Models for Understanding Time Series from Intensive Care Units

Patients in intensive care are monitored by many sensors (heart rate, blood pressure, temperature etc) giving rise to time-series data that has rich structure. The goal of this project is to identify various events in the data streams, both physiological and artifactual. If this can be achieved reliably then identified or predicted physiological events could be flagged to medical staff, as a "smart alarm". Artifactual events (such as a probe recalibration) need to be identified and then discounted. The methods for this work will be based on the Factorial Switching Linear Dynamical System (FSLDS; Quinn, Williams and McIntosh, 2009), but there are many new irections
to explore. The work will be carried out in collaboration with Intensive Care Units in Scotland.

This is an opportunity to join a world-leading research group in machine learning. The machine learning group in the Institute for Adaptive and Neural Computation is made up of 6 academic staff: Chris Bishop, Chris Williams, Amos Storkey, Charles Sutton, Guido Sanguinetti, Iain Murray. The group conducts research into the development of novel probabilistic machine learning methods, and the application of these novel methods to cutting edge scientific/technological problems.

The project is suitable for a student with a strong mathematical background, ideally a first class degree in Computer Science, Mathematics, Physics or Engineering. Some knowledge of machine learning and computer vision is highly desirable. Informal enquiries should be addressed to Prof Chris Williams; please attach a CV, a list of courses taken and grades obtained, and a 1-2 page statement of your research interests. See http://homepages.inf.ed.ac.uk/ckiw/mypages/students.html for more information for prospective PhD students. We recommend that students make informal contact a before making a formal application, ideally as soon as possible: the more time between informal contact and the application deadline the better. Application deadlines match the standard Informatics deadlines at http://www.ed.ac.uk/schools-departments/informatics/postgraduate/apply/keydatesresearchappns.

We advise students to apply before the 16 December 2011 deadline.

Formal application must be through the School's normal PhD application process: http://www.ed.ac.uk/schools-departments/informatics/postgraduate/apply Select the Informatics: Institute for Adaptive and Neural Computation research area.