Dr Starkey completed his PhD in the application of artificial intelligence techniques to engineering problems from University of Aberdeen in 2001 and attained an Honours degree in Applied Mathematics from St Andrews University in 1993. Since then he has been awarded an Enterprise Fellowship from Royal Society of Edinburgh and Scottish Enterprise.
Dr Starkey's main research theme is in the intelligent application of data mining techniques in new problem areas. He has developed novel methods for automatically determining features of interest. These techniques have been successfully applied to a number of different fields, including econometrics (the study of financial markets), bioinformatics (in particular genomic and proteomic analysis), engineering problems and the analysis of seismic data.
He also forms part of a team that has developed the GRANIT system, a technology capable of the non-destructive testing of ground anchorages.
Current projects include:
- Investigating data mining methods applied to econometrics
- In silico identification of functional human cis-regulatory sequence-gene linkage (funded by BBSRC) joint project with Dr Alasdair MacKenzie and Scott Davidson
- a grant from the BBSRC Research Equipment Initiative for a computer rack system to facilitate the computations required for textual bioinformatic approaches
- Analysis of seismic data for automated recognition of geological features, joint project with Dr Anne Schwab
- “Design and assessment of condition of soil anchorages in a dynamic environment using the centrifuge modelling technique” funded by EPSRC, jointly with Drs Ivanovic and Neilson and Prof Rodger and also Prof Davies of University of Dundee
- Investigation into genomic prediction for melatonin action in animals, joint project with Dr David Hazlerigg
- “Pattern recognition approaches to understand replication origin specification”, joint project with Dr Anne Donaldson and Dr Conrad Nieduszynski
- Further Info
Dr Andrew Starkey is CEO of a recent spin-out company from the University of Aberdeen, BlueFlow Ltd.
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- Ezenkwu, CP & Starkey, A 2019, 'Unsupervised Temporospatial Neural Architecture for Sensorimotor Map Learning' IEEE Transactions on Cognitive and Developmental Systems. [Online] DOI: https://doi.org/10.1109/TCDS.2019.2934643
- Ezenkwu, CP & Starkey, A 2019, Machine Autonomy: Definition, Approaches, Challenges and Research Gaps. in K Arai, R Bhatia & S Kapoor (eds), Intelligent Computing: CompCom 2019, Proceedings. Advances in Intelligent Systems and Computing, Springer , Cham, pp. 335-358, Computing Conference 2019, London, United Kingdom, 16/07/19. [Online] DOI: https://doi.org/10.1007/978-3-030-22871-2_24
- Starkey, A & Ahmad, AU 2018, Semi-automated data classification with feature weighted self organizing map. in ICNC-FSKD 2017 - 13th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery. Institute of Electrical and Electronics Engineers Inc., pp. 136-141, 13th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery, ICNC-FSKD 2017, Guilin, Guangxi, China, 29/07/17. [Online] DOI: https://doi.org/10.1109/FSKD.2017.8392964
- Ahmad, AU & Starkey, A 2018, 'Application of feature selection methods for automated clustering analysis: a review on synthetic datasets' Neural Computing and Applications, vol. 29, no. 7, pp. 317-328. [Online] DOI: https://doi.org/10.1007/s00521-017-3005-9
- Starkey, A, Ahmad, AU & Hamdoun, H 2017, 'Automated Feature Identification and Classification Using Automated Feature Weighted Self Organizing Map (FWSOM)' IOP Conference Series: Materials Science and Engineering, vol. 261, no. 1, 012006, pp. 1-7. [Online] DOI: https://doi.org/10.1088/1757-899X/261/1/012006
- Abdul Aziz, A, Starkey, A & Campbell Bannerman, M 2017, Evaluating Cross Domain Sentiment Analysis using Supervised Machine Learning Techniques. in Intelligent Systems Conference 2017., 17652472 , IEEE Explore, London, SAI Intelligent Systems Conference 2017 (IntelliSys 2017), London, United Kingdom, 7/09/17. [Online] DOI: https://doi.org/10.1109/IntelliSys.2017.8324369
- Walker, AD, Alexopoulos, P, Starkey, A, Pan, JZ, Gómez-Pérez, JM & Siddharthan, A 2016, Answer type identification for question answering: Supervised learning of dependency graph patterns from natural language questions. in G Qi, K Kozaki, JZ Pan & S Yu (eds), Semantic Technology: 5th Joint International Conference, JIST 2015, Yichang, China, November 11-13, 2015, Revised Selected Papers. vol. 9544, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 9544, Springer-Verlag, pp. 235-251, 5th Joint International Conference on Semantic Technology, JIST 2015, Yichang, China, 11/11/15. [Online] DOI: https://doi.org/10.1007/978-3-319-31676-5_17
- Ahmad, AU & Starkey, A 2016, Comparison of methods for automated feature selection using a Self-Organising Map. in C Jayne & L Iliadis (eds), Engineering Applications of Neural Networks: 17th International Conference, EANN 2016, Aberdeen, UK, September 2-5, 2016, Proceedings. vol. CCIS 269, Communications in Computer and Information Science, vol. 629, Springer-Verlag, pp. 134-146. [Online] DOI: https://doi.org/10.1007/978-3-319-44188-7_10
- El-Hussein, S, Harrigan, JJ & Starkey, A 2015, 'Finite element simulation of guided waves in pipelines for long range monitoring against third party attacks' Journal of Physics: Conference Series, vol. 628, no. 1, 012039. [Online] DOI: https://doi.org/10.1088/1742-6596/628/1/012039
- Walker, A, Starkey, A, Pan, JZ & Siddharthan, A 2014, Making test corpora for question answering more representative. in E Kanoulas, M Lupu, P Clough, M Sanderson, M Hall, A Hanbury & E Toms (eds), Information Access Evaluation. Multilinguality, Multimodality, and Interaction : CLEF 2014. . Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 8685 LNCS, Springer-Verlag, pp. 1-6, 5th International Conference of the CLEF Initiative, CLEF 2014, Sheffield, United Kingdom, 15/09/14. [Online] DOI: https://doi.org/10.1007/978-3-319-11382-1_1