# Scientific

## Universal torsion, L^2-invariants, polytopes and the Thurston norm

We introduce universal torsion which is defined for -acyclic manifolds with torsion free fundamental group and takes values in certain -groups of a skew field associated to the integral group ring. It encompasses well-know invariants such as the Alexander polynomial and -torsion. We discuss also twisted -torsion and higher order Alexander polynomials which can also be derived from the universal invariant and assign certain polytopes to the universal torsion. This gives especially in dimension 3 interesting invariants which recover for instance the Thurston norm.

## Introduction to the Farrell-Jones Conjecture

## Decision problems, curvature and topology

## PIMS Symposium on the Geometry and Topology of Manifolds

## Nassif Ghoussoub Receives Honorary Degree from the University of Victoria

## Climate Change – does it all add up?

Climate change has the potential to affect all of our lives. But is it really happening, and what has maths got to do with it?

In this talk I will take a light hearted view of the many issues concerned with predicting climate change and how mathematics and statistics can help make some sense of it all. Using audience participation I will look at the strengths and weaknesses of various climate models and we will see what the math can tell us about both the past and the future of the Earth's climate and how mathematical models can help in our future decision making.

## PIMS-SFU Undergraduate Summer School on Rigorous Computing

## A topological look at the vector (cross) product in three dimensions

## It’s All in the Follow Through – what research in math education says ... and doesn’t say

## Robustness of Design: A Survey

When an experiment is conducted for purposes which include fitting a particular model to the data, then the ’optimal’ experimental design is highly dependent upon the model assumptions - linearity of the response function, independence and homoscedasticity of the errors, etc. When these assumptions are violated the design can be far from optimal, and so a more robust approach is called for. We should seek a design which behaves reasonably well over a large class of plausible models. I will review the progress which has been made on such problems, in a variety of experimental and modelling scenarios - prediction, extrapolation, discrimination, survey sampling, dose-response, etc