Professor Fabian Spill PhD

Professor Fabian Spill

School of Mathematics
Professor of Applied Mathematics
UKRI Future Leaders Fellow

Contact details

School of Mathematics
Watson Building
University of Birmingham
B15 2TT

Fabian Spill is a Professor of Applied Mathematics.

Fabian's research is centred on various aspects of Mathematical Biology. From the mathematical side he is mainly interested in applications of stochastic models and various differential equations, from ODEs to coupled bulk-surface reaction-diffusion systems. From the application side, he is interested in cancer biology, mechanobiology, and the dynamic interplay of cells and their microenvironment.


  • PhD in Physics, Imperial College London, 2010
  • Diploma in Physics, Humboldt University Berlin, 2007


Fabian Spill studied physics and mathematics at Humboldt University, Berlin, graduating with a diploma in physics in 2007. He then completed a PhD in theoretical physics at Imperial College London in 2010, working on Yangians, integrable systems and string theory under supervision of Arkady Tseytlin. After a brief spell in finance, where he worked as a quantitative analyst developing and implementing mathematical models to price and risk-manage complex derivatives, he moved into mathematical biology. First, he joined the University of Oxford in 2012, working with Helen Byrne and Philip Maini. Then, he moved to the US in 2014, working with Roger Kamm and Muhammad Zaman at the Massachusetts Institute of Technology and at Boston University. He returned to Britain in 2017, starting his current position at the University of Birmingham; he received a UKRI Future Leaders Fellowship in 2020, and was promoted to Reader in 2021 and Professor in 2023.

Postgraduate supervision

Fabian is happy to supervise PhD students in any area of his research. All PhD projects may either focus on the development of mathematical methods, or they may be performed in close collaboration with leading experimentalists, for example, in biology, medicine or engineering.

Please refer to the PhD Opportunities list for more information, choosing F Spill as the supervisor for a list of currently available projects.

Contact Fabian if you have ideas for alternative projects.


Fabian has diverse research interests in the field of mathematical biology. Currently, he is trying to understand how mechanical properties of the cells and their microenvironment influence cell behaviour through mechanosensing pathways. For instance, YAP/TAZ are two important intracellular molecules which increase their activity with increasing stiffness of the substrate on which the cells are attached too, and this can drive proliferation of these cells. In the context of tumours, which are often stiffer than comparable healthy tissues, this might imply that physical properties such as stiffness can drive tumour progression (such as uncontrolled proliferation), complementing well-studied genetic alterations in tumours.

Fabian is developing mathematical models of the YAP/TAZ regulating pathway to study how mechanical and molecular stimuli are integrated by cells to mediate their responses. Moreover, he is interested in understanding how the subcellular localisation of signalling molecules affects the outcome of signal integration. This is of importance far beyond mechanosensing pathways, as almost all pathways involve subcellular localisation of at least some important molecules, such as those binding to the cell membrane. This can be especially important when cells change their shapes, and thus the region of membrane/cytosol interactions changes. Consequently, otherwise identical cells with different shapes can behave differently, simply because of their altered geometry.

Fabian is also interested in the application of stochastic models to biology. He investigated how stochastic effects can change the behaviour of reaction-diffusion systems, developed methods to improve simulation efficiency of such systems, and applied such methods to biological systems including tumour angiogenesis or travelling wave problems. More recently, he investigated how stochastic effects can shift the evolutionary outcome of the in-vitro selection of oligonucleotides. This later system is used to identify molecules which have particular binding properties to diverse target molecules.