Jamieson Kaiser

JKaiserJamieson Kaiser

Monash University


Jamie is about to enter his final year of an aerospace engineering and science double degree at Monash University. In his science degree he will be completing a double major in maths and a minor in physics. Jamie has already completed two internships for his engineering degree, one with the CSIRO looking at better understanding the anisotropic behaviour of carbon fiber and the other with DSTO working on calibrating their schlieren imaging system in the transonic wind tunnel. Jamie is very excited to get to spend the summer working on maths research with Dr. Joel Miller in the Monash Maths Department, thanks to an AMSI scholarship.

With Joel’s guidance he will be investigating the spread of dynamic processes on random networks which have some spatial structure. The comparison of these results to those on purely random networks should provide some insight into the effects of the more structured networks. This research as a wide range of applications from infectious disease modelling to understanding how ideas propagate in events like the Arab Spring.

Outside of maths, Jamie’s biggest passion is comedy which he discovered while on exchange at Penn State through their stand-up club and humour publication Phroth. He also loves listening to radio shows and podcasts and has had a radio show on Radio Monash for three years. He also stays fit and active by playing soccer and won a silver medal in the Australian Uni Games in lawn bowls this year.

He is unsure exactly what his future direction will be but is mainly tossing up between further studies into mathematics or trying to combine his two loves of science and presenting ideas into a career in science communication.  Whatever the future holds, he hopes it will be interesting.

The Spread Of Dynamic Processes On Random Graphs With Spatial Structure

Many dynamic processes happen on networks such as the spread of diseases or ideas.  Some of these are well understood in random networks.  However, real networks have spatial structure to them, which influences the spread.  In this project we will look at a (still unpublished) class of random networks that have spatial structure.  We will simulate the spread of these processes and then study the resulting outcomes, comparing them with random networks.  This has application to understanding how diseases spread, understanding how the Arab Spring spread, or any of a number of other interesting social or biological problems.

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