About

My favourite topic areas – Data Science, Machine Learning, Cloud computing, PLC control and Spectroscopy. During my career progression from a research data scientist to an educator, academic and commercial service consultant, I have developed an appreciation of communication - essential to bring the potential of Data to life.

Teaching Masters of Data Science at James Cook University

  • MA5851: Natural Language Processing
  • MA5852: Computer Vision and AWS Sagemaker
  • MA5832: Data Mining and Machine Learning
  • MA5830: Data Visualisation
  • MA5820: Statistical Methods for Data Scientists
  • MA5810: Introduction to Data Mining
  • MA5800: Foundations for Data Science

Publications

International peer review journal publications

  1. O’Shea M, Donald D, Simpson J, Keefe E, Staunton S. “Development of laboratory near infrared (NIR) spectroscopy systems for sugar mill and refinery applications.”  International Sugar Journal, Vol 116 , p 748-753 (2014)
  2. Donald D. “Laboratory information management system integration of a NIR instrument network.” Proc. International Conference on Near Infrared Spectroscopy, France (2013)
  3. O’Shea M, Donald D, Simpson J, Keefe E, Staunton S. “Development of laboratory near infrared (NIR) spectroscopy systems for sugar mill and refinery applications.”  Proc. International. Soc. Sugar Cane Technol. Brazil (2013)
  4. Donald D, Everingham Y, Coomans D. “Joint multiple adaptive wavelet regression ensembles” Chemometrics and Intelligent Laboratory Systems, vol 108, Issue 2, p133–141 (2011)
  5. Donald D., Y. Everingham and D. Coomans, Integrated wavelet principal component mapping for unsupervised clustering on near infra-red spectra, Chemometrics and Intelligent Laboratory Systems, 2005. 77(1-2): p. 32-42.
  6. Donald D., Everingham Y., Coomans D., Cozzolino D. and Gishen M., Adaptive wavelet modelling of a 3-way experimental design in chemometrics, Chemometrics and Intelligent Laboratory Systems, 2006, vol. 82 (1-2), p. 122-129.
  7. Donald D., Hancock T., Coomans D. and Everingham Y., Bagged super wavelet reduction for boosted prostate cancer classification of SELDI-TOF mass spectral serum profiles, Chemometrics and Intelligent Laboratory Systems, 2006, vol. 82 (1-2), p. 2-7.
  8. Donald D., Coomans D., Everingham Y., Cozzolino D. and Gishen M., Repeated Measures Experimental Design in Near Infrared Spectroscopy using Adaptive Wavelets, Current Development in Theory and Applications of Wavelets, 2007 vol. 1 (2), p. 165 – 182.
  9. D. Donald, C Huddlestone-Home, Model validation for MLE logistic regression on cyclic data using bootstrapping, Submitted to Journal of the Royal Statistical Society: Series C. (06/10/2005)
  10. Y. Everingham, K. Lowe, D. Donald, D. Coomans, and J. Markley, Advanced satellite imagery to classify sugarcane crop characteristics, Advanced satellite imagery to classify sugarcane crop characteristics, 2007, Agronomy for Sustainable Development, vol. 27 (2). pp. 111-117.

Book chapters

  1. Donald D, Everingham Y, McKinna L, Coomans D, “Feature selection in the wavelet domain: Adaptive wavelets.” Comprehensive Chemometrics, Chemical and Biochemical Data Analysis. Editors-in-Chief:  Stephen D. Brown, Romà Tauler, and Beata Walczak.  ISBN: 978-0-444-52701-1. Vol 3, Chapter 23, p647-679 (2009)

Conference proceedings

  1. David Donald. “Convolutional Neural Network analysis with multivariate inputs for fibre prediction of sugarcane” Australian Near Infrared Spectroscopy Group Conference, Cairns 2022.
  2. Justin Sexton, Yvette Everingham, David Donald, et. Al. “A comparison of non-linear regression methods for improved on-line near infrared spectroscopic analysis of a sugarcane quality measure” Journal of Near Infrared Spectroscopy, Volume: 26 issue: 5, p 297-310 (2018)
  3. J Sexton, Y Everingham, D Donald, S Staunton, R White “A feasibility test for detection of atypical cane samples using near infrared spectroscopy” Proc. Aust. Soc. Sugar Cane Technol. Vol 40 (2018)
  4. J Sexton, Y Everingham, D Donald “A comparison of data mining algorithms for improving NIR models of cane quality measures” Proc. Aust. Soc. Sugar Cane Technol. Vol 39 (2017)
  5. Keeffe E, Staunton S, Simpson J, Donald D. “NIR Spectroscopy in sugar mill laboratories: An adoption issue” Proc. International Conference on Near Infrared Spectroscopy, Brazil (2015)
  6. Sallam N, Achadian E, Putra L, Dianpratiwi T, Kristini A, Donald D, Magarey R. “In search of varietal resistance to sugarcane moth borers in Indonesia” Proc. Aust. Soc. Sugar Cane Technol. Vol 36 (2014)
  7. Donald D, Graham B, Staunton S, Simpson J, O’Shea M. “Routine data generation for sugar mill and refinery applications using a laboratory-based near infrared (NIR) instrument.”  Proc. Aust. Soc. Sugar Cane Technol. Vol 35 (2013)
  8. Curtis M, Donald D, Ridd M. “Determination of sucrose and glucose in sugarcane using a glucose biosensor.” Proc. Aust. Soc. Sugar Cane Technol. Vol 34 (2012)
  9. Donald D, Staunton S, Burgess D. “In-field measurement of sugarcane composition for drying-off on the Tablelands.” Proc. Aust. Soc. Sugar Cane Technol. Vol 33 (2011)
  10. O’Shea M, Staunton S, Donald D, Simpson J. “Developing laboratory near infrared (NIR) instruments for the analysis of sugar factory products.” Proc. Aust. Soc. Sugar Cane Technol. Vol 33 (2011)
  11. Staunton S, Donald D, Pope G.  “Estimating sugarcane composition using ternary growth relationships.” Proc. Aust. Soc. Sugar Cane Technol. Vol 33 (2011)

Awards

2011 - ASSCT Presidents Medal for the best paper presented

2013 – ASSCT Lloyd Cripps Sugar Chemistry Award

Supervision, Completed

  • Statistical data mining algorithms for optimising analysis of spectroscopic data from on-line NIR mill systems (2020, PhD , Industry Advisor)