THE REES DISTINGUISHED LECTURER SERIES
October 22, 2009
3:30 – 4:30 pm
TBA
TITLE: The Marriage Equation:
A practical theory for predicting divorce and a scientifically-based marital therapy
Professor James D. Murray
Center for Mathematical Biology
Mathematical Institute
University of Oxford
&
Applied Mathematics
University of Washington
ABSTRACT
The rise in divorce rates in developed countries is a widespread, important but poorly understood phenomenon. I shall describe a simple, but surprisingly predictive, mathematical model, based on only a few parameters describing specific marital interaction patterns. The mathematical model characterizes differences between different types of stable couples whose marriages are likely to last from two types of unstable couples. I shall show how we gather a couple’s interaction data, how their parameters are determined and what they predict for the couple’s marital future. In a 12 year longitudinal study on a large number of marriages our model predicted divorce with an accuracy of 94%. The work has helped us design new scientifically-based intervention strategies for troubled marriages which are proving encouragingly successful in clinical practice.
October 23, 2009
3:30 – 4:30 pm
TBA
TITLE: On the Growth of Brain Tumors: enhancing imaging techniques
& highlighting inadequacies of current therapies
Professor James D. Murray
Center for Mathematical Biology
Mathematical Institute
University of Oxford
&
Applied Mathematics
University of Washington
ABSTRACT
The prognosis for patients with high grade brain tumours (gliomas) is grim and the various treatment protocols such as surgery, radiation and chemotherapy cannot effect a cure. I shall describe, without any technical details, a simple but very practical model which uses patient data and brain scans to quantify the spatio-temporal growth of such brain tumours. Analysis of the model shows how difficult it is to decide on the tumour volume to be treated and shows why such treatments have so little success. The model simulations can estimate life expectancy for individual patients and show how it is possible to use the patient's past record to predict the efficacy of possible treatments. Recent patient data indicates that calculating such an index of treatment efficacy is indeed a realistic aim.