Dr Ali Zia
email Ali.Zia@anu.edu.au

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About

I received a B.Sc.(Hons.) degree in computer science from the University of Punjab, Lahore, Pakistan, in 2006. I got a Master of Computing degree from Australian National University, Canberra, Australia in 2009, and a PhD degree from Griffith University, Queensland, Australia in 2020. I am currently working at the Australian National University (ANU) and CSIRO as a postdoctoral research fellow. Before that, I was working as a researcher at ARC Research Hub for Driving Farming Productivity and Disease Prevention, Griffith University, Australia. Prior to that, I worked as a developer/programmer at Griffith University, Australia, and before that, I worked as Assistant Professor at COMSATS University, Lahore, Pakistan. I also worked as a researcher at Neville Roach Laboratory, NICTA, Sydney, Australia. Preceding that, I also worked at various software houses in Lahore, Pakistan.

Please visit my personal web-site for updated information:

www.ali-zia.me

Affiliations

Research interests

My research interests include pattern recognition, machine learning, computer vision, 3D structure analysis and spectral imaging with their applications to electricity load forecasting, remote sensing, agriculture, medicine, and environmental informatics.

Publications

  • Zia, A, Zhou, J & Gao, Y 2021, 'Exploring Chromatic Aberration and Defocus Blur for Relative Depth Estimation from Monocular Hyperspectral Image', IEEE Transactions on Image Processing, vol. 30, pp. 4357-4370.
  • Bao, D, Zhou, J, Bhuiyan, S et al. 2021, 'Early Detection of Sugarcane Smut Disease in Hyperspectral Images', 36th International Conference on Image and Vision Computing New Zealand, IEEE, New Zealand.
  • Tayab, U, Zia, A, Yang, F et al. 2020, 'Short-term load forecasting for microgrid energy management system using hybrid HHO-FNN model with best-basis stationary wavelet packet transform', Energy, vol. 203, pp. 1-11.
  • Tayab, U, Lu, J, Yang, F et al. 2019, 'Microgrid Energy Management System for Academic Building', 29th Australasian Universities Power Engineering Conference (AUPEC), IEEE, USA, pp. 1-5.
  • Al-khafaji, S, Zhou, J, Zia, A et al. 2018, 'Spectral-Spatial Scale Invariant Feature Transform for Hyperspectral Images', IEEE Transactions on Image Processing, vol. 27, no. 2, pp. 837-850.
  • Al-khafaji, S, Zia, A, Zhou, J et al. 2017, 'Material Based Boundary Detection in Hyperspectral Images', 2017 International Conference on Digital Image Computing: Techniques and Applications, DICTA 2017, ed. Y Guo, M Murshed, Z Wang, D Feng, H Li, W Cai & J Gao, IEEE, Piscataway, United States, pp. 1-7.
  • Zia, A, Zhou, J & Gao, Y 2015, 'Relative Depth Estimation from Hyperspectral Data', International Conference on Digital Image Computing: Techniques and Applications (DICTA 2015), IEEE, Piscataway, NJ, USA, pp. 1-7.
  • Chaudhry, T, Gulrez, T, Zia, A et al. 2010, 'Bezier curve based dynamic obstacle avoidance and trajectory learning for autonomous mobile robots', ISDA 2010 : 10th International Conference on Intelligent Systems Design and Applications, ed. Aboul Ella Hassanien, Ajith Abraham, Francesco Marcelloni, Hani Hagras, IEEE Xplore, online, pp. 1059-1065.
  • Huang, J, Zia, A, Zhou, J et al 2008, 'Content-based image retrieval via subspace-projected salient features', Digital Image Computing: Techniques and Applications (DICTA 2008), ed. A. Robles-Kelly, Institute of Electrical and Electronics Engineers (IEEE Inc), Piscataway, NJ USA, pp. 593-599.

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