and analysis of systems involving autonomous robots.