Dr Keith Smith

Lecturer

Computer and Information Sciences

Contact

Personal statement

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

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Publications

A comprehensive hierarchical comparison of structural connectomes in Major Depressive Disorder cases v. controls in two large population samples
Thng Gladi, Shen Xueyi, Stolicyn Aleks, Adams Mark J, Yeung Hon Wah, Batziou Venia, Conole Eleanor L S, Buchanan Colin R, Lawrie Stephen M, Bastin Mark E, McIntosh Andrew M, Deary Ian J, Tucker-Drob Elliot M, Cox Simon R, Smith Keith M, Romaniuk Liana, Whalley Heather C
Psychological Medicine (2024)
https://doi.org/10.1017/S0033291724000643
Classification accuracy of structural and functional connectomes across different depressive phenotypes
Yeung Hon Wah, Stolicyn Aleks, Shen Xueyi, Adams Mark, Romaniuk Liana, Thng Gladi, Buchanan Colin R, Tucker-Drob Elliot M, Bastin Mark E, McIntosh Andrew M, Cox Simon R, Smith Keith M, Whalley Heather C
Imaging Neuroscience Vol 2, pp. 1-24 (2024)
https://doi.org/10.1162/imag_a_00064
Exploring the efficacy of a graph classification GNN in learning non-linear graph metrics
Maurya Shivam, Yeung Hon Wah, Smith Keith Malcolm
Complex Networks 2023 (2023)
Robust, high temporal-resolution EEG functional connectivity detects increased connectivity coinciding with P300 in visual short-term memory binding in both familial and sporadic prodromal Alzheimer’s Disease
Roy Om, Moshfeghi Yashar, Ibanez Agustin, Lopera Francisco, Parra Mario A, Smith Keith M
Complex Networks 2023 , pp. 679-682 (2023)
Predicting sex, age, general cognition and mental health with machine learning on brain structural connectomes
Yeung Hon Wah, Stolicyn Aleks, Buchanan Colin R, Tucker-Drob Elliot M, Bastin Mark E, Luz Saturnino, McIntosh Andrew M, Whalley Heather C, Cox Simon R, Smith Keith
Human Brain Mapping Vol 44, pp. 1913-1933 (2023)
https://doi.org/10.1002/hbm.26182
Functional alignments in brain connectivity networks
Clark Ruaridh A, Parra Mario A, Smith Keith, Escudero Javier, Ibañez Agustín, McGeown William J, Macdonald Malcolm
Complex Networks 2022 : The 11th International Conference on Complex Networks and their Applications (2022)

More publications

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Contact

Dr Keith Smith
Lecturer
Computer and Information Sciences

Email: keith.m.smith@strath.ac.uk
Tel: Unlisted