Dr Samuel Johnson

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samuel johnson

Position

Turing Fellow

Partner Institution

University of Birmingham

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Research areas

Dynamical systems & differential equations Neural networks Neuroscience Nonlinear dynamics Deep learning Graph theory Stochastic (Mathematical modelling) Data science of government & politics Social networks Combinatorics

Bio

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.

Research interests

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.

Turing Research

Turing Publications