Meet the Speaker – Qianqian Yang


Queensland University of Technology

We talk to Dr Qianqian Yang about the challenges facing researchers in her field and advice for aspiring researchers.


1. Can you tell us about your work? What drives your interest in this field?

I love to work on fractional order PDE models and their applications. In particular, I work on a few problems: (i) anomalous diffusion models for MRI signals to probe healthy and diseased brain tissue microstructure, (ii) MR image-based mathematical modelling of brain tumour growth, and (iii) numerical methods for solving fractional order PDEs.

2. What are the most interesting “big questions” or challenges facing researchers in your area?

When applying fractional models to real application problems, one of the challenges facing researchers is to interpret fractional order model parameters (alpha or beta) in terms of their physical meaning. In diffusion weighted MRI, fractional order model parameters are measurements of the extent of heterogeneity of the tissue, and spatially resolved maps of fractional order parameters provide a better contrast of tissue structure compared with the conventional diffusion maps.

3. Do you have any advice for future researchers?

Keep learning (or keep sharpening skills), be curious (keep finding interesting problems to solve), and be patient.

4. Deepening field knowledge and providing a networking platform, why are opportunities such as AMSI Winter School so valuable? What do you hope attendees take from your lectures?

Fractional calculus and applications has become a hot topic in the literature in the past two decades. AMSI Winter School provides such a great opportunity that for the first time we introduce this concept and methods in classes to more young talented mathematicians in Australia. I hope the attendees can apply the techniques developed in the lectures to their own problems one day.

Dr Qianqian Yang will be presenting the topic Numerical methods for solving space-fractional reaction-diffusion equations at the 2019 Winter School at Queensland University of Technology this July

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