Samuel Johnson received a PhD in physics from the University of Granada in 2011. He went on to work as a postdoc at the University of Oxford, a Marie Curie research fellow at Imperial College London, and a Zeeman lecturer at the University of Warwick, before taking up a lectureship in applied mathematics at the University of Birmingham in 2017.
Sam works on several topics related to complex systems, focusing particularly on the relationship between network structure and dynamics:
- Cooperation and conflict. Together with colleagues at The Alan Turing Institute, Sam is studying how networks of human interaction affect whether a society is peaceful or at war.
- Neural networks. Much of Sam’s work has focused on how the computational properties of neural networks depend on their architecture. This research is related to both neuroscience and artificial intelligence.
- Trophic coherence. Sam and his collaborators have recently identified and studied a feature of directed networks called trophic coherence, which is important for properties such as dynamical stability and robustness. They are currently investigating the causes and consequences of this property in a wide variety of systems, including ecosystems, financial networks, neural networks, railways and gene regulatory networks.