Rate My Professor Ian Wood
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Creates a collaborative learning environment.
Always supportive and understanding.
Creates dynamic and engaging lessons.
Inspires curiosity and a love for knowledge.
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About Ian
Dr. Ian Wood is a Lecturer in Statistics in the School of Mathematics and Physics at the University of Queensland. He holds a Bachelor of Science (Advanced Honours), a Bachelor of Engineering (Honours), and a Doctor of Philosophy from the University of Queensland, where he completed his PhD in 2004 with a thesis titled 'Boltzmann machine learning: analysis and improvements'. Since 2008, he has been employed as a Lecturer at the University of Queensland. His research interests encompass classification, bioinformatics, stochastic optimisation, machine learning, and mixture models. Dr. Wood has contributed to various collaborative projects, including developments in statistical methods for data analysis and modeling.
Dr. Wood teaches a range of statistics courses, including fourth-year advanced statistics, statistics for first-year pharmacy students, and postgraduate data science courses such as DATA7202 Statistical Methods for Data Science and STAT3006 Statistical Learning. His teaching portfolio also includes PHRM3301 Social Pharmacy and the Health System 3A, PHRM1102 Pharmacy Practice and Medicines Management 1B, and advanced courses like STAT4401/7502 Advanced Statistics I and STAT4402/7503 Advanced Statistics II. Key publications include 'Naphthalimide derivatives as film-based fluorescent sensors for rapid detection of illicit drugs' (2025, Advanced Sensor Research), 'InSpectra – A Platform for Identifying Emerging Chemical Threats' (2023, Journal of Hazardous Materials), 'A modified expectation-maximization algorithm for latent Gaussian graphical model' (2022, Canadian Journal of Statistics), 'ORAI1 regulates sustained cytosolic free calcium fluctuations during breast cancer cell apoptosis and apoptotic resistance via a STIM1 independent pathway' (2022, The FASEB Journal), 'Direct feature evaluation in black-box optimization using problem transformations' (2018, Evolutionary Computation), 'Asymptotic normality of the maximum pseudolikelihood estimator for fully visible Boltzmann machines' (2016, IEEE Transactions on Neural Networks and Learning Systems), 'Characterizing Uncertainty in High-Density Maps from Multiparental Populations' (2014, Genetics), and 'Analysis of the genome and transcriptome of Cryptococcus neoformans var. grubii reveals complex RNA expression and microevolution leading to virulence attenuation' (2014, PLoS Genetics).
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