Peter S. Mann

Welcome to my homepage! I am a post doctoral researcher at the University of St Andrews in Scotland. I work at the interface of graph theory, combinatorics, machine learning, epidemiology and differential geometry in the School of Computer Science. A common theme of my research investigates the role of network structure on dynamics that occur on top of them with an emphasis on higher-order structure beyond pairwise interactions.

I am particuarly interested in using the generating function formulation, in conjunction with techniques from statistical mechanics, to solve the dynamics of spin and percolation models. These models frequently have application to epidemiology or machine learning of complex or high-dimensional datasets.

Parallel to this work I am the author of a textbook on mathematical physics published by Oxford University Press (2018) that has since been adopted and endorsed by several leading universities. The book is suitable for undergraduate studies in Newtonian dynamics and senior undergraduate and postgraduate studies in Lagrangian and Hamiltonian dynamics. The material is presented in an accessible manner for all audiences; physicists, mathematicians or other scientific backgrounds.