Overview
Background
Gordon holds a PhD in Chemical Engineering from the University of Cape Town, South Africa, which focused on the application of machine vision, image processing and machine learning algorithms for modelling grade in froth flotation systems.
Gordon spent ten years working for the Victorian Government developing technical computing and modelling solutions. These included the development of the Environmental Systems Modelling Platform, a tool that aims to bring multiple environmental models and datasets into a single easy to use software package, and the development of the Native Vegetation Regulations Tool, to calculate the interactions between proposed clearings and models of rare and threatened species, and thereby determine the required offset credits. More recently, Gordon worked as a data scientist at the Victorian Centre for Data Insights, where he worked with a team focused on delivering innovative data driven solutions across the government sector.
Gordon now applies his data analytics, modelling and technical computing skills at the JKMRC where he works with the Advanced Process Prediction and Control group developing tools for improved time series analysis and visualisation of industrial data and comminution process models.
Availability
- Dr Gordon Forbes is:
- Available for supervision
Fields of research
Qualifications
- Bachelor of Science in Electrical Engineering, University of Cape Town
- Masters (Research), University of Cape Town
- Doctor of Philosophy, University of Cape Town
Research interests
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Soft sensors and modelling
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Data analytics
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Xray tomography
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Machine learning
Works
Search Professor Gordon Forbes’s works on UQ eSpace
2024
Journal Article
Application of machine learning for generic mill liner wear prediction in Semi-Autogenous Grinding (SAG) mills
Pural, Yusuf Enes, Ledezma, Tania, Hilden, Marko, Forbes, Gordon, Boylu, Feridun and Yahyaei, Mohsen (2024). Application of machine learning for generic mill liner wear prediction in Semi-Autogenous Grinding (SAG) mills. Minerals, 14 (12) 1200, 1-16. doi: 10.3390/min14121200
2024
Other Outputs
Feed and product characterisation for gravity separation modelling
Forbes, Gordon (2024). Feed and product characterisation for gravity separation modelling. Brisbane, QLD Australia: The University of Queensland.
2024
Journal Article
Sustainable resource management: the end of nickel mining?
Nell (née Campbell), Kristy, Valenta, Richard K., Forbes, Gordon, Yahyaei, Mohsen and Ilyas, Hafiz M. A. (2024). Sustainable resource management: the end of nickel mining?. Recycling, 9 (6) 102, 1-17. doi: 10.3390/recycling9060102
2024
Conference Publication
Coalescence in Fluidized Bed Flotation: Understanding the Interplay Between Chemistry and Hydrodynamics
Skliar, Anna, Verster, Isabella, Yenial Arslan, Unzile, Forbes, Gordon and Forbes, Liza (2024). Coalescence in Fluidized Bed Flotation: Understanding the Interplay Between Chemistry and Hydrodynamics. XXXI International Minerals Processing Congress, Washington, DC United States, 29 September - 3 October 2024. Washington, DC United States: SME.
2024
Journal Article
Impact of Pyrite Textures Prevalence on Flotation Performance in Mount Isa Copper Orebodies
Jefferson Montoya, M., Jones, T.R, Curtis-Morar, C., Parbhakar-Fox, A., Forbes, G. and Forbes, E. (2024). Impact of Pyrite Textures Prevalence on Flotation Performance in Mount Isa Copper Orebodies. Mineral Processing and Extractive Metallurgy Review, ahead-of-print (ahead-of-print), 1-15. doi: 10.1080/08827508.2024.2349204
2023
Conference Publication
An object-based image recognition approach methodology for pyrite texture quantification in flotation performance studies
Jefferson, Mayra, Forbes, Gordon, Brown, Elliot, Curtis-Morar, Catherine, Parbhakar-Fox, Anita and Elizaveta Forbes (2023). An object-based image recognition approach methodology for pyrite texture quantification in flotation performance studies. Procemin-GEOMET, Santiago, Chile, 4-6 October 2023.
2023
Conference Publication
Identification of semi-autogenous grinding mill operating states using clustering
Adhikari, Niranjan, Forbes, Gordon, Hilden, Marko and Yahyaei, Mohsen (2023). Identification of semi-autogenous grinding mill operating states using clustering. SAG Conference 2023, Vancouver, BC Canada, 24-28 September 2023.
2023
Conference Publication
Trusted automation, the pathway toward process automation of SABC circuits
Yahyaei, M., Hilden, M. and Forbes, G. (2023). Trusted automation, the pathway toward process automation of SABC circuits. SAG 2023, Vancouver, BC, Canada, 24-28 September 2023.
2023
Conference Publication
Trusted automation, the pathway toward process automation of SABC circuits
Yahyaei, M., Hilden, M. and Forbes, G. (2023). Trusted automation, the pathway toward process automation of SABC circuits. SAG Conference 2023, Vancouver, BC Canada, 24-28 September 2023.
2023
Conference Publication
Mine-to-mill the next phase—incorporating soft sensors and data analytics
Madrid, P., Forbes, G., Vizcarra, T., Hilden, M. and Wong, B. (2023). Mine-to-mill the next phase—incorporating soft sensors and data analytics. SAG 2023, Vancouver, BC, Canada, 24-28 September 2023.
2023
Other Outputs
SAG Advanced Process Control review: Final report for Dugald River Mine
Yahyaei, Mohsen, Hilden, Marko, Forbes, Gordon and Meng, Yuhao (2023). SAG Advanced Process Control review: Final report for Dugald River Mine. Brisbane, Australia: The University of Queensland, Julius Kruttschnitt Mineral Research Centre (JKMRC).
2023
Conference Publication
Data analytics and modelling for trustable process automation
Yahyaei, Mohsen, Forbes, Gordon and Hilden, Marko (2023). Data analytics and modelling for trustable process automation. 10th International Congress on Automation, Robotics and Digitalization in Mining, Santiago, Chile, 9-11 August 2023.
2023
Journal Article
Addressing geological challenges in mineral resource estimation: a comparative study of deep learning and traditional techniques
Battalgazy, Nurassyl, Valenta, Rick, Gow, Paul, Spier, Carlos and Forbes, Gordon (2023). Addressing geological challenges in mineral resource estimation: a comparative study of deep learning and traditional techniques. Minerals, 13 (7) 982, 982. doi: 10.3390/min13070982
2023
Conference Publication
Integration will take you forward: causal networks as a new approach to address inherent problems with risk management practice in mining organisations
Seligmann, B.J., Micklethwaite, S., Forbes, G., Lin, Y., Trendle, J., Bowdidge-Calvert, C., Verster, I., Antonio, C., Ziemski, M. and Hernandez-Santin, L. (2023). Integration will take you forward: causal networks as a new approach to address inherent problems with risk management practice in mining organisations. 26th World Mining Congress, Brisbane, QLD Australia, 26-29 June 2023. Brisbane, QLD Australia: 26th World Mining Congress.
2023
Conference Publication
Linking ore type with process performance
Forbes, Gordon, Reyes, Francisco, Madrid, Percy, Wong, Bevin and Yahyaei, Mohsen (2023). Linking ore type with process performance. 26th World Mining Congress, Brisbane, QLD, Australia, 26-29 June 2023.
2022
Conference Publication
Detection of ball mill overloading using dynamic time warping
Adhikari, Niranjan, Forbes, Gordon, Hilden, Marko and Yahyaei, Mohsen (2022). Detection of ball mill overloading using dynamic time warping. IMPC Asia-Pacific 2022, Melbourne, VIC Australia, 22-24 August 2022. Carlton, VIC Australia: The Australasian Institute of Mining and Metallurgy.
2022
Conference Publication
Soft Sensors for Advanced Process Monitoring and Control of Comminution Circuits
Hilden, Marko, Reyes, Francisco, Ye, Ziming, Jokovic, Vladimir, Forbes, Gordon and Yahyaei, Mohsen (2022). Soft Sensors for Advanced Process Monitoring and Control of Comminution Circuits. IMPC Asia Pacific 2022, Melbourne, VIC Australia, 22-24 August 2022. Carlton, VIC Australia: Australasian Institute of Mining and Metallurgy.
2022
Journal Article
Frother characterization using a novel bubble size measurement technique
Wang, Junyu, Forbes, Gordon and Forbes, Elizaveta (2022). Frother characterization using a novel bubble size measurement technique. Applied Sciences, 12 (2) 750, 750. doi: 10.3390/app12020750
2021
Conference Publication
Soft sensors and their application in advanced process control of mineral processing plants
Yahyaei, Mohsen, Hilden, Marko, Reyes, Francisco and Forbes, Gordon (2021). Soft sensors and their application in advanced process control of mineral processing plants. Procemin-Geomet 2021, Santiago, Chile, 20-22 October 2021. Santiago, Chile: Gecamin.
2021
Journal Article
Beyond the social license to operate: whole system approaches for a socially responsible mining industry
Verrier, Brunilde, Smith, Carl, Yahyaei, Mohsen, Ziemski, Marcin, Forbes, Gordon, Witt, Kathy and Azadi, Mehdi (2021). Beyond the social license to operate: whole system approaches for a socially responsible mining industry. Energy Research and Social Science, 83 102343, 102343. doi: 10.1016/j.erss.2021.102343
Funding
Current funding
Supervision
Availability
- Dr Gordon Forbes is:
- Available for supervision
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Supervision history
Current supervision
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Doctor Philosophy
Machine Learning for Identification of Operating States in SABC Circuits
Principal Advisor
Other advisors: Dr Marko Hilden, Professor Mohsen Yahyaei
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Doctor Philosophy
Study of Application of Machine Learning and Deep Learning Algorithms in Resource Estimation
Associate Advisor
Other advisors: Associate Professor Carlos Spier, Professor Rick Valenta
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Doctor Philosophy
Evaluation of the environmental reactivity of porphyry copper ore and gangue before and after mining and processing
Associate Advisor
Other advisors: Dr Nathan Fox, Associate Professor Anita Parbhakar-Fox
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Doctor Philosophy
Flotation properties of base metal sulphides in composite particles, as a function of their mineral chemistry.
Associate Advisor
Other advisors: Associate Professor Anita Parbhakar-Fox, Associate Professor Liza Forbes
Completed supervision
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2024
Doctor Philosophy
Study of Application of Machine Learning and Deep Learning in Resource Estimation
Associate Advisor
Other advisors: Associate Professor Carlos Spier, Professor Rick Valenta
Media
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