Using mathematics to understand dynamical biological systems

Mechanistic modelling of dynamical biological systems

I specialise in so-called mechanistic modelling of dynamical biological systems that change over time. Mechanistic models are a specific type of mathematical model that is based on scientific laws and they are often contrasted to statistical models. Despite the fact that mechanistic models are harder to implement than their statistical counterpart, they have several advantages. They require little data for model calibration, they contribute to mechanistic process understanding and they have great predictive capacity.

I have worked on many mechanistic models of different biological systems. Examples of biological processes I have worked on include biological ageing in baker’s yeast, cell polarisation in baker’s yeast, age-related increase in cancer risk and prion-like increase of biomarkers for neurodegenerative diseases such as Alzheimer’s disease. I have also worked on more methodological questions regarding model analysis, model selection and identifiability analysis using a special mathematical tool called Lie symmetries.

My background

I am currently a Postdoctoral Research Fellow at the Department of Mathematical Sciences of Chalmers University of Technology and the University of Gothenburg in Gothenburg, Sweden. From the same Department, I have a MSc in Engineering Mathematics and Computational Science from Chalmers University of Technology and a PhD in Applied Mathematics from the University of Gothenburg. I am also a Research Fellow with the Wenner-Gren Foundations in Stockholm. The Wenner-Gren Foundations funded both my current position and my previous position where I worked as a Postdoctoral Research Fellow at the Wolfson Centre for Mathematical Biology (WCMB) which is part of the Mathematical Institute of the University of Oxford.