Dr Tony Bagnall
| Job Title | Contact | Location |
|---|---|---|
| Senior Lecturer |
Anthony dot Bagnall at uea dot ac dot uk
Tel: +44 (0)1603 59 3794 |
Environmental 2.23 |
Career
Tony joined CMP as a part time MRes student/part time teaching assistant in 1993 having finished his BSc in Mathematics and Statistics at the University of Hertfordshire. After completing his Masters by research in 1995 he began a PhD titled "Modelling the UK electricity market with autonomous adaptive agents". After a brief period as a research assistant on a data mining project sponsored by Master Foods and Centrica, in 1999 he completed his PhD and was appointed as a Lecturer in Statistics for Data Mining jointly in the schools of Computer Science and Mathematics. In 2003 statistics moved into CMP and since then Tony has been a full member of the school. In 2007 he was promoted to senior lecturer.
Tony has been involved in researching areas of optimization, machine learning, agent systems, statistics and data mining. Currently he is primarily focused on time series data mining. He is involved in several ongoing projects, links to which can be found below:
PhD Projects
The following opportunity exists to pursue a PhD with Dr. Bagnall on the project Data Mining Biomakers in Clinical Magnetic Resonance Imaging.
Research Projects
Predictive Modelling of Bone Ageing with Luke Davis
Time Series Data Mining Electricity Usage Patterns with Jason Lines
Time Series Data Mining with Clipped Series
Website
Key Research Interests
His main current research interest is in the design and evaluation of algorithms for time series data mining and the development of novel time series application areas.
Selected Publications:
Bull, L., Studley, M., Bagnall, A.J., and Whittley, I.M. Learning Classifier System Ensembles with Rule-Sharing. IEEE Transactions on Evolutionary Computation, Volume 11, Issue 4, Page(s) 496-502, 2007.
Bagnall, A. J., Ratanamahatan, C., Keogh, E., Lonardi, S. and Janacek, G. J. A Bit Level Representation for Time Series Data Mining with Shape Based Similarity. Data Mining and Knowledge Discovery Journal, Volume 13, Issue 1, Page(s) 11-40, 2006.
Bagnall, A. J. and Toft, I. E. Autonomous Adaptive Agents for Single Seller Sealed Bid Auctions. Journal of Autonomous Agents and Multi-Agent Systems, Volume 13, Issue 1, Page(s) 259-292, 2006.
Bagnall, A. J. and Smith, G. D. A Multi-Agent Model of the UK Market in Electricity Generation. IEEE Transactions on Evolutionary Computation, Volume 9, Issue 5, Page(s) 522-536, 2005.
List all publications by Dr Tony Bagnall (Eprints)
Past Research Projects and Grants
| Project Title | Start Date | End Date | Funding Body | Project Members |
|---|---|---|---|---|
| Time Series Data Mining | 1/11/2006 | 30/4/2008 | Lancaster University | N/A |
| MARS PROJECT | 1/10/2006 | 30/9/2008 | MARS | N/A |
| Super-computer data mining | 1/1/2005 | 31/3/2007 | EPSRC | N/A |
| CASE for new academic studentship | 1/10/2004 | 30/9/2007 | Effem Holdings Ltd | Tony Bagnall, Beatriz de la Iglesia |
| The development of an electronic auction database and data mining analysis tool | 29/4/2002 | 28/4/2004 | DTI - Knowledge Transfer Partnerships | Tony Bagnall, George Smith |
| The development of an electronic auction database and datamining analysis tool | 29/4/2002 | 28/5/2005 | Effem Holdings Ltd | Tony Bagnall, George Smith |
Teaching Interests
Tony currently teaches programming, data structures and algorithms and machine learning. Previously he has taught on numerous mathematics, statistics and computing courses.
CMPC2M11: Data Structures and Algorithms
CMPC2M07: Programming 2 (currently called Software Engineering I)
Article
Toms, AP, Farghal, A, Kasmai, B, Bagnall, A and Malcolm, PN (2011) Physiology of the small bowel: a new approach using {MRI} and proposal for a new metric of function. Medical Hypotheses, 76 (6). pp. 834-839.
Zatuchna, Z and Bagnall, A (2009) Learning Mazes with Aliasing States: An LCS Algorithm with Associative Perception. Adaptive Behavior, 17 (1). pp. 28-25. ISSN 1059-7123
Zatuchna, ZV and Bagnall, AJ (2009) A learning classifier system for mazes with aliasing clones. Natural Computing, 8 (1). pp. 57-99. ISSN 1567-7818
Bagnall, AJ, Cawley, GC, Bull, L, Whittley, IM, Studley, M, Pettipher, M and Tekiner, F (2007) Super Computer Heterogeneous Classifier Meta-Ensembles. International Journal of Data Warehousing and Mining (IJDWM), 3 (2). pp. 67-82. ISSN 1548-3924
Bull, L, Studley, M, Bagnall, AJ and Whittley, IM (2007) Learning Classifier System Ensembles With Rule-Sharing. IEEE Transactions on Evolutionary Computation, 11 (4). pp. 496-502. ISSN 1089-778X
Bagnall, AJ, Ratanamahatan, C, Keogh, E, Lonardi, S and Janacek, GJ (2006) A Bit Level Representation for Time Series Data Mining with Shape Based Similarity. Data Mining and Knowledge Discovery Journal, 13 (1). pp. 11-40. ISSN 1384-5810
Bagnall, AJ and Toft, IE (2006) Autonomous Adaptive Agents for Single Seller Sealed Bid Auctions. Journal of Autonomous Agents and Multi-Agent Systems, 12 (3). pp. 259-292. ISSN 1387-2532
Bagnall, AJ and Smith, GD (2005) A multiagent model of the UK market in electricity generation. IEEE Transactions on Evolutionary Computation, 9 (5). pp. 522-536. ISSN 1089-778X
Bagnall, AJ and Janacek, GJ (2005) Clustering time series with clipped data. Machine Learning, 58 (2). pp. 151-178. ISSN 0885-6125
Bagnall, AJ, Rayward-Smith, VJ and Whittley, IM (2001) The Next Release Problem. Information and Software Technology, 43 (14). pp. 883-890. ISSN 0950-5849
Book Section
Davis, L, Theobald, B-J, Toms, A and Bagnall, A (2011) On the Extraction and Classification of Hand Outlines. In: Proceedings onf the 12th International Conference on Intelligent Data Engineering and Automated Learning. Spring, pp. 92-99.
Lines, JA, Bagnall, AJ, Caiger-Smith, P and Anderson, S (2011) Classification of Household Devices by Electricity Usage Profiles. In: Proceedings of the 12th International Conference on Intelligent Data Engineering and Automated Learning. UNSPECIFIED, pp. 403-412.
Younsi, R and Bagnall, AJ (2010) A Randomized Sphere Cover Classifier. In: Proceedings of the 11th International Conference on Intelligent Data Engineering and Automated Learning. UNSPECIFIED.
Bagnall, A, Cawley, G, Whittley, I, Bull, L, Studley, M, Pettipher, M and Tekiner, F (2008) Super Computer Heterogeneous Classifier Meta-Ensembles. In: Data Warehousing and Mining: Concepts, Methodologies, Tools and Applications. IGI Global, pp. 1320-1333. ISBN 978-1599049519
Bagnall, AJ and Zatuchna, Z (2005) On the Classification of Maze Problems. In: Foundations of Learning Classifier Systems. Studies in Fuzziness and Soft Computing, 183 . Springer, pp. 307-316. ISBN 978-3-540-25073-9
Janacek, GJ, Bagnall, AJ and Powell, M (2005) A likelihood ratio distance measure for the similarity between the Fourier transform of time series. In: Advances in Knowledge Discovery and Data Mining. Lecture Notes in Computer Science, 3518 . Springer Berlin / Heidelberg, pp. 205-213.
Ratanamahatan, C, Keogh, E, Bagnall, AJ and Lonardi, S (2005) A Novel Bit Level Time Series Representation with Implication of Similarity Search and Clustering. In: Advances in Knowledge Discovery and Data Mining. Lecture Notes in Computer Science, 3518 . Springer Berlin / Heidelberg, pp. 51-65. ISBN 978-3-540-26076-9
Bagnall, AJ and Toft, IE (2004) An Agent Model for First Price and Second Price Private Value Auctions. In: Artificial Evolution. Lecture Notes in Computer Science, 2936 . Springer Berlin / Heidelberg, pp. 281-292. ISBN 978-3-540-21523-3
Gill, AA, Smith, GD and Bagnall, AJ (2004) Improving decision tree performance through induction and cluster-based stratified sampling. In: Intelligent Data Engineering and Automated Learning – IDEAL 2004. Lecture Notes in Computer Science, 3177 . Springer Verlag, Berlin, pp. 339-344. ISBN 978-3-540-22881-3
Bagnall, AJ and Smith, GD (2000) An adaptive agent model for generator company bidding in the UK power pool. In: Artificial Evolution. Lecture Notes in Computer Science, 1829 . Springer-Verlag, pp. 191-203. ISBN 978-3-540-67846-5
Monograph
Bagnall, A, Moxon, S and Studholme, D (2007) Time Series Data Mining Algorithms for Identifying Short RNA in Arabidopsis thaliana. Technical Report. University of East Anglia.
Bagnall, AJ, Janacek, GJ and Zhang, M (2003) Clustering Time Series from Mixture Polynomial Models with Discretised Data. Research Report. University of East Anglia.
Conference or Workshop Item
Bagnall, A, Moxon, S and Studholme, D (2008) Time Series Data Mining Algorithms for Identifying Short RNA in Arabidopsis thaliana. In: Proceedings of BIOCOMP 2008.
Bagnall, AJ, Whittley, IM, Janacek, GJ, Kemsley, K, Studley, M and Bull, L (2006) A Comparison of DWT/PAA and DFT for Time Series Classification. In: Proceedings of 2006 International Conference on Data Mining, June 26-29, 2006, Las Vegas, NV.
Bagnall, AJ, Whittley, IM, Studley, M, Pettipher, M, Tekiner, F and Bull, L (2006) Variance Stabilizing Regression Ensembles for Environmental Models. In: International Joint Conference on Neural Networks (IJCNN '06), Vancouver, BC.
Whittley, IM, Bagnall, AJ, Bull, L, Pettipher, M, Studley, M and Tekiner, F (2006) Attribute Selection Methods for Filtered Attribute Subspace based Bagging with Injected Randomness (FASBIR). In: Feature Selection for Data Mining Workshop, Part of the 2006 SIAM Conference on Data Mining, April 22, 2006, Bethesda, Maryland.
Zatuchna, Z and Bagnall, AJ (2006) Modelling of Temperament in an Associative Reinforcement Learning Agent. In: Symposium on Associative Learning and Reinforcement Learning at Adaptation in Artificial and Biological Systems (AISB'06).
Zatuchna, Z and Bagnall, AJ (2006) A Reinforcement Learning Agent with Associative Perception. In: Symposium on Associative Learning and Reinforcement Learning at Adaptation in Artificial and Biological Systems (AISB'06).
Bull, L, Studley, M, Bagnall, AJ and Whittley, IM (2005) On the use of rule-sharing in learning classifier system ensembles. In: Proceedings of the 2005 Congress on Evolutionary Computation, 5 Sept 2005, Edinburgh, Scotland.
Zatuchna, Z and Bagnall, AJ (2005) AgentP classifier system: self-adjusting vs. gradual approach. In: The 2005 IEEE Congress on Evolutionary Computation, 2-5 Sept. 2005.
Bagnall, AJ and Janacek, GJ (2004) Clustering time series from ARMA models with clipped data. In: KDD '04 Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining, 22-25 August 2004, Seattle, WA, USA.
Bagnall, AJ and Toft, IE (2004) Zero Intelligence Plus and Gjerstad-Dickhaut Agents for Sealed Bid Auctions. In: Workshop on Trading Agent Design and Analysis, part of the Third International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS 2004), July 20, 2004, Columbia University, New York, NY.
de la Iglesia, B, Philpott, MS, Bagnall, AJ and Rayward-Smith, VJ (2003) Data Mining Rules Using Multi-Objective Evolutionary Algorithms. In: Proceedings of 2003 IEEE Congress on Evolutionary Computation, 8-12 December 2003, Canberra, Australia.
Bagnall, AJ and Cawley, GC (2003) Learning classifier systems for data mining: a comparison of XCS with other classifiers for the Forest Cover data set. In: Proceedings of the IEEE/INNS International Joint Conference on Artificial Neural Networks (IJCNN-2003), 20-24 July 2003, Portland, OR.
Bagnall, AJ, Janacek, GJ, de la Iglesia, B and Zhang, M (2003) Clustering Time Series from Mixture Polynomial Models with Discretised Data. In: Proceedings of the second Australasian Data Mining Workshop.
Bagnall, AJ and Smith, GD (2000) Game playing with autonomous adaptive agents in a simplified economic model of the UK market in electricity generation. In: Proceedings of IEEE-PES / CSEE International conference on power system technology (Powercon 2000), 4-7 Dec 2000, Perth, WA, Australia .
Bagnall, AJ (2000) A Multi-Adaptive Agent Model for Generator Company Bidding in the UK Market in Electricity. In: Genetic and Evolutionary Computation Conference (GECCO-2000), July 8-12, 2000, Las Vegas, Nevada, USA.
Thesis
Bagnall, AJ (2000) Modelling the UK market in electricity generation with autonomous adaptive agents. Doctoral thesis, University of East Anglia.
Key Responsibilities
Deputy Director PgR
