keithmalcolmsmith.com, theory of biological networks, University of Edinburgh

Welcome

I am a Lecturer in the Department of Computer and Information Sciences, University of Strathclyde, where I am part of the Digital Health and Wellness Group. Previously I was lecturer for a couple of years at the Department of Physics and Mathematics, Nottingham Trent University, and UKRI Innovations Fellow in Medical Informatics at the Usher Institute, University of Edinburgh & Health Data Research UK. My PhD was in biomedical signal processing at IDCOM, University of Edinburgh.

My work focuses on the development and application of computational tools for the analysis of biomedical data, particularly for neuroimaging data of human brain structure and function, but also for other biological networks, like protein interaction networks and metabolic networks.

I most enjoy:

working on interdisciplinary problems with a wide range of experts
exploring creative ways for analysing data
coming up with experiments to provide novel insights into problems
statistical solutions for assessing significance of biomedical results

My main research interests to date include:

Hierarchical complexity of human brain structural and functional connectivity and its relevance in brain development and degeneration
Machine learning of brain MRI data for Major Depressive Disorder
Theory of biological networks
Theory and applications of signal processing for neuroimaging
Statistical complexity and generative models of networks

Selected Journal Publications/pre-prints:

Smith KM, Smith JP, Statistical Complexity of Heterogeneous Geometric Networks. https://arxiv.org/abs/2304.05484 (2023) [link]
Yeung HW, ..., Smith KM*, Whalley HC*, Classification Accuracy of Structural and Functional Connectomes across Different Depressive Phenotypes. Imaging Neuroscience, 10.1162/imag_a_00064 (2023) [link]
Yeung HW, ..., Smith KM*, Predicting Sex, Age, General Cognition, and Mental Health with Machine Learning on Brain Structural Connectomes. Human Brain Mapping, 44(5): 1913-1933 (2023) [link]
Klein B†, Holmer L, Smith KM†, Johnson MM, Swain A, Stolp L, Teufel AI, Kleppe AS†, Resilience and Evolvability of Protein-Protein Interaction Networks. Communications Biology, 4: 1352 (2021) [link]
Smith KM, Explaining the Emergence of Complex Networks through Log-Normal Fitness in a Euclidean Node Similarity Space. Scientific Reports, 11: 1976 (2021). [link]
Blesa M, Galdi P, ..., Smith KM*, Boardman JP*, Hierarchical Complexity of the Macro-scale Neonatal Brain. Cerebral Cortex, 31(4): 2071-2084 (2021). [link]
Smith KM, Bastin ME, Cox SR, Valdes-Hernandez M, Wiseman S, Escudero J, Sudlow C, Hierarchical Complexity of the Adult Human Structural Connectome. NeuroImage, 191: 205-215 (2019). [link]
Smith KM, Spyrou L, Escudero J, Graph-Variate Signal Analysis. IEEE Transactions on Signal Processing, 67(2): 293-305 (2019). [link]