PhD student, RMIT University
Why did you choose to study the IDTC program?
I first heard about the IDTC program while visiting AMSI. I had been working as a software developer for two years and was ready for a new challenge. Ultimately my goal was to find a job in industry where I would be able to use my mathematical background. However, seeing as my earlier studies were all in pure mathematics, I thought it would not be a bad idea to further educate myself. The IDTC program turned out to be a perfect fit, combining an interesting industry problem with course work and academic research. On top of that the scholarship and travel budget were very attractive compared to other PhD programs.
What new skills or experiences have you learned along the way?
I have learned a lot about academic research. For instance I have learned how to find and analyse relevant literature, how to do research and how to write about it for publication as well as how to present at conferences. Furthermore, the IDTC allowed me to gain in-depth knowledge on topics related to my research as well as non-related topics. I have also learned valuable skills by attending the IDTC meetings, such as communicating my research and discussing problems with people from industry at the MISG.
Would you recommend this program to other PhD students?
Yes, definitely. I think the program is a great initiative and has many perks over doing a regular PhD. The regular meetings of our cohort as well as the coursework and additional presentations and workshops have been very valuable.
How would you describe your research?
My research aims to develop mathematical tools and measurements to better understand the structure of large networked data. There are many examples of networked data, for instance social networks, communication networks, transport networks and biological networks. Since datasets are increasing in size and complexity, new mathematical tools are necessary to better understand large systems.
What problem does your research solve?
Some of the most important techniques in network analysis rely on random network models: algorithms that generate networks using a random process. The interdisciplinary nature of network science calls for a great variety of such models. My research addresses both the need for a more comprehensive overview and the need for a greater variety of random network models by reformulating existing algorithms and introducing new algorithms.
What impact does your research have on people’s lives?
The impact of my research is in its future applications, when the developed mathematical models are used in the analysis of real networks. In this regard, because of the great diversity of real networks, the mathematical models developed through this research have potentially limitless application.
What career goals do you have after completing the IDTC program?
When I complete my PhD, I hope to find work within a research and development group of a technological company to develop and implement algorithms.
How has the IDTC program prepared you to enter the workforce?
I have learned valuable communication skills and am more knowledgeable about all the different fields in mathematics. I feel confident looking up relevant literature to solve applied problems.