Associate Professor
School of Mathematics
University of Bristol, U.K.

My research focuses on the use of information theory to study formation, maintenance and decline of complex systems. Examples are vitrification, protein dynamics, quantum physics and stem cell differentiation. This research is part of a long-term goal to build a foundational framework for complex systems involving many areas of mathematics, science, and philosophy of science. In a recent book I have developed a taxonomy of complex systems. This is relevant for phenomena ranging from physics to biology to social science. Current topics are:
  • stability of democracy,
  • measuring features of complexity in climate change adaptation and mitigation interventions,
  • information theoretic measures of complexity features,
  • philosophical foundations of complexity.

I am external faculty at the Complexity Science Hub Vienna.
I am affiliated member of the Centre for Science and Philosophy.
What is a complex system?
In a forthcoming book I have developed a taxonomy of complex systems in collaboration with James Ladyman. This question is still not fully answered. Complex systems consist of many elements with many interactions between them. Their macroscopic behaviour is largely unpredictable from the elements alone because of feedback and noise. Early aspects of this work are published in the European Journal of Philosophy of Science.
Complex system perspective on democracy
Complex systems theory offers a range of powerful new tools to analyse the stability of social institutions in general, and democracy in particular. What makes a democracy stable? And which processes potentially lead to instability of a democratic system? This work offers a complex systems perspective on this question, informed by areas of the mathematical, natural, and social sciences.
Entropy landscape of stem cells
It has been conjectured that there is an analogy to the concept of entropy in statistical mechanics. In order to assess these predictions, we computed the Shannon entropy single-cell gene expression data. We find that the Shannon entropy is not decreasing but instead it increases toward the point of commitment before decreasing again. This indicates the importance of noise in cellular development.
Special Issue 'Information Theory in Complex Systems'