Article
Multiscale matrix pencils for separable reconstruction problems
Cuyt A & Lee W (2024) Multiscale matrix pencils for separable reconstruction problems. Numerical Algorithms, 95, pp. 31-72. https://doi.org/10.1007/s11075-023-01564-3
Lecturer in Mathematics, Computing Science
Lecturer in A.I/Data Science, Computing Science
Professor Matt-Mouley Bouamrane
Professor in Health/Social Informatics, Computing Science
Lecturer, Computing Science
Lecturer in Computing Science, Computing Science
Tutor, Computing Science
Honorary Professor, Computing Science
Emeritus Professor, Computing Science
Emeritus Professor, Mathematics
Lecturer, Computing Science
Tutor, Computing Science and Mathematics - Division
Teaching Fellow, Mathematics
Research Fellow, Computing Science
Senior Lecturer, Computing Science
Senior Lecturer, Computing Science
Lecturer, Computing Science
Operations Officer
Senior Technical Specialist IT
Lecturer, Computing Science
Chair in Food Security & Sustainability, Mathematics
Article
Multiscale matrix pencils for separable reconstruction problems
Cuyt A & Lee W (2024) Multiscale matrix pencils for separable reconstruction problems. Numerical Algorithms, 95, pp. 31-72. https://doi.org/10.1007/s11075-023-01564-3
Book Chapter
Meiklem R, Bouamrane M, Kingsmore D, Stevenson K, Dunlop M & Thomson P (2024) Patient-Centred, Technology-Based Interventions for High Treatment Burden: An Overview of the State of the Art. In: Bichel-Findlay J, Otero P, Scott P & Huesing E (eds.) MEDINFO 2023 — The Future Is Accessible. Vol 310 ed. Studies in Health Technology and Informatics, Volume 310: MEDINFO 2023 — The Future Is Accessible. Proceedings of the 19th World Congress on Medical and Health Informatics: IOS Press, pp. 529 - 533. https://doi.org/10.3233/shti231021
Book Chapter
Lapp L, Bouamrane M, Roper M, Kavanagh K & Schraag S (2024) Decision Support in Cardiac Surgery: Early Exploration of Requirements with Cardiac Anesthetists and Surgeons. In: Digital Health and Informatics Innovations for Sustainable Health Care Systems. Studies in Health Technology and Informatics, Volume 316. IOS Press, pp. 1827 - 1831. https://doi.org/10.3233/shti240786
An FPGA-based neuromorphic vision system accelerator
Ali T, Rainey J, Lau SY, Gheorghiu E, Maier P, Appiah K & Bhowmick D (2024) An FPGA-based neuromorphic vision system accelerator. In: Bouma H, Prabhu R, Yitzhaky Y & Kuijf HJ (eds.) volume 13206. SPIE "Artificial Intelligence for Security and Defence Applications II, Edinburgh, 16.09.2024-20.09.2024. SPIE. https://doi.org/10.1117/12.3034095
Article
Ahmed FA, Yousef M, Ahmed MA, Ali HO, Mahboob A, Ali H, Shah Z, Aboumarzouk O, Al Ansari A & Balakrishnan S (2024) Deep learning for surgical instrument recognition and segmentation in robotic-assisted surgeries: a systematic review. Artificial Intelligence Review, 58 (1). https://doi.org/10.1007/s10462-024-10979-w
Combined Depth and Semantic Segmentation from Synthetic Data and a W-Net Architecture
Swingler K, Rumble T, Goutcher R, Hibbard P, Donoghue M & Harvey D (2024) Combined Depth and Semantic Segmentation from Synthetic Data and a W-Net Architecture. In: volume 1. 16th International Conference on Neural Computation Theory and Applications, Porto, Portugal, 20.11.2024-22.11.2024. SCITEPRESS - Science and Technology Publications, pp. 413-422. https://doi.org/10.5220/0012877500003837
Article
Semantically-Informed Graph Neural Networks for Irony Detection in Turkish
Bolucu N & Can Buglalilar B (2024) Semantically-Informed Graph Neural Networks for Irony Detection in Turkish. ACM Transactions on Asian and Low-Resource Language Information Processing (TALLIP).
Presentation / Talk
Predicting the impact of climate change on tick populations- a dynamic GIS approach
Norman R (2024) Predicting the impact of climate change on tick populations- a dynamic GIS approach. Royal Society Publishing Systems Biology Seminars, 01.11.2024. https://doi.org/10.52843/cassyni.dw8w3r
Article
McLean KA, Sgrò A, Brown LR, Buijs LF, Mozolowski K, Daines L, Cresswell K, Potter MA, Bouamrane M & Harrison EM (2024) Implementation of digital remote postoperative monitoring in routine practice: a qualitative study of barriers and facilitators. BMC Medical Informatics and Decision Making, 24 (1), p. 14. https://bmcmedinformdecismak.biomedcentral.com/articles/10.1186/s12911-024-02670-5; https://doi.org/10.1186/s12911-024-02670-5
Article
COVID-19 in Scottish care homes: A metapopulation model of spread among residents and staff
Baister M, McTaggart E, McMenemy P, Megiddo I & Kleczkowski A (2024) COVID-19 in Scottish care homes: A metapopulation model of spread among residents and staff. Epidemics, 48, Art. No.: 100781. https://www.sciencedirect.com/science/article/pii/S1755436524000422; https://doi.org/10.1016/j.epidem.2024.100781
Article
Worton AJ, Norman RA, Gilbert L & Porter RB (2024) GIS-ODE: linking dynamic population models with GIS to predict pathogen vector abundance across a country under climate change scenarios. Journal of the Royal Society Interface, 21 (217). https://doi.org/10.1098/rsif.2024.0004
Article
Blayney MC, Reed MJ, Masterson JA, Anand A, Bouamrane MM, Fleuriot J, Luz S, Lyall MJ, Mercer S, Mills NL, Shenkin SD, Walsh TS, Wild SH, Wu H & McLachlan S (2024) Multimorbidity and adverse outcomes following emergency department attendance: population based cohort study. BMJ Medicine, 3, Art. No.: e000731. https://doi.org/10.1136/bmjmed-2023-000731
Conference Abstract
McLean K, Sgrò A, Brown L, Buijs L, Potter M, Bouamrane MM & Harrison E (2024) Reducing the Burden to Deliver Remote Postoperative Surveillance Using Machine Learning for Surgical-Site Infection (SSI). British Journal of Surgery, 111 (Supplement_6), Art. No.: znae163.012. https://doi.org/10.1093/bjs/znae163.012
Edited Proceedings
ISSAC '24: Proceedings of the 2024 International Symposium on Symbolic and Algebraic Computation
Hauenstein J, Lee W & Chen S (eds.) (2024) ISSAC '24: Proceedings of the 2024 International Symposium on Symbolic and Algebraic Computation. The 2024 International Symposium on Symbolic and Algebraic Computation, Raleigh NC USA, 16.07.2024-19.07.2024. Association for Computing Machinery. https://dl.acm.org/
Conference Paper (published)
A Bi-Level Approach to Vehicle Fleet Reduction: Successful Case Study in Community Healthcare
Brownlee AEI, Thomson SL & Oladapo R (2024) A Bi-Level Approach to Vehicle Fleet Reduction: Successful Case Study in Community Healthcare. In: Genetic and Evolutionary Computation Conference 2024, Melbourne, Australia, 14.07.2024-18.07.2024. GECCO '24: ACM. https://doi.org/10.1145/3638530.3664137
Gu Y & Wei H (2024) Uncertainty-Informed Model Selection Method for Nonlinear System Identification and Interpretable Machine Learning. In: Proceedings of 2024 32nd Mediterranean Conference on Control and Automation (MED). 2024 32nd Mediterranean Conference on Control and Automation (MED), Chania - Crete, Greece, 11.06.2024-14.06.2024. IEEE, pp. 909-914. https://doi.org/10.1109/med61351.2024.10566184
Article
Watkinson M & Brownlee AEI (2024) Comparing apples and oranges? Investigating the consistency of CPU and memory profiler results across multiple java versions. Automated Software Engineering, 31, Art. No.: 28. https://doi.org/10.1007/s10515-024-00423-2
Book Chapter
Introduction To Global Aquatic Food Security
Norman R & Crumlish M (2024) Introduction To Global Aquatic Food Security. In: Crumlish M & Norman R (eds.) Aquatic Food Security. 1 ed. Essex: 5M publishing. https://5mbooks.com/product/aquatic-food-security
Book Chapter
The role of intensification in global aquaculture production
Norman R & Subasinghe R (2024) The role of intensification in global aquaculture production. In: Crumlish M & Norman R (eds.) Aquatic Food Security. Essex: 5M Books. https://5mbooks.com/product/aquatic-food-security
PRISMA reporting guideline and standards for qualitative evidence synthesis
PI: Professor Emma France
Funded by: Medical Research Council
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EXPOWER: EXPOnential Analysis EmPOWERing Innovation
PI: Dr Wen-shin Lee
Funded by: European Commission (Horizon 2020)
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Multimodal data analysis for monitoring invasive aquatic weeds in India
PI: Dr Savi Maharaj
Funded by: Royal Academy of Engineering
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Integrated risk mapping and targetted snail control to support schistosomiasis elimination in Brazil and Cote d'Ivoire under future climate change
PI: Professor Rachel Norman
Funded by: Natural Environment Research Council
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Advancing exponential analysis: high-resolution information from sparse and regularly sampled data
PI: Dr Wen-shin Lee
Funded by: The Carnegie Trust
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EmFi - Emergency Finance
PI:
Funded by: Algorand Foundation
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Scottish Mathematical Sciences Training Centre New Module Development
PI: Dr Anna Kirpichnikova
Funded by: Scottish Mathematical Sciences Training Centre
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Developing a Theoretical understanding of non linearities in the food system and practical ideas to take advantage of them
PI: Professor Rachel Norman
Funded by: The Leverhulme Trust
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Curriculum Development for Sustainable Seafood and Nutrition Security
PI: Professor Amaya Albalat
Funded by: European Commission (Horizon 2020)
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Women in Mathematics Day
PI: Dr Anna Kirpichnikova
Funded by: London Mathematical Society
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AirOpt - optimisation of airspace to save 2MT CO2 a year
PI: Dr Sandy Brownlee
Funded by: Innovate UK
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Gender Imbalance in Digital Technology
PI:
Funded by: Skills Development Scotland Co Ltd
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Innovation Voucher: Huli Route Matching
PI: Dr Sandy Brownlee
Funded by: Scottish Funding Council
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How blockchain-based digitization of land records can boost financial inclusion in Bangladesh
PI:
Funded by: Innovate UK
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Future Payment Systems: Data, Technology and Privacy after Covid.
PI:
Funded by: Engineering and Physical Sciences Research Council
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Innovation Voucher: Mindstream connect
PI: Dr Sandy Brownlee
Funded by: Scottish Funding Council
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INtelligent FOod Recognition and Monitoring for patient wellbeing
PI:
Funded by: Falcon Foodservice Equipment
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Know Your Numbers Business and Personal Wealth Planner
PI: Dr Sandy Brownlee
Funded by: Scottish Funding Council
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Airspace Optimisation Tool
PI: Dr Sandy Brownlee
Funded by: Scottish Funding Council
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Towards grammar-aware operators for automatic improvement of software
PI: Dr Sandy Brownlee
Funded by: The Carnegie Trust
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