Dr Michael Watts
Biography/ Background
I completed my PhD in computational intelligence in the Department of Information Science at the University of Otago in 2004. From 2004 to 2007 I was a post-doctoral fellow in the National Centre for Advanced Bioprotection Technologies (now the Bio-Protection Research Centre) at Lincoln University, New Zealand, where I developed intelligent methods for predicting the invasion and distribution of invasive insect crop pests. From 2007 to 2009 I was a post-doctoral fellow in the School of Biological Sciences at the University of Sydney, where I again applied intelligent methods to predicting the distribution of the Australian plague locust. I started work in the Global Ecology Lab here at Adelaide in January 2010.
Some links that are relevant to my background:
Social Media Links:
Qualifications
B.Sc. (Hons I), Information Science, University of Otago, 1996
Ph.D., Computational Intelligence, University of Otago, 2004
Teaching Interests
I have four years of experience teaching data processing and computational intelligence in the Department of Information Science at the University of Otago, New Zealand. Below are links to some of the lectures I presented for those courses.
Data Processing Course Lectures
These lectures were presented to the course INFO 233, Data
Processing (now Information Structure and Networks). Lectures are available as HTML, Open Document Format (ODP) presentations, Power Point (PPT) or as PDF (six slides per page).
Download all lectures in all formats: DP.zip (5.78 MB).
Computational Intelligence Lectures
These lectures were presented to the course INFO
331, Intelligent Information Systems. Lectures are
available as HTML, Open Office Impress (ODP) presentations, Power Point presentations, or as PDF
(six slides per page).
Download all lectures in all formats: IIS.zip (16.7 MB).
Research Interests
- Ecological modelling and informatics
- Artificial neural networks
- Evolving connectionist systems
- Applications of neural networks
- Evolutionary algorithms
- Knowledge discovery
- Intelligent methods for ecological informatics
Publications
Total refereed publications: 56
Other publications: 19
Total citations: 316
h-index: 8
List of publications over the last five years.
Book Chapters
Watts, M.J., Bianconi, A., Serapiao, A.B.S., Govone, J.S., and von Zuben, C.J. The Effectiveness of Artificial Neural Networks in Modelling the Nutritional Ecology of a Blowfly Species. In:
Ecological Modelling. W-J Zhang, ed. Novascience Press. (2011).
Watts,
M.J. Towards a formalisation of evolving connectionist systems. In: Artificial
Neural Networks. S.J. Kim, ed. Novascience Press. (2010).
Watts,
M.J. and Worner,
S.P. Modelling Insect Habitat Suitability with Artificial Neural
Networks. In:
Insect Habitats: Characteristics, Diversity and Management.
Edina L. Harris and Newell E. Davies, eds. Novascience Press. (2010).
Journal Articles
Lam, A.Y.S., Watts, M. J., Wu, D. and Estévez, P.A. IEEE CIS Social Media: Have you joined our online community? IEEE Computational Intelligence. (2012) 7(1) 4-5,79.
Bradshaw, C.J.A. , McMahon, C.R., Miller, P.S., Lacy, R.C., Verant, M.L., Pollak, J.P., Fordham, D.A., Watts, M.J., Prowse, T.A.A. and Brook, B.W. Dynamics of bovine tuberculosis in Australian swamp buffalo based on coupled epidemiological and demographic models. Journal of Applied Ecology (2012) 49(1) 268-277.
Fordham, D.A., Wigley, T.M.L., Watts, M.J., and Brook, B.W. Strengthening forecasts of climate change impacts with multi-model ensemble averaged projections using MAGICC/SCENGEN 5.3. Ecography (2012) 35 4-8. Citations: 1
Fordham, D.A., Akcakaya, H.R., Araujo, M.B; Elith, J., Keith, D., Pearson, R. G., Auld, T., Mellin, C., Morgan, J., Regan, T., Tozer, M., Watts, M.J., White, M., Wintle, B., Yates, C. and Brook, B.W. Plant extinction risk under climate change: are forecast range shifts alone a good indicator of species vulnerability to global warming? Global Change Biology, Accepted, 2011.
Bianconi, A., Govone, J.S., Manly, B.F.J. and Watts, M.J. The use of a multivariate statistical procedure in analysing the germination process of two bean cultivars, compared with a univariate approach. Proceedings of the International Academy of Ecology and Environmental Sciences (2011) 1(2) 70-76.
Watts, M.J. and Worner, S.P. Using artificial neural networks to predict the distribution of bacterialcrop diseases from biotic and abiotic factors. Computational Ecology and Software Accepted, 2011.
Watts, M.J. and Worner, S.P. Improving cluster-based methods for investigating potential for insect species establishment: region-specific risk factors. Computational Ecology and Software (2011) 1(2) 70-76. Citations: 1
Watts, M.J. , Li, Y., Russell, B.D., Mellin, C., Connell, S.D. and Fordham, D.A. A novel method for mapping reefs and subtidal rocky habitats using artificial neural networks. Ecological Modelling, (2011) 222(15) 2606-2614. Citations: 1
Pontin, D.R., Schliebs,S., Worner, S.P. and Watts, M.J. Finding relevant data in
noisy, complex ecological times series: a comparison of two feature
selection methods. Ecological Modelling. (2011) 222(10) 1657-1665. Citations: 1
Watts, M.J. Using data clustering as a method of estimating the risk of establishment of bacterial crop diseases. Computational Ecology and Software. (2011) 1(1) 1-13. Citations: 1
Watts, M.J. A decade of Kasabov's Evolving Connectionist Systems: A Review. IEEE Transactions on Systems, Man and Cybernetics Part C - Applications and Reviews (2009) 39(3) 253-269. Citations: 14
Watts, M.J., Worner, S.P., Estimating the risk of insect species invasion: Kohonen self-organising maps versus k-means clustering. In: Ecological Modelling (2009) 220(6) 821-829. Citations:8
Watts, M.J. and Worner, S.P. Comparing Ensemble and Cascaded Neural Networks that Combine Biotic and Abiotic Variables to Predict Insect Species Distribution. In: Ecological Informatics (2008) 3(6) 354-366. Citations: 7
Watts, M.J. and Worner, S.P. Using Artificial Neural Networks to Determine the Relative Contribution of Abiotic Factors Influencing the Establishment of Insect Pest Species. In: Ecological Informatics (2008) 3(1) 64-74. Citations: 7
Watts, M.J. and Worner, S.P. Comparison of a Self Organising Map and Simple Evolving Connectionist System for Predicting Insect Pest Establishment. In: International Journal of Information Technology. (2006) 12(6) 35-42. Citations:1
Full Refereed Conference Papers
Watts, M.J. and Worner, S.P. Predicting the Distribution of Fungal Crop Diseases from Abiotic and Biotic Factors using Multi-layer Perceptrons. In: Proceedings of ICONIP 2008, LNCS 5506 pg 899-906.
Pontin, D.R., Worner, S.P. and Watts, M.J. Using Time Lagged Input Data to Improve Prediction of Stinging Jellyfish Occurrence at New Zealand Beaches by Multi-Layer Perceptrons. In: Proceedings of ICONIP 2008, LNCS 5506 pg 907-914. Citations: 1
Worner S.P., Watts M.J., Pitt J.P.W. & Gevrey M. Being prepared: ecological informatics and computational intelligence methods applied to invasive insect risk assessment. International Congress of Entomology, 6-11 July, Durban, South Africa, 2008
Pontin, D.R., Watts, M.J. and Worner, S.P. Using Multi-Layer Perceptrons to Predict the Presence of Jellyfish of the Genus Physalia at New Zealand Beaches. International Joint Conference on Neural Networks 2008, Hong Kong, June 1-6, 2008. pg1171-1176
Worner, S.P. and Watts, M.J. Null Model Analysis of a Self Organising Map of Invasive Species Distributions. 5th International Conference on Ecological Informatics (ISEI5) Novel Computational Techniques for Improved Management, Understanding and Forecasting of Complex Ecological Data
December 4 - 6, 2006, Santa Barbara, CA, USA 2006.
Watts, M.J. and Worner, S.P. Null-model Validation of MLP Input Contribution Analysis in Ecology. 6th International Conference on Hybrid Intelligent Systems (HIS 06') and 4th Conference on Neuro-Computing and Evolving Intelligence (NCEI '06). 13-15 December, AUT Technology Park, Auckland, New Zealand
Worner, S.P., Watts, M and M. Gevrey. 2006. Bootstrapping a self organising map model to estimate the uncertainty in assemblages of alien invasive species. Proceedings Management of sustainability and ecological modelling. International Congress of Ecological Modelling, August 28 - September 1, Ube -Yamaguchi, Japan 2006. pg 206-207 (2006)
Watts, M.J. and Worner, S.P. Using MLP to Determine Abiotic Factors Influencing the Establishment of Insect Pest Species. In: Proceedings of 2006 International Joint Conference on Neural Networks (IJCNN 2006), Vancouver, Canada, pg 3506-3511 (2006)
Watts, M.J. Nominal-Scale Evolving Connectionist Systems. In: Proceedings of 2006 International Joint Conference on Neural Networks (IJCNN 2006), Vancouver, Canada, pg 4057-4061 (2006)
Technical Reports
Watts, M.J. and Worner, S.P. Further Sensitivity Analysis of Simple Evolving Connectionist Systems Applied to the Lincoln Aphid Data Set. Technical Report, Bio-Protection and Ecology, Lincoln University. ISBN 978-0-86476-177-5. February, 2007. Citations: 1
Watts, M.J. and Worner, S.P. Comparison of Multi-Layer Perceptrons and Simple Evolving Connectionist Systems over the Lincoln Aphid Data Set. Technical Report, Bio-Protection and Ecology, Lincoln University. ISBN 978-0-86476-175-9. February, 2007. Citations: 1
Watts, M.J. and Worner, S.P. Using Multi-Layer Perceptrons to Model the Lincoln Aphid Data Set. Technical Report, Bio-Protection and Ecology, Lincoln University. ISBN 978-0-86476-176-7. February, 2007.
Fairweather, J., Hunt, L., Rosin, C., Campbell, H., Benge, J. and Watts, M. Understanding kiwifruit management using causal mapping. Agriculture Research Group on Sustainability (ARGOS) Research Report 06/09. 2006. Citations: 8
Seminars
Artificial Neural Networks in Bio-Protection. Presented to School of Biological Sciences, University of Sydney, Australia, 14 September 2007.
Relational Databases in Bio-Protection and Ecology. Presented to Bio-Protection and Ecology Division, Lincoln University, New Zealand, 28 February 2007.
Determining Abiotic Factors Influencing Insect Pest Establishment using Artificial Neural Networks. Presented to Bio-Protection and Ecology Division, Lincoln University, 14 June 2006.
Evolving Connectionist Systems: A family of artificial neural networks. Presented to Bio-Protection and Ecology Division, Lincoln University, New Zealand, 11 May 2005.
Professional Associations
Institute of Electrical and Electronic Engineers (IEEE)
IEEE Computer society
IEEE Computational Intelligence Society
International Neural Network Society (INNS)
International Society of Ecological Modellers
Expertise for Media Contact
| Categories | Information technology |
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| Expertise | artificial intelligence;computational intelligence;evolutionary computation;artificial neural networks;ecological modelling |
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| Notes | Currently researching software models for the effects of climate change on species distributions. Previously have experience with intelligent computational techniques for modelling invasive insect pests and crop diseases. Blog on computational intelligence here: http://computational-intelligence.blogspot.com/ |
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| Mobile | 0426 830 097 |
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| After hours | 08 7073 1540 |
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Entry last updated: Wednesday, 14 Nov 2012
