Dr Ian Wood
Lecturer
School of Mathematics and Physics
+61 7 336 56139
Researcher biography
Dr. Ian Wood's research interests are in classification, bioinformatics, stochastic optimisation, machine learning and mixture models.
He received his PhD from the University of Queensland in 2004.
Journal Articles
Feraud, Mathieu, O’Brien, Jake W., Samanipour, Saer, Dewapriya, Pradeep, van Herwerden, Denice, Kaserzon, Sarit, Wood, Ian, Rauert, Cassandra and Thomas, Kevin V. (2023). InSpectra – A Platform for Identifying Emerging Chemical Threats. Journal of Hazardous Materials, 455 131486, 1-15. doi: 10.1016/j.jhazmat.2023.131486
Zheng, Chaowen, Huang, Jingfang, Wood, Ian A. and Wu, Yichao (2022). A modified expectation-maximization algorithm for latent Gaussian graphical model. Canadian Journal of Statistics, 50 (2), 612-637. doi: 10.1002/cjs.11643
Bassett, John J., Robitaille, Mélanie, Peters, Amelia A., Bong, Alice H. L., Taing, Meng‐Wong, Wood, Ian A., Sadras, Francisco, Roberts‐Thomson, Sarah J. and Monteith, Gregory R. (2022). ORAI1 regulates sustained cytosolic free calcium fluctuations during breast cancer cell apoptosis and apoptotic resistance via a STIM1 independent pathway. The FASEB Journal, 36 (1) e22108, e22108. doi: 10.1096/fj.202002031rr
Saleem, Sobia, Gallagher, Marcus and Wood, Ian (2018). Direct feature evaluation in black-box optimization using problem transformations. Evolutionary Computation, 27 (1), 75-98. doi: 10.1162/evco_a_00247
Nguyen, Hien D. and Wood, Ian A. (2016). Asymptotic normality of the maximum pseudolikelihood estimator for fully visible boltzmann machines. IEEE Transactions on Neural Networks and Learning Systems, 27 (4) 7103361, 897-902. doi: 10.1109/TNNLS.2015.2425898
Nguyen, Hien D. and Wood, Ian A. (2016). A block successive lower-bound maximization algorithm for the maximum pseudo-likelihood estimation of fully visible Boltzmann machines. Neural Computation, 28 (3), 485-492. doi: 10.1162/NECO_a_00813
Nguyen, Hien D., McLachlan, Geoffrey J. and Wood, Ian A. (2016). Mixtures of spatial spline regressions for clustering and classification. Computational Statistics and Data Analysis, 93, 76-85. doi: 10.1016/j.csda.2014.01.011
Ahfock, Daniel, Wood, Ian, Stephen, Stuart, Cavanagh, Colin R. and Huang, B. Emma (2014). Characterizing Uncertainty in High-Density Maps from Multiparental Populations. Genetics, 198 (1), 117-128. doi: 10.1534/genetics.114.167577
Janbon, Guilhem, Ormerod, Kate L., Paulet, Damien, Byrnes III, Edmond J., Yadav, Vikas, Chatterjee, Gautam, Mullapudi, Nandita, Hon, Chung-Chau, Billmyre, R. Blake, Brunel, François, Bahn, Yong-Sun, Chen, Weidong, Chen, Yuan, Chow, Eve W. L., Coppée, Jean-Yves, Floyd-Averette, Anna, Gaillardin, Claude, Gerik, Kimberly J., Goldberg, Jonathan, Gonzalez-Hilarion, Sara, Gujja, Sharvari, Hamlin, Joyce L., Hsueh, Yen-Ping, Ianiri, Giuseppe, Jones, Steven, Kodira, Chinnappa D., Kozubowski, Lukasz, Lam, Woei, Marra, Marco ... Dietrich, Fred S. (2014). Analysis of the genome and transcriptome of Cryptococcus neoformans var. grubii reveals complex RNA expression and microevolution leading to virulence attenuation. PLoS Genetics, 10 (4) e1004261, e1004261.1-e1004261.26. doi: 10.1371/journal.pgen.1004261
Gollapalli, Mohammed, Li, Xue and Wood, Ian (2013). Automated discovery of multi-faceted ontologies for accurate query answering and future semantic reasoning. Data and Knowledge Engineering, 87, 405-424. doi: 10.1016/j.datak.2013.05.005
Nguyen, Hien D., Wood, Ian and Hill, Michelle M. (2012). A robust permutation test for quantitative SILAC proteomics experiments. Journal of Integrated OMICS, 2 (2), 80-93. doi: 10.5584/jiomics.v2i2.109
Gao, Bo and Wood, Ian (2012). TAM-EDA: multivariate t distribution, archive and mutation based estimation of distribution algorithm. ANZIAM Journal, 54 (SUPPL), C720-C746. doi: 10.0000/anziamj.v54i0.6365
Grace, Adam W. and Wood, Ian A. (2012). Approximating the tail of the Anderson–Darling distribution. Computational Statistics and Data Analysis, 56 (12), 4301-4311. doi: 10.1016/j.csda.2012.04.002
Chow, Eve W. L., Morrow, Carl A., Djordjevic, Julianne T., Wood, Ian A. and Fraser, James A. (2012). Microevolution of Cryptococcus neoformans driven by massive tandem gene amplification. Molecular Biology and Evolution, 29 (8), 1987-2000. doi: 10.1093/molbev/mss066
Rathnayake, Suren I., Wood, Ian A., Abeyratne, Udantha R. and Hukins, Craig (2010). Nonlinear features for single-channel diagnosis of sleep-disordered breathing diseases. IEEE Transactions on Biomedical Engineering, 57 (8) 5424006, 1973-1981. doi: 10.1109/TBME.2010.2044175
Oldmeadow, Chris, Wood, Ian, Mengersen, Kerrie, Visscher, Peter M., Martin, Nicholas G. and Duffy, David L. (2008). Investigation of the relationship between smoking and appendicitis in Australian twins. Annals of Epidemiology, 18 (8), 631-636. doi: 10.1016/j.annepidem.2008.04.004
Zhu, J. X., McLachlan, G. J., Jones, L. B. T. and Wood, I. A. (2008). On selection biases with prediction rules formed from gene expression data. Journal of Statistical Planning and Inference, 138 (2), 374-386. doi: 10.1016/j.jspi.2007.06.003
Wood, I. A., Visscher, P. M. and Mengersen, K. L. (2007). Classification based upon gene expression data: bias and precision of error rates. Bioinformatics, 23 (11), 1363-1370. doi: 10.1093/bioinformatics/btm117
Wood, Ian A., Moser, Gerhard, Burrell, Daniel L., Mengersen, Kerrie L. and Hetzel, D. Jay S. (2006). A meta-analytic assessment of the Thyroglobulin marker for marbling in beef cattle. Genetics Selection Evolution, 38 (5), 479-494. doi: 10.1051/gse:2006016
Gallagher, Marcus, Downs, Tom and Wood, Ian (2002). Empirical evidence for ultrametric structure in multi-layer perceptron error surfaces. Neural Processing Letters, 16 (2), 177-186. doi: 10.1023/A:1019956303894
Conference Papers
Van Ryt, Saskia, Gallagher, Marcus and Wood, Ian (2020). A novel mutation operator for variable length algorithms. AI 2020: Advances in Artificial Intelligence: 33rd Australasian Joint Conference, Canberra, ACT, Australia, 29 - 30 November 2020. Heidelberg, Germany: Springer. doi: 10.1007/978-3-030-64984-5_14
Saleem, Sobia, Gallagher, Marcus and Wood, Ian (2018). A model-based framework for black-box problem comparison using gaussian processes. 15th International Conference on Parallel Problem Solving from Nature, PPSN 2018, Coimbra, Portugal, 8-12 September 2018. Cham, Switzerland: Springer Verlag. doi: 10.1007/978-3-319-99259-4_23
Bogomolov, T., Filar, J. A., Luscombe, R., Nazarathy, Y., Qin, S., Swierkowski, P. and Wood, I. (2017). Size does matter: A simulation study of hospital size and operational efficiency. 22nd International Congress on Modelling and Simulation, Hobart, TAS Australia, 3 - 8 December 2017. Modelling and Simulation Society of Australia and New Zealand Inc. (MSSANZ).
Chan, Amy, Wood, Ian A. and Fripp, Jurgen (2016). Maximum pseudolikelihood estimation for mixture-Markov random field segmentation of the brain. International Conference on Digital Image Computing - Techniques and Applications (DICTA), Gold Coast, Australia, 30 November-2 December 2016. Piscataway, NJ, United States: IEEE. doi: 10.1109/DICTA.2016.7797062
Ormerod, K. L., Byrnes, E. J., III, Wood, I. A., Lodge, J. K., Heitman, J. and Fraser, J. A. (2014). The H99 family tree: variation in the common laboratory reference strains of Cryptococcus neoformans var. grubii characterised through whole-genome sequencing. 9th International Conference on Cryptococcus and Cryptococcosis, Amsterdam, The Netherlands, 15-19 May 2014. Berlin, Germany: Wiley-Blackwell Verlag GmbH. doi: 10.1111/myc.12196
Nguyen, Hien D. and Wood, Ian A. (2012). Variable selection in statistical models using population-based incremental learning with applications to genome-wide association studies. 2012 IEEE World Congress on Computational Intelligence (IEEE-WCCI 2012), Brisbane Australia, 10-15 June 2012. Piscataway NJ, United States: I E E E. doi: 10.1109/CEC.2012.6256577
Gollapalli, Mohammed, Li, Xue, Wood, Ian and Governatori, Guido (2011). Approximate record matching using hash grams. 2011 IEEE 11th International Conference on Data Mining (ICDM 2011), Vancouver Canada, 11-14 December 2011. Piscataway, NJ, United States: IEEE. doi: 10.1109/ICDMW.2011.33
Gollapalli, Mohammed, Li, Xue, Wood, Ian and Governatori, Guido (2011). Ontology guided data linkage framework for discovering meaningful data facts. 7th International Conference on Advanced Data Mining and Applications (ADMA 2011), Beijing, China, 17-19 December 2011. Heidelberg, Germany: Springer. doi: 10.1007/978-3-642-25856-5_19
Rowland, S. L. and Wood, I. (2011). Producing new forms of engaging: High-benefit assessment for undergraduate science students. 18th Annual ASM Conference for Undergraduate Educators, Baltimore, MD, United States, 2 - 5 June 2011. United States: American Society for Microbiology. doi: 10.1128/jmbe.v12i1.298
Rowland, S., Gillam, E. M. J., Hamilton, S. E., Ramakrishna, M., Reid, A., Smith, C., Ward, L. C., Wood, I. and Wright, A. (2010). Rebuilding a generalist biochemistry course around core concepts rather than heavy content: Painting the big picture for a large mixed-learner cohort. 21st Biennial Conference on Chemistry Education, Denton, TX, U.S.A., 1-5 August 2010.
Gallagher, M. R., Wood, I., Keith, J. and Sofronov, G. (2007). Bayesian inference in estimation of distribution algorithms. IEEE Congress on Evolutionary Computation (CEC 2007), Singapore, 25-28 September 2007. Piscataway, NJ, U.S.A.: IEEE - Institute of Electrical Electronics Engineers Inc.. doi: 10.1109/CEC.2007.4424463
Wood, I. A., Mengersen, K. and Moser, G. (2005). Comparative Mapping of Genomes. International Workshop on Statistical Modelling (IWSM 2005), Sydney, Australia, 10-15 July, 2005. Amsterdam, The Netherlands: Statistical Modelling Scoiety.
Wood, and Downs, T (1998). Demon algorithms and their application to optimization problems. 2nd IEEE World Congress on Computational Intelligence (WCCI 98), Anchorage Ak, May 04-09, 1998. NEW YORK: IEEE.
Thesis
Wood, Ian Andrew (2004). Boltzmann machine learning : analysis and improvements. PhD Thesis, School of Information Technology and Electrical Engineering, The University of Queensland. doi: 10.14264/106803