PhD Candidate in Applied Mathematics, The University of Melbourne
My name is Claire Miller, and I am an applied mathematician currently studying for my PhD in Melbourne, Australia, submitting in February 2020. My current research is in computational biology, specifically multi-cellular modelling of skin tissue. For more details on this, refer to the research section. In this section, I will instead provide a bit of background about my research journey.
I studied engineering (computational and mechanical, with honours) at the University of Adelaide for my undergraduate degree, before moving to Melbourne to work as a graduate fellow at CSIRO. Whilst at CSIRO, I worked on development of a mathematical model for bushfire progression. This was really exciting work, particularly due to the obvious need for these types of models as, living in Australia, bushfires are so common and can be so devastating. Again, for more details, refer to the research section.
After a couple of years at CSIRO, I decided to go back for further study to get my PhD in applied mathematics. After much searching and talking to many, many, many researchers, I discovered the world of computational biology. Computational biology has so much breadth of opportunity and topics it encompasses, it can push you in any area of applied mathematics you could possibly think of. What excites me most about this area, is thinking about how the fundamental work we are putting in now could have a big impact people’s quality of life in the future. This is the most important thing to me about any research I do.
My current research in the computational biology field sits in multi-celullar systems, and the development of multi-scale models. In the future, I intend to stay in the biology application, but am very open to exploring other sub-fields.
The following is a list of all my publications in reverse chronological order. For citation information and abstracts please refer to my Google Scholar.
Article in revision – Claire Miller, Edmund Crampin, James Osborne. Maintaining the stem cell niche in multicellular models of epithelia. Intended for resubmission to: Physical Review E. Currently available on arXiv:1811.10781 [q-bio.TO].
Claire Miller, Matt Plucinski, Alec Stephenson, Carolyn Huston, Kay Charman, Mahesh Prakash, Andrew Sullivan, Simon Dunstall. Electrically caused wildfires in Victoria, Australia are over-represented when fire danger is elevated. Landscape and Urban Planning 167:267-274 (2017).
James Hilton, Claire Miller, Jason Sharples, Andrew Sullivan. Curvature effects in the dynamic propagation of wildfires. International Journal of Wildland Fire 25(12):1238-1251 (2016).
James Hilton, Claire Miller, Andrew Sullivan. A power series formation for two-dimensional wildfire shapes. International Journal of Wildland Fire 25(9):970-979 (2016).
James Hilton, Claire Miller, Andrew Sullivan, Chris Rucinski. Effects of spatial and temporal variation in environmental conditions on simulation of wildfire spread. Environmental Modelling and Software 67:118-127 (2015).
Claire Miller, James Hilton, Andrew Sullivan, Mahesh Prakash. SPARK – A bushfire spread prediction tool. Environmental Software Systems; Infrastructures, Services and Applications, pp. 262-271 (2015).
James Hilton, Claire Miller, Matt Bolger, Lachlan Hetherton, Mahesh Prakash. An Integrated Workflow Architecture for Natural Hazards, Analytics and Decision Support. Environmental Software Systems; Infrastructures, Services and Applications, pp. 333-342 (2015).
Gary Delaney, James Hilton, Paul Cleary, Claire Miller. The role of inter-grain friction in determining the mechanical and structural properties of superellipsoid packings. Powders and Grains 2013: Proceedings of the 7th International Conference on Micromechanics of Granular Media (2013).
Thesis title: Understanding the regulation of epidermal tissue structure by molecular and cellular processes using multi-scale models.
Supervisors: Dr James Osborne and Prof. Edmund Crampin.
The skin forms the body’s protective barrier against the world, with the epidermis providing the outer-most layer of this defense. The epidermis is a complex system combining sub-cellular, cellular, and tissue level processes to maintain its structure. If we want to understand what happens during biological malfunction, such as in skin disease or cancers, it is important to first understand normal function.
In my PhD, I have developed a multi-cellular model of the inter-follicular (between hair follicles) epidermis. The model uses overlapping spheres to model cell interactions and a stochastic rule-based method to model cell proliferation. I am using this model to help understand how the epidermis regulates itself in homeostasis. Specifically, I am interested in regulation of epidermal tissue height. The main aspects to steady state tissue height are maintenance of a stem cell population in the basal layer, and a steady rate of cell loss from the top of the tissue. I have looked at both these aspects in detail in my project.
The maintenance of the basal layer is an area I look at in my first paper, available on arxiv (arXiv:1811.10781 [q-bio.TO]). In this paper, I describe an artefact in commonly used epithelial modelling methods that can cause erroneous loss of stem cells from the basal layer. I describe how this loss occurs from the model, and suggest a method to counteract it. I show that, using this method, higher population sizes can be maintained in the basal layer of the epidermis in our models. The method suggested is reflective of a mechanism that has been observed during division in different tissues: the regulation of mitotic spindle orientation.
The second aspect to maintaining tissue height is the regulation of cell loss from the top of the tissue. I have been investigating how to regulate this and am implementing a degradation of cell-cell adhesion as a way to control cell loss. I am investigate the implentation of this degradation loss both as a simple scaling of adhesion as a cell gets older, and also by implementing a system of ODEs in each cell to represent the subcellular interactions that are thought to cause the loss of adhesion.
My model is built using the Chaste libraries. For more details go to https://www.cs.ox.ac.uk/chaste/.
In Australian landscapes, bushfires can cause devestating damage to communities, and even fatalities. If we want to best be able to combat these fires, understanding where they are likely to spread is critical. Getting this information as quickly as possible is vital to decision makers.
When I was at CSIRO I worked on a team developing a fire spread prediction model. The model was developed for use in operational situations and was implemented using a level set method. The rate of spread model that determined the level set function was based on empirical data. For more information about the model, I refer you to the following papers: model implementation, and a high level description of the prediction tool. Alternatively see the Spark website.
The model was also developed for fire research. This included understanding the effect of uncertainty in inputs to model output, and investigating different rate of spread functions. Papers on this research: the effect of variation in inputs, and the effect of including curvature in the spread function
A lot of my work in this area was around data collection for input into the model. This included stabilisation and conversion of video footage of fires into 2 dimensional fire lines, and sourcing of fuel data from different sources such as government data or satellite data.
In addition, I did some research into understanding why powerline fires tended to be more significant than other ignition types. The paper that came from this work can be accessed here.
Outside of my research, I love getting outdoors. I try and spend as many weekends as possible either multi-day hiking, bouldering, or skiing in the winter. I also have a website about multi-day hiking in Australia: https://www.glampliteoz.com.
My current local time is .