Dr Allan Tucker
Honorary Research Associate
Department
Biodiversity Informatics and Spatial Analysis
Team
Specialism
Intelligent data analysis, machine learning, artificial intelligence, data-mining
I am interested in the use of AI modelling techniques to try and solve challenging real-world problems with a focus on biological, clinical and ecological big data. My PhD at Birkbeck College, entitled "The Automatic Explanation of Multivariate Time Series" was sponsored by the Engineering and Physical Sciences Research Council; Honeywell Hi-Spec Solutions, UK; and Honeywell HTC, USA. I lead the Intelligent Data Analysis group at Brunel University London with 40 members of academic and research staff. Previously I have worked in conjunction with Leiden University Medical School, UCL and Rothamsted Research on gene regulatory networks. My current projects include modelling diverse datasets at Kew including text mining approaches for extracting knowledge form digitised flora and XXXX. I also have projects analysing various clinical datasets from Moorfield’s Eye Hospital and the Royal Free Hospitals in London, as well as projects exploring the dynamics of fish populations in the Northern Atlantic and Baltic seas using Hidden Markov Models in conjunction with the Canadian Department of Fisheries and Oceans, DEFRA and the University of Helsinki. I have a number of advisory roles for the EU on biodiversity and with the MHRA on regulation of AI in the NHS.
- PhD, University of London, 2001
- BSc (Hons), University of Sheffield
Uusitalo, L., Tomczak, MT., Müller-Karulis, B., Putnis, I., Trifonova, N. & Tucker, A. (2018)
Hidden variables in a Dynamic Bayesian Network identify ecosystem level change.
Ecological Informatics, 45: 9 - 15.
Curtis, TY., Bo, V., Tucker, A. & Halford, NG. (2018)
Construction of a network describing asparagine metabolism in plants and its application to the identification of genes affecting asparagine metabolism in wheat under drought and nutritional stress.
Food and Energy Security, 7(1): e00126 - e00126.
Nicolson, N., Challis, K., Tucker, A. & Knapp, S. (2017)
Erratum to: Impact of e-publication changes in the International Code of Nomenclature for algae, fungi and plants (Melbourne Code, 2012) - did we need to “run for our lives”?.
BMC Evolutionary Biology, 17(1):156.
Nicolson, N. & Tucker, A. (2017)
Identifying Novel Features from Specimen Data for the Prediction of Valuable Collection Trips.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 235 - 246.
Kirkup, D. & Tucker, A. (2014)
Extracting Predictive Models from Marked-Up Free-Text Documents at The Royal Botanic Gardens, Kew, London.
Symposium on Intelligent Data Analysis. Brussels. 1 - 1 November. Lecture Notes in Computer Science 309 - 320.
Tucker, A. & Duplisea, D. (2012)
Bioinformatics tools in predictive ecology: Applications to fisheries.
Philosophical Transactions of the Royal Society: Part B, 367 (1586): 279 - 290.