| 11:00 - 11:30 || Arrival and Coffee |
| 11:30 - 12:30 || Michael Goldstein, Durham University, UK
Uncertainty Analysis for Complex Physical Models
Accounting for, and analysing, all the sources of uncertainty that arise when using
a complex model to describe a large scale physical system is a very challenging
task. I will give an overview of some Bayesian approaches for assessing such uncertainties,
with particular application to problems of model calibration. The approach will be illustrated
with an application concerning the calibration of a Galaxy Formation simulation against
various observational features drawn from Galaxy Surveys.
| 12:30 - 14:30 || Lunch |
| 14:30 - 15:30 || Richard Gibbens, University of Cambridge, UK
Road transport data and their uses
There is an increasing quantity of road transport data that is becoming available. Both historical archives, in some cases consisting of decades worth of data, as well as new types and sources of data are being made available. In the future we can expect these new forms of data to be available in near real-time. What uses can be made of this data?
In this talk we shall illustrate how road traffic data is helping modellers grapple with the nature of traffic flows and congestion. New forms of data are also an opportunity for service providers to assist travellers and transport operators. We shall consider a specific application where historical data can be combined in a statistical model with real-time traffic data to make better predictions of journey times. Surprisingly, our findings suggest that good prediction tools can be constructed that have rather modest online requirements.
| 15:30 - 16:00 || Coffee/Tea |
| 16:00 - 17:00 || Carola Tiede, Max Planck Institute for Astronomy, Heidelberg, Germany
Classifying objects and finding structure in astronomical surveys
Astronomy is a data-driven discipline. It seeks to describe
and explain the observable universe within the framework of
physics. In doing so it has revolutionized parts of science, famous
examples being nuclear fusion (the reactions which power the sun and
all stars) and the apparent existence of large amounts of dark matter
(inferred from observations of stellar motions). We cannot
experiment with the universe: we can only learn by observing,
modelling and interpreting data. Surveys, then, which reach fainter
objects, higher spatial resolution, new wavelength regions and higher
precision, are astronomy's lifeblood. Surveys routinely now
observe billions of stars and galaxies, measuring positions,
velocities, colours and spectra. Modelling, interpreting and
understanding these heterogeneous, multidimensional data sets is a
huge challenge, and relies on efficient nonlinear algorithms for
classification, regression and clustering. I shall give an overview of
the challeneges in this area facing the upcoming Gaia Galactic survey
mission. I shall present some techniques (standard and novel,
statistical and heuristic) which the scientific community is using to
address these challenges.
| 17:00 || Close |
Lunch will be provided by a local Thai restaurant (Zen) 15mins walk from the Maths Department. Lunch will consist of a soup starter followed by a choice of meat or vegetarian main and comes with one soft drink. Those who wish to make their own lunch arrangements can pay a reduced registration fee.
This event is intended as a day meeting, and therefore we do not offer any overnight accommodation. If you are planning an overnight stay, then information
on suitable accommodation (en-suite rooms, B&B, in Durham colleges) is available here. All colleges
offer suitable accommodation, if you wish a recommendation then we would suggest Collingwood College.
More information about travelling to Durham can be found here and here. A useful map
can be found here, where the Department of Mathematical Sciences is marked (15).
Car parking at the Department of Mathematical Sciences is in extremely limited supply. For those arriving by car, it will be possible to obtain a day-permit at the entrance barriers - however this is no guarantee that you will find a place.
A preferable alternative would be to use the Durham Park and Ride at the nearby Howlands Park site which offers a large supply of secure parking.
The registration fee is £35 which includes morning coffee, lunch and afternoon tea. A reduced rate of £25 is available to students. For those who
wish to make their own lunch arrangements a further reduced rate of £25 and £15 is available for non-students and students respectively.
To register, please complete this online form as soon as possible. After completing the online registration,
please send your payment by cheque made payable to Durham University with a completed invoice form to:
Department of Mathematical Sciences
Full payment instructions are given on the invoice form.
If you have any questions, please contact Jochen Einbeck via email, or telephone (0191) 3343125.