Who am I and what am I doing here? Allan Tucker A brief introduction to my research www.brunel.ac.uk\~cssrajt.

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Presentation transcript:

Who am I and what am I doing here? Allan Tucker A brief introduction to my research

Outline of talk My background My current research and collaborations A sample of results and publications Plan of future research and funding Conclusions

A bit of background BSc Cognitive Science: University of Sheffield, 1996 PhD Computer Science: University of London, 2001 Post doctorate research: Brunel University,

IDA group at Brunel Headed by Professor Liu Bioinformatics, Genomics, and Medical Informatics Data Mining and Intelligent Systems Dynamic Systems and Signal Processing Graphics, Images and Visualisation Multivariate Time Series and Statistical Analysis

Areas of interest Bayesian networks Automatic explanation of data Multivariate time series Classification Optimisation

Collaborations Moorfield’s eye hospital Visual field understanding and classification UCL, Department of virology Gene expression data Royal Holloway Optimisation Brunel University Within IDA Software engineering

One slide tutorial on Bayesian networks Graph structure Local probability distributions Combine expert knowledge and data (but little research on this)

Some results Spatio-temporal models of visual fields Artificial intelligence in medicine, 2004

Some results (continued) Predicting Glaucoma

Some results (continued) Explanation Intelligent Data Analysis, 2002 & 2004

Some results (continued) Combining expert knowledge and data to identify relevant genes Bioinformatics, under review

Journal Publications Tucker, A. Crampton, J. Swift, S. “RGFGA: An Efficient Representation and Crossover for Grouping Genetic Algorithms” Evolutionary Computation, Provisionally Accepted. Tucker, A. Vinciotti, V. Liu, X. Garway-Heath, D. “A Spatio-Temporal Bayesian Network Classifier for Understanding Visual Field Deterioration”, Artificial Intelligence in Medicine, Elsevier, In Press. Swift, S. Tucker, A. Liu, X. Martin, N. Orengo, C. Kellam, P. “Consensus Clustering and Functional Interpretation of Gene Expression Data”, Genome Biology, In Press. Tucker, A. Vinciotti, V. Liu, X. “The Robust Selection of Predictive Genes Via a Simple Classier”, Submitted to Bioinformatics. Tucker, A and Liu, X “A Bayesian Network Approach to Explaining Time Series with Changing Structure”, Intelligent Data Analysis – An International Journal, In Press. Kellam, P. Liu, X. Martin, N. Orengo, C. Swift, S. Tucker, A. “A Framework for Modelling Virus Gene Expression Data”, Intelligent Data Analysis, Counsell, S. Liu, X. Mcfall, J. Swift, S. Tucker, A “Using Evolutionary Computation for Clustering Data”, Intelligent Data Analysis, Tucker, A. Liu, X. Ogden-Swift, A. “Evolutionary learning of dynamic probabilistic models with large time lags”, International Journal of Intelligent Systems, Swift, S. Tucker, A. Martin, N. Liu X. “Grouping Multivariate Time Series Variables: Applications to Chemical process and Visual Field Data”, Knowledge Based Systems, Tucker, A. Swift, S. Liu, X. “Grouping Multivariate Time Series via Correlation”, IEEE Transactions on Systems, Man, and Cybernetics. Part B: Cybernetics, 2001.

Recent Conference Publications Vinciotti, V. Tucker, A. Liu, X. Panteris, E. Kellam, P. “Identifying genes with high confidence from small samples”, Workshop on Data Mining in Functional Genomics, at the European Conference in Artificial Intelligence ECAI Sheng, W. Tucker, A. Liu, X. “Clustering with Niching Genetic K-means Algorithm”, GECCO Tucker, A. Vinciotti, V. Liu, X. Garway-Heath, D. “Bayesian Networks to Classify Visual Field Data”, The Association for Research in Vision and Ophthalmology Annual Conference, ARVO Tucker, A. Garway-Heath, D. Liu, X. “Bayesian Classification and Forecasting of Visual Field Deterioration”, Proceedings of IDAMAP Counsell, S., Liu, X., Najjar, R., Swift, S., Tucker, A., “Applying Intelligent Data Analysis to Coupling Relationships in Object-oriented Software”, IDA Tucker, A. Liu, X. “Learning Dynamic Bayesian Networks from Multivariate Time Series with Changing Dependencies”, IDA Tucker, A. Garway-Heath, D. Liu, X. “Spatial Operators for Evolving Dynamic Probabilistic Networks from Spatio-Temporal Data”, GECCO Counsell, S. Liu, X. McFall, J. Swift, S. and Tucker, A. “Optimising the Grouping of Users to Serves Using Intelligent Data Analysis”, ICEIS Kellam, P. Liu, X. Martin, N. Orengo, C. Swift, S. Tucker, A. “A Framework for Modelling Short, High-Dimensional Multivariate Time Series: Preliminary Results in Virus Gene Expression Data Analysis”, IDA Tucker, A. Swift, S. Martin, N. Liu X. “Grouping Multivariate Time Series Variables: Applications to Chemical process and Visual Field Data”, ES 2000.

Future directions Continue existing research collaborations Bioinformatics – HIV data, Gene identification Software Engineering – Analysis of code Optimisation – adaptive parameters, representations Recently secured funding from Zeis Meditech in conjunction with Moorfield’s to generate substantial data on visual fields and retinal images EPSRC first grant Optimisation with adaptive parameters BBSRC new investigation scheme Combining databases (GO ENSEMBL) into coherent models of the human genome EPSRC advanced fellowship?

Summary Record of working within Brunel over 4 years Multiple projects and collaborations with a number of institutions Good publication record including several “grade A” journals Keen to build upon my research record

Thanks for listening Any questions?

Some results Clustering (MTS and Consensus) IEEE System Man & Cybernetics, 2001 Genome Biology, 2004

Some results (continued) Efficient representations for GAs International Journal of Intelligent Systems, 2001 Evolutionary computation, provisionally accepted