ORCID as entered in ROS
https://orcid.org/0000-0002-3345-5912
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Journal articles
, 2025, 'The impact of surface polarisation on the degradation of tunnel oxide passivating contacts in silicon solar cells', Solar Energy Materials and Solar Cells, 282, http://dx.doi.org/10.1016/j.solmat.2024.113340
, 2024, 'Deep learning-based perspective distortion correction for outdoor photovoltaic module images', Solar Energy Materials and Solar Cells, 277, http://dx.doi.org/10.1016/j.solmat.2024.113107
, 2024, 'Extracting the parameters of two-energy-level defects in silicon wafers using machine learning models', Solar Energy Materials and Solar Cells, http://dx.doi.org/10.1016/j.solmat.2024.113123
, 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, 'Raging with the Machine in the Uncanny Valley: Human–AI Cocreativity in the Eurovision-Themed AI Song Contest', Computer Music Journal, 47, pp. 44 - 63, http://dx.doi.org/10.1162/comj_a_00674
, 2022, 'On the kinetics of high intensity illuminated annealing of n-type SHJ solar cells: 0.4%
, 2022, 'Silicon Heterojunction Solar Cells and p-type Crystalline Silicon Wafers: A Historical Perspective', Solar RRL, http://dx.doi.org/10.1002/solr.202200449
, 2022, 'High-Intensity Illuminated Annealing of Industrial SHJ Solar Cells: A Pilot Study', IEEE Journal of Photovoltaics, 12, pp. 267 - 273, http://dx.doi.org/10.1109/JPHOTOV.2021.3122932
, 2022, 'Impact of surface doping profile and passivation layers on surface-related degradation in silicon PERC solar cells', Solar Energy Materials and Solar Cells, 235, http://dx.doi.org/10.1016/j.solmat.2021.111497
, 2021, 'Increased surface recombination in crystalline silicon under light soaking due to Cu contamination', Solar Energy Materials and Solar Cells, 232, http://dx.doi.org/10.1016/j.solmat.2021.111360
, 2020, 'Investigation of light-induced degradation in N-Type silicon heterojunction solar cells during illuminated annealing at elevated temperatures', Solar Energy Materials and Solar Cells, 218, pp. 110752, http://dx.doi.org/10.1016/j.solmat.2020.110752
, 2020, 'Evidence for a Light-Induced Degradation Mechanism at Elevated Temperatures in Commercial N-Type Silicon Heterojunction Solar Cells', Solar RRL, 4, http://dx.doi.org/10.1002/solr.202000214
, 2019, 'Effects of Interfacial Layers on the Open Circuit Voltage of Polymer/Fullerene Bulk Heterojunction Devices Studied by Charge Extraction Techniques', ACS Applied Materials and Interfaces, 11, pp. 21030 - 21041, http://dx.doi.org/10.1021/acsami.9b02850
, 2017, 'Quantifying Recombination Losses during Charge Extraction in Bulk Heterojunction Solar Cells Using a Modified Charge Extraction Technique', Advanced Energy Materials, 7, http://dx.doi.org/10.1002/aenm.201602026
, 2015, 'Driving Force Dependence of Electron Transfer Kinetics and Yield in Low-Band-Gap Polymer Donor-Acceptor Organic Photovoltaic Blends', Journal of Physical Chemistry C, 119, pp. 12829 - 12837, http://dx.doi.org/10.1021/acs.jpcc.5b01617
Conference Papers
, 2024, 'An unsupervised learning approach to model potential induced degradation in photovoltaic modules', in Abdullah-Vetter Z (ed.), Sydney, Australia, presented at
, 2024, 'Applications of a machine learning model for real-time interpolated PVsyst simulations', in Applications of a machine learning model for real-time interpolated PVsyst simulations, Sydney, Australia, presented at
, 2024, 'Assessing the practical accuracy and limitations of PVsyst models for performance assessment of utility photovoltaic systems', Sydney, Australia, presented at
, 2024, 'Automated multiclass and severity classification of defects in photovoltaic module luminescence images using unsupervised machine learning', Sydney, Australia, presented at
, 2024, 'Development and application of virtual photovoltaic soiling sensors', Sydney, Australia, presented at
, 2024, 'Efficiency loss analysis in solar cells using explainable AI on I-V data and luminescence images', Sydney, Australia, presented at
, 2024, 'Evaluating statistical degradation rate calculation methods using current-voltage measurements', Sydney, Australia, presented at
, 2024, 'Optimising lifecycle management for utility-scale photovoltaic systems: An integrated electrical, economic, and environmental strategy', Sydney, Australia, presented at
, 2024, 'Regional driving factors of degradation in Australian residential photovoltaic systems: A performance loss analysis', Sydney, Australia, presented at
, 2024, 'First approximations for cleaning of soil accumulated at Australian PV sites', Numazu, Japan, presented at
, 2024, 'Optimising electrical, financial, and environmental outcomes for photovoltaic module lifecycle management: an automated computational approach', Numazu, Japan, presented at
, 2024, 'Assessing degradation trends of residential photovoltaic systems and their drivers across Australia', Numazu, Japan, presented at
, 2024, 'Digital-twins of utility PV systems: PVsyst-based model limitations and implications', Numazu, Japan, presented at
, 2024, 'Variable performance loss rates at different times of the day in a utility-scale PV system', Numazu, Japan, presented at
, 2024, 'Machine learning applications for photovoltaic systems analysis', Queen's College, Oxford, United Kingdom, presented at
, 2024, 'Identifying distinct performance patterns in utility-scale photovoltaic plants using an unsupervised machine learning model', Vienna, Austria, presented at
, 2024, 'Photovoltaic cell defect classification from luminescence images: Embedding and clustering with unsupervised machine learning', Vienna, Austria, presented at
, 2024, 'Photovoltaic module array luminescence image preprocessing: Heuristic algorithms for perspective correction and cell segmentation', Vienna, Austria, presented at
, 2024, 'Deep learning-assisted extraction of photoluminescence and series resistance images from a single electroluminescence measurement', Seattle, USA, presented at
, 2024, 'Extracting the parameters of two-energy-level defects in silicon wafers using machine learning models', Seattle, USA, presented at
, 2024, 'Photovoltaic soiling from particulate matter across Australia', Canberra, Australia, presented at
, 2023, 'Automated photovoltaic module quality assessment from luminescence images: defect classification using unsupervised machine learning', Melbourne, Australia, presented at
, 2023, 'Advanced analysis of internal quantum efficiency measurements of GaAs solar cells using machine learning', Melbourne, Australia, presented at
, 2023, 'AI-driven extraction of spatially-resolved photoluminescence and series resistance from electroluminescence images', Melbourne, Australia, presented at
, 2023, 'Distortion correction for real-world solar panel images based on deep learning', Melbourne, Australia, presented at
, 2023, 'Enhancing luminescence images through deep learning-based point spread function correction', Melbourne, Australia, presented at
, 2023, 'Photovoltaic module performance and degradation analysis', Melbourne, Australia, presented at
, 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
, 2023, 'Automated photovoltaic module end-of-life assessment', UNSW Sydney, Australia, presented at
, 2023, 'Automated photovoltaic module quality assessment: defect identification and classification from luminescence images using machine learning', Puerto Rico, presented at
, 2023, 'Predicting damp heat degradation in heterojunction modules using machine learning', Puerto Rico, presented at
, 2023, 'Predicting damp heat degradation in heterojunction modules using machine learning', Puerto Rico, presented at
, 2023, 'Using GPT-3 to Achieve Semantically Relevant Data Sonificiation for an Art Installation', Springer Nature, Brno, Czech Republic, pp. 212 - 227, presented at
, 2023, 'The Human-Built Environment-Natural Environment Relation-An Immersive Multisensory Exploration with 'System of a Sound'', in International Conference on Intelligent User Interfaces, Proceedings IUI, pp. 8 - 11, http://dx.doi.org/10.1145/3581754.3584119
, 2023, 'Using GPT-3 to Achieve Semantically Relevant Data Sonificiation for an Art Installation', in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp. 212 - 227, http://dx.doi.org/10.1007/978-3-031-29956-8_14
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https://orcid.org/0000-0002-3345-5912