Andrew is a theoretical physicist focusing on the use of mathematical and physical principles to answer important questions in biology and medicine. His PhD research focused on the intersection of string theory, particle physics and condensed matter physics, with a special emphasis on the use of D-branes to uncover novel dualities in low dimensional gauge theories. More recently, he has been focused on (i) translating risk models of COVID and sepsis into weighted knowledge graphs, (ii) developing novel distance metrics for unsupervised learning on medical patients and (iii) using topologically motivated algorithms for clustering and inference on multi-omics data.