Dr Francesca Arrigo is a Lecturer in Mathematics and Statistics at the University of Strathclyde whose research lies at the interface of numerical linear algebra, matrix analysis, and network science. Her work develops mathematical and computational tools for analysing complex networks, with a particular focus on centrality measures. 

Her research has made important contributions to the theoretical foundations of network science. She has published influential work on non-backtracking walks, dynamic network measures, nonlinear eigenvector-based centralities, and, most recently, Katz centrality.

Dr Arrigo's most significant contribution has been the establishment of a linear algebraic framework for analysing networks using non-backtracking walks. This work demonstrated how excluding or downweighting immediate returns in network walks can yield more realistic measures of centrality than classical approaches. The resulting theory has helped shape modern research on network centrality, resilience, and information propagation, and constitutes a significant advance in the mathematical foundations of network science.