Select Publications
Journal articles
2024, 'Machine learning for advanced characterisation of silicon photovoltaics: A comprehensive review of techniques and applications', Renewable and Sustainable Energy Reviews, 202, http://dx.doi.org/10.1016/j.rser.2024.114617
,2024, 'Automatic Quantitative Analysis of Internal Quantum Efficiency Measurements of GaAs Solar Cells Using Deep Learning', Advanced Science, http://dx.doi.org/10.1002/advs.202407048
,2023, 'Advanced analysis of internal quantum efficiency measurements using machine learning', Progress in Photovoltaics: Research and Applications, 31, pp. 790 - 802, http://dx.doi.org/10.1002/pip.3683
,Conference Papers
2024, 'An unsupervised learning approach to model potential induced degradation in photovoltaic modules', in Abdullah-Vetter Z (ed.), Sydney, Australia, presented at Asia-Pacific Solar Research Conference, Sydney, Australia, 03 December 2024
,2023, 'Advanced analysis of internal quantum efficiency measurements of GaAs solar cells using machine learning', Melbourne, Australia, presented at Asia-Pacific Solar Research Conference, Melbourne, Australia, 05 December 2023
,2023, 'Using latent ordinary differential equation neural networks to predict the degradation of heterojunction PV modules at the end of damp heat tests', Melbourne, Australia, presented at Asia-Pacific Solar Research Conference, Melbourne, Australia, 05 December 2023
,2023, 'Automated analysis of internal quantum efficiency measurements of GaAs solar cells using machine learning', in Conference Record of the IEEE Photovoltaic Specialists Conference, Institute of Electrical and Electronics Engineers (IEEE), Puerto Rico, pp. 1 - 3, presented at 50th IEEE Photovoltaics Specialists Conference, Puerto Rico, 12 June 2023 - 16 June 2023, http://dx.doi.org/10.1109/PVSC48320.2023.10359747
,2023, 'Predicting damp heat degradation in heterojunction modules using machine learning', Puerto Rico, presented at 50th IEEE Photovoltaics Specialists Conference, Puerto Rico, 12 June 2023
,2023, 'Predicting damp heat degradation in heterojunction modules using machine learning', Puerto Rico, presented at 50th IEEE Photovoltaics Specialists Conference, Puerto Rico, 12 June 2023, http://dx.doi.org/10.1109/PVSC48320.2023.10359614
,2022, 'Accelerating the solar energy transition through artificial intelligence', Nagoya, Japan, presented at 33rd International Photovoltaic Science and Engineering Conference, Nagoya, Japan, 13 November 2022
,2022, 'Automated analysis of internal quantum efficiency using chain order regression', in Conference Record of the IEEE Photovoltaic Specialists Conference, Institute of Electrical and Electronics Engineers (IEEE), Philadelphia, USA, pp. 476 - 478, presented at 49th IEEE Photovoltaics Specialists Conference, Philadelphia, USA, 06 June 2022 - 10 June 2022, http://dx.doi.org/10.1109/PVSC48317.2022.9938500
,2022, 'Using machine learning to predict the complete degradation of accelerated damp heat testing in just 10% of the time', in Conference Record of the IEEE Photovoltaic Specialists Conference, Institute of Electrical and Electronics Engineers (IEEE), Philadelphia, USA, pp. 0472 - 0474, presented at 49th IEEE Photovoltaics Specialists Conference, Philadelphia, USA, 06 June 2022 - 10 June 2022, http://dx.doi.org/10.1109/PVSC48317.2022.9938942
,2022, 'On the effect of misalignment distributions on the I-V curve of micro-CPV modules', Miyazaki, Japan (Online), presented at 18th International Conference on Concentrator Photovoltaic Systems, Miyazaki, Japan (Online), 25 April 2022 - 27 April 2022
,2021, 'A review of deep learning for defects classification in silicon cells and modules from luminescence images', UNSW, Sydney, presented at 2021 Asia-Pacific Solar Research Conference, UNSW, Sydney, 16 December 2021 - 17 December 2021
,2021, 'Simplified analysis of internal quantum efficiency using machine learning', Sydney, presented at Asia-Pacific Solar Research Conference, Sydney, 16 December 2021, http://dx.doi.org/10.26190/unsworks/28136
,2021, 'A deep learning approach for loss-analysis from luminescence images', in Conference Record of the IEEE Photovoltaic Specialists Conference, Institute of Electrical and Electronics Engineers (IEEE), Online, pp. 97 - 100, presented at 48th IEEE Photovoltaics Specialists Conference, Online, 20 June 2021 - 25 June 2021, http://dx.doi.org/10.1109/PVSC43889.2021.9518512
,2021, 'Localization of defects in solar cells using luminescence images and deep learning', in Conference Record of the IEEE Photovoltaic Specialists Conference, Institute of Electrical and Electronics Engineers (IEEE), Online, pp. 745 - 749, presented at 48th IEEE Photovoltaics Specialists Conference, Online, 20 June 2021 - 25 June 2021, http://dx.doi.org/10.1109/PVSC43889.2021.9518702
,2020, 'Localisation of solar cell defects in luminescence images using deep learning', Online, presented at Asia Pacific Solar Research Conference, Online, 30 November 2020
,Reports
2022, Solar Potential of Australian Social Housing Stock, http://dx.doi.org/10.26190/unsworks/28351, https://apvi.org.au/solar-potential-of-australian-social-housing-stock/
,2021, Powering a sporting nation: Rooftop solar potential for AFL, http://dx.doi.org/10.26190/unsworks/28026
,2021, Powering a sporting nation: Rooftop solar potential for Australian soccer, http://dx.doi.org/10.26190/unsworks/28022
,2021, Powering a sporting nation: Rooftop solar potential of Australian cricket, http://dx.doi.org/10.26190/unsworks/28025
,2020, Sunny side up: how schools, prisons and libraries can power Queensland’s renewable future, http://dx.doi.org/10.13140/RG.2.2.20897.22880
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