Overview
Background
Dr. Anthony Halog: Global Leader in AI-Enabled Circular Economy and Sustainable Systems
Dr. Anthony Halog is an internationally recognized expert in AI-driven circular economy, life cycle assessment (LCA), and sustainable systems engineering. His research integrates artificial intelligence, industrial ecology, and systems thinking to optimize green hydrogen production, bioeconomy transitions, and waste-to-energy systems.
As a Senior Academic at the University of Queensland, Dr. Halog leads research projects funded by ARC, EU Horizon, and industry partners. He has published over 130 high-impact journal articles, advancing knowledge in sustainability science and AI-enabled resource optimization. His work has influenced policy development and industry decarbonization strategies in Australia, Europe, and the Middle East.
Dr. Halog has been awarded prestigious international fellowships, including the OECD Research Fellowship (UK/Finland), DAAD Fellowship (Germany), Japan Society for the Promotion of Science (JSPS) Fellowship, and NSERC Fellowship (Canada). He has held visiting research positions in the UK, Germany, Japan, Saudi Arabia, and Morocco, expanding his global impact on circular economy modeling and AI applications in sustainability.
Beyond academia, he plays a key role in policy advisory and industry collaboration, partnering with the OECD, the United Nations, and the European Commission. As a keynote speaker and editorial board member, he continues to shape global discourse on sustainability transitions and AI-driven resource efficiency.
Availability
- Dr Anthony Halog is:
- Available for supervision
- Media expert
Fields of research
Qualifications
- Bachelor of Science, University of Mindanao
- Masters (Research) of Engineering, Asian Institute of Technology
- Masters (Coursework) of Business Administration (Advanced), Monash University
- Doctoral Diploma, Karlsruher Institut für Technologie
Research interests
-
AI/Digitalisation-Enabled Circular Bioeconomy
This research project aims to leverage digitalization, AI, and data analytics to advance the circular bioeconomy by optimizing the conversion of sustainable biomass into high-value bioproducts. Using life cycle sustainability assessment (LCSA) and systems modeling, the project will enhance resource efficiency, reduce environmental impact, and support the transition to a circular economy. Key outcomes include scalable solutions for sustainable production systems and policy recommendations for bioeconomy advancement.
-
Transitions to Energy Sustainability
This research project focuses on advancing energy sustainability through the integration of digitalisation, artificial intelligence (AI), data science, and analytics methods. The aim is to develop innovative solutions that enhance the efficiency and sustainability of energy systems. By leveraging AI and data-driven approaches, this project will explore the optimization of renewable energy integration, predictive maintenance, and energy consumption patterns, contributing to a resilient, low-carbon energy future.
-
Corporate Environmental Management for Sustainable and ESG Business Practices
This research project on Corporate Environmental Management aims to leverage digitalisation, AI, data science, and analytics to advance sustainable business practices aligned with ESG frameworks. By integrating cutting-edge technologies, the project will develop predictive models and decision-support systems to optimise resource efficiency, reduce carbon footprints, and enhance circular economy strategies. The project seeks to create scalable solutions that drive sustainability in corporate operations, making significant contributions to both academic research and industry practices.
-
AI/Data Science-Enabled Circular Economy
Leveraging digitalization, AI, and data analytics, this research explores innovative pathways for advancing a circular economy. By integrating these technologies, the project aims to optimize resource efficiency, minimize waste, and close material and energy loops, supporting sustainable production and consumption. The focus is on developing data-driven strategies to enhance circularity across industries, contributing to global sustainability and achieving economic resilience through cutting-edge, circular business models.
-
Digitalisation-Enabled Industrial Ecology
Leveraging digitalisation, AI, and data science, this project in Industrial Ecology aims to innovate sustainable industrial systems by analyzing material and energy flows. It focuses on transforming linear production processes into circular, low-carbon models, enhancing resource efficiency and minimizing waste. The research integrates life cycle assessment, circular economy principles, and advanced computational methods to develop scalable solutions for sustainable production and consumption systems, aligning with global sustainability goals.
-
Environmental systems modelling and analysis
This research focuses on environmental systems modeling and analysis, leveraging digitalization, AI, and data science to optimize sustainability outcomes. By integrating tools such as Life Cycle Assessment (LCA) and Material Flow Analysis (MFA), the project aims to address complex environmental challenges in circular bioeconomy, renewable energy, and resource management. This innovative approach supports decision-making for sustainable development and enhances the environmental performance of industrial systems.
-
AI-enabled Green Economy
This research investigates the integration of digitalization, AI, and data science to drive a just transition to a low-carbon, resource-efficient, and socially inclusive green economy. By analyzing the socio-environmental-economic impacts of converting sustainable feedstocks and waste into bioproducts, this work aims to enhance circular bioeconomy practices, improve resource efficiency, and reduce ecological footprints in line with sustainable development goals.
-
Data Analytics-Supported Green Supply Chain Management
This research project on Data Analytics-Supported Green Supply Chain Management leverages digitalisation, AI, data science, and analytics methods to optimise supply chains for sustainability. The project aims to reduce carbon footprints, enhance resource efficiency, and promote circular economy practices by integrating advanced data analytics with life cycle assessment (LCA) and systems thinking. The innovative approach targets key sustainability goals, making a significant impact on environmental performance and supply chain resilience.
-
Techno-Economic Analysis and Life Cycle Analysis
This project focuses on advancing Techno-Economic Analysis (TEA) and Life Cycle Analysis (LCA) by leveraging digitalization, Artificial Intelligence (AI), data science, and analytics. It aims to optimize sustainable energy systems and circular economy processes, integrating environmental, economic, and social impacts. The project will develop innovative, data-driven models to enhance decision-making in bioeconomy, renewable energy, and waste valorization industries, contributing to a low-carbon, circular economy and sustainable development goals (SDGs).
Research impacts
Dr. Anthony Halog's research has made a significant impact beyond academia, driving sustainability in various sectors and influencing policy at global levels. His work on life cycle assessment (LCA) and circular economy strategies has directly contributed to reducing environmental footprints in industries such as energy, waste management, and bioeconomy.
One of the most notable outcomes of Dr. Halog’s research is the application of LCA to optimize waste management systems, particularly in transitioning to a circular economy. His studies have been instrumental in shaping waste-to-energy policies in Indonesia and bioenergy strategies across the ASEAN region. These contributions have led to the development of sustainable practices that reduce greenhouse gas emissions and enhance resource efficiency.
Dr. Halog’s research has also been pivotal in advancing the understanding of sustainable supply chains, helping businesses minimize their environmental impact while maintaining economic viability. His interdisciplinary approach, combining systems thinking with practical applications, has empowered industries to adopt more sustainable practices, ultimately benefiting society by fostering a healthier environment and promoting economic resilience.
Through his extensive publications and collaborations, Dr. Halog’s work continues to influence sustainability policies and practices globally, making a lasting impact on both the economy and the environment.
Works
Search Professor Anthony Halog’s works on UQ eSpace
2013
Conference Publication
Towards a circular economy: an application of input-output oriented approach to improve eco-efficiency of Australia's food industry
Pagotto, Murilo and Halog, Anthony (2013). Towards a circular economy: an application of input-output oriented approach to improve eco-efficiency of Australia's food industry. 12th Annual IAS-STS Conference, Graz, Austria, 6-7 May 2013. Graz, Austria: Institute for Advanced Studies on Science, Technology and Society (IAS-STS).
2013
Book Chapter
Environmental assessment of a forest derived "Drop-in" biofuel
Halog, Anthony and Bortsie-Aryee, Nana Awuah (2013). Environmental assessment of a forest derived "Drop-in" biofuel. Biofuels - Economy, Environmental and Sustainability. (pp. 287-302) edited by Zhen Fang. Rijeka, Croatia: InTech. doi: 10.5772/50478
2013
Conference Publication
Production of a map of greenhouse gas emissions and energy use from Australian agriculture
Navarro, J., Bryan, B., Marinoni, O., Eady, S. and Halog, A. (2013). Production of a map of greenhouse gas emissions and energy use from Australian agriculture. 20th International Congress on Modelling and Simulation (MODSIM 2013), Adelaide, Australia, 1-6 December 2013. Canberra, Australia: Modelling and Simulation Society of Australia and New Zealand.
2013
Other Outputs
5.2. The integrated partial market equilibrium and LCA modelling (PME-LCA)
Earles, J. Mason and Halog, Anthony (2013). 5.2. The integrated partial market equilibrium and LCA modelling (PME-LCA). Luxembourg, Belgium: European Commission.
2012
Conference Publication
Using system dynamics to support consequential life cycle analysis: the forest based "drop-in" biofuel supply chain example
Aryee, Nana Awuah Bortsie and Halog, Anthony (2012). Using system dynamics to support consequential life cycle analysis: the forest based "drop-in" biofuel supply chain example. 2012 AIChE Spring Meeting and 8th Global Congress on Process Safety, 12AIChE, Houston, TX, United States, 1-5 April 2012. New York, NY, United States: AIChE.
2012
Conference Publication
Application of agent-based modeling (ABM) of an integrated system modeling framework for designing a sustainable industrial park
Bichraoui, Najet and Halog, Anthony (2012). Application of agent-based modeling (ABM) of an integrated system modeling framework for designing a sustainable industrial park. 2012 AIChE Spring Meeting and 8th Global Congress on Process Safety, 12AIChE, Houston, TX, United States, 1-5 April 2012. New York, NY, United States: AIChE.
2012
Conference Publication
Life cycle sustainability assessment of wood derived drop-in biofuels-case of the northeast forest based product industry
Bortsie-Aryee, Nana Awuah, Halog, Anthony and Wheeler, Clayton (2012). Life cycle sustainability assessment of wood derived drop-in biofuels-case of the northeast forest based product industry. IEEE International Symposium on Sustainable Systems and Technology (ISSST), Boston, United States, 16-18 May 2012. Piscataway, NJ, United States: IEEE. doi: 10.1109/ISSST.2012.6228026
2012
Conference Publication
Agent-based Modelling Simulation for the Development of an Industrial Symbiosis - Preliminary Results
Bichraoui, N., Guillaume, B. and Halog, A. (2012). Agent-based Modelling Simulation for the Development of an Industrial Symbiosis - Preliminary Results. The 3rd International Conference on Sustainable Future for Human Security, Japan, Kyoto University, 3-5 November 2012. Amsterdam, The Netherlands: Elsevier BV. doi: 10.1016/j.proenv.2013.02.029
2012
Conference Publication
Advancing computational modeling and analysis for assessing sustainability of large scale bioenergy production
Halog, Anthony and Bortsie-Aryee, Nana (2012). Advancing computational modeling and analysis for assessing sustainability of large scale bioenergy production. 2012 AIChE Spring Meeting and 8th Global Congress on Process Safety, 12AIChE, Houston, TX, United States, 1-5 April 2012. New York, NY, United States: AIChE.
2011
Journal Article
Advancing integrated systems modelling framework for life cycle sustainability assessment
Halog, Anthony and Manik, Yosef (2011). Advancing integrated systems modelling framework for life cycle sustainability assessment. Sustainability, 3 (2), 469-499. doi: 10.3390/su3020469
2010
Conference Publication
Comparative life cycle assessment of biofuel produced in two forest product biorefineries
Earles, Mason and Halog, Anthony (2010). Comparative life cycle assessment of biofuel produced in two forest product biorefineries.
2009
Journal Article
Models for evaluating energy, environmental and sustainability performance of biofuels value chain
Halog, Anthony (2009). Models for evaluating energy, environmental and sustainability performance of biofuels value chain. International Journal of Global Energy Issues, 32 (1-2), 83-101. doi: 10.1504/ijgei.2009.027975
2008
Journal Article
Developing a dynamic systems model for the sustainable development of the Canadian oil sands industry
Halog, Anthony and Chan, Albert (2008). Developing a dynamic systems model for the sustainable development of the Canadian oil sands industry. International Journal of Environmental Technology and Management, 8 (1), 3-22. doi: 10.1504/IJETM.2008.016295
2006
Conference Publication
Toward sustainable production in the Canadian oil sands industry
Halog, Anthony and Chan, Albert (2006). Toward sustainable production in the Canadian oil sands industry. Katholieke Universiteit Leuven.
2004
Journal Article
An approach to selection of sustainable product improvement alternatives with data uncertainty
Halog, Anthony (2004). An approach to selection of sustainable product improvement alternatives with data uncertainty. Journal of Sustainable Product Design, 4 (1-4), 3-19. doi: 10.1007/s10970-006-0002-y
2003
Conference Publication
Development of an assessment methodology for waste gasification technology under stochastic data
Halog, Anthony, Sagisaka, Masayuki and Inaba, Atsushi (2003). Development of an assessment methodology for waste gasification technology under stochastic data.
2003
Conference Publication
Ecological loss function: Basis for preliminary environmental evaluation and design of techniques
Halog, A, Sagisaka, M and Inaba, A (2003). Ecological loss function: Basis for preliminary environmental evaluation and design of techniques. 3rd International Symposium on Environmentally Conscious Design and Inverse Manufacturing (EcoDesign 03), Tokyo Japan, Dec 08-11, 2003. IEEE. doi: 10.1109/VETECF.2003.240339
2003
Conference Publication
Development of an assessment methodology for waste gasification technology under stochastic data
Halog, A, Sagisaka, M and Inaba, A (2003). Development of an assessment methodology for waste gasification technology under stochastic data. 1st International Conference on Energy and Environment (EnerEnv 2003), Changsha Peoples R China, Oct 11-14, 2003. SCIENCE PRESS.
2003
Journal Article
Modelling Uncertainties in Assessing Waste Gasification Technology
Halog, A., Sagisaka, M. and Inaba, A. (2003). Modelling Uncertainties in Assessing Waste Gasification Technology. Macro Review, 16 (1), 251-255. doi: 10.11286/jmr1988.16.251
2003
Conference Publication
Assessment of waste gasification technology under data uncertainty
Halog, A, Sagisaka, M and Inaba, A (2003). Assessment of waste gasification technology under data uncertainty. 3rd International Symposium on Environmentally Conscious Design and Inverse Manufacturing (EcoDesign 03), Tokyo Japan, Dec 08-11, 2003. IEEE. doi: 10.1109/VETECF.2003.240405
Funding
Past funding
Supervision
Availability
- Dr Anthony Halog is:
- Available for supervision
Before you email them, read our advice on how to contact a supervisor.
Available projects
-
Circular Economy and Resource Governance: Transition to Circular Agriculture and Bioeconomy in Australia
This research project explores the transition to circular agriculture and bioeconomy in Australia, focusing on sustainable phosphate utilization for fertilizer production. By integrating life cycle and systems engineering approaches, the project aims to optimize resource management, reduce environmental impacts, and support sustainable development. The research aligns with Australia's national priorities, contributing to innovative strategies for environmental conservation, waste management, and sustainable agricultural practices.
-
Dynamic System Modelling of Relationships between Environmental Sustainability, Food and Health Issues
This project aims to develop a cutting-edge computational model to explore the complex interrelationships between sustainability, climate change, food systems, dietary choices, and human health. Utilizing system dynamics and agent-based modeling (ABM), alongside AI, data science, and digitalization, the project will enable scenario analysis and policy formulation. The focus is on creating sustainable solutions, with an emphasis on developing expertise in modeling, data management, and innovative analytics for dynamic system analysis.
-
Life Cycle Sustainability Analysis of Deployment of Renewable Energy technologies
This project critically evaluates the environmental and socio-economic impacts of large-scale renewable energy deployment, focusing on green hydrogen, hydro and bioenergy. Utilizing advanced life cycle assessment (LCA), system dynamics, and data science, it identifies key impact "hot spots" across the energy lifecycle. The project aims to develop strategic frameworks for sustainable renewable energy adoption, leveraging digitalization, AI, and analytics to optimize resource efficiency and minimize trade-offs in renewable energy systems.
-
Systems Modelling of Linked Circular Economies
This project innovatively integrates System Dynamics Modelling (SDM) to analyze the urban food-energy-water nexus, aiming to minimize waste by explicitly linking circular economies. By leveraging digitalization, AI, and data science, the project visualizes resource pathways, identifies inefficiencies, and proposes sustainable solutions. This approach enhances urban resource management, reduces waste, and addresses critical sustainability challenges, making it highly relevant to experts in circular economy and sustainable urban development.
-
Integrated Assessment Modelling
This innovative research project integrates Industrial Ecology methods, including Life Cycle Assessment (LCA), Material Flow Analysis (MFA), and Input-Output Analysis (IOA), with Integrated Assessment Modelling (IAM) to explore low-carbon transition pathways. Utilizing the open-source MESSAGEix framework, the project will assess climate change mitigation and circular economy impacts in energy, transport, and materials sectors. Leveraging AI, digitalization, and data science, this framework aims to guide sustainable energy transitions and circular economy strategies.
-
Material Flow Accounting and Input-output Analysis for Reducing Energy Demand
This research project aims to reduce energy demand by transforming material and product consumption patterns across the supply chain. By integrating a hybrid model combining monetary-based input-output, physical, and energy data, the project will analyze historical consumption drivers over 20 years. Utilizing digitalization, AI, and data science, the project will inform sustainable consumption and production policies, contributing to climate action and enhancing resource efficiency across Australia's economy.
-
Dynamic System Modelling and Analysis for Pursuing Sustainable Bioeconomy
This project aims to develop a cutting-edge, spatially and temporally explicit systems model for sustainable aviation fuel production in Australia using bioenergy feedstocks such as microalgae, pongamia pinnata, and sugarcane. By integrating digitalization, AI, and data science, the model will assess carbon and water footprints, human health impacts, and economic viability. The project will address uncertainties and optimize bioenergy pathways, contributing to Australia's low-carbon energy future.
-
Socio-Economic and Ethical Implications of Scaling Up Green Hydrogen Production in Australia
This research explores the socio-economic and ethical challenges of scaling up green hydrogen production in Australia, crucial for achieving net-zero emissions. By analyzing current technologies, environmental impacts, and public perceptions, the study aims to develop strategies for equitable and sustainable hydrogen adoption. It integrates quantitative and qualitative methods to assess technical viability, justice issues, and stakeholder engagement, providing insights to guide policy development and promote a socially just energy transition.
-
Integration of Multi Agent Systems (MAS) and LCA for Analysing Australian Agri-food Sector
This project aims to develop a practical and comprehensive methodology for the integration of Multi Agent Systems (MAS) and life cycle assessment (LCA). In order to identify and characterize the Australian agro-system, this project will develop a prototype computational model to simulate Australian agricultural sector. Preferably, applicant has background in computer science or applied mathematics with experience in agent-based systems as well as strong interest in computation, applied mathematics, optimization and scientific programming. Successful applicant will develop skills in modelling, analysis, data management, scenario and policy formulation and the development of sustainable solutions.
-
Pursuing Circular Agriculture and Bioeconomy for Sustainable Industrial Development
This research project aims to transform agri-food systems from linear production to a circular economy by developing a comprehensive database and applying advanced life cycle and systems-based methods. The project will assess biodiversity, land use, water, and phosphorus impacts across selected food sub-sectors. Leveraging digitalization, AI, and data analytics, it will propose circular economy models for sustainable consumption and production, ensuring resilience and environmental efficiency in Australian agriculture.
-
Modelling Urban Metabolism of Cities
This research project aims to develop a holistic multi-agent-based framework to model complex urban systems like Brisbane and assess their sustainability. Leveraging digitalization, AI, data science, and analytics, the project will create a roadmap for sustainable urban development. Through comprehensive literature review, survey development, and statistical analysis, it will provide innovative solutions for urban planners and policymakers to address resource pressure, ecosystem degradation, and sustainable city growth. Keywords: sustainable urban development, multi-agent systems, AI, digitalization, urban sustainability, data science.
-
Agent-Based Modelling of Linked Circular Economies
This project explores innovative waste reduction in urban food-energy-water (FEW) nexus by integrating circular economies through Agent-Based Modeling (ABM). By simulating stakeholder decision-making, the project analyzes resource fluxes as emergent properties, identifying synergies, feedbacks, and thresholds within the FEW nexus. Leveraging digitalization, AI, and data science, the project aims to optimize urban resource management, enhancing sustainability by reducing inefficiencies and minimizing waste across interconnected systems.
-
Stocks and Flows of Metals and Mineral Resources: Quantifying Environmental Impacts and Risks
This research project explores the metal and mineral resource needs of Japanese and Korean industries, with a focus on rare earth metals and other resources supplied by Australia's mining sector. It will develop a comprehensive database to quantify resource usage and propose circular economy models for Queensland’s mining industry, leveraging digitalization, AI, and systems thinking. The project aims to align resource extraction with ecological limits while meeting international demands sustainably.
-
Digitalisation-Enabled Circular Bioeconomy for Global Transformation
This project aims to develop a digitalisation-enabled circular bioeconomy framework, focusing on the integration of advanced digital technologies with circular bioeconomy principles. The research will explore how digital tools such as AI and blockchain can enhance the sustainability of bioeconomic practices, particularly in agricultural value chains. This project will address challenges in environmental valuation, public acceptance of innovative technologies, and governance of sustainable value chains. The outcomes will contribute to policy recommendations and innovative models for the circular bioeconomy, supporting the global sustainability and digitalisation goals.
-
Dynamic System Modelling of Relationships between Environmental Sustainability, Food and Health Issues
This project aims to develop a cutting-edge computational model to explore the complex interrelationships between sustainability, climate change, food systems, dietary choices, and human health. Utilizing system dynamics and agent-based modeling (ABM), alongside AI, data science, and digitalization, the project will enable scenario analysis and policy formulation. The focus is on creating sustainable solutions, with an emphasis on developing expertise in modeling, data management, and innovative analytics for dynamic system analysis.
-
Life Cycle Sustainability Analysis of Deployment of Renewable Energy technologies
This project critically evaluates the environmental and socio-economic impacts of large-scale renewable energy deployment, focusing on green hydrogen, hydro and bioenergy. Utilizing advanced life cycle assessment (LCA), system dynamics, and data science, it identifies key impact "hot spots" across the energy lifecycle. The project aims to develop strategic frameworks for sustainable renewable energy adoption, leveraging digitalization, AI, and analytics to optimize resource efficiency and minimize trade-offs in renewable energy systems.
-
Systems Modelling of Linked Circular Economies
This project innovatively integrates System Dynamics Modelling (SDM) to analyze the urban food-energy-water nexus, aiming to minimize waste by explicitly linking circular economies. By leveraging digitalization, AI, and data science, the project visualizes resource pathways, identifies inefficiencies, and proposes sustainable solutions. This approach enhances urban resource management, reduces waste, and addresses critical sustainability challenges, making it highly relevant to experts in circular economy and sustainable urban development.
-
Circular Economy and Resource Governance: Transition to Circular Agriculture and Bioeconomy in Australia
This research project explores the transition to circular agriculture and bioeconomy in Australia, focusing on sustainable phosphate utilization for fertilizer production. By integrating life cycle and systems engineering approaches, the project aims to optimize resource management, reduce environmental impacts, and support sustainable development. The research aligns with Australia's national priorities, contributing to innovative strategies for environmental conservation, waste management, and sustainable agricultural practices.
-
Integrated Assessment Modelling
This innovative research project integrates Industrial Ecology methods, including Life Cycle Assessment (LCA), Material Flow Analysis (MFA), and Input-Output Analysis (IOA), with Integrated Assessment Modelling (IAM) to explore low-carbon transition pathways. Utilizing the open-source MESSAGEix framework, the project will assess climate change mitigation and circular economy impacts in energy, transport, and materials sectors. Leveraging AI, digitalization, and data science, this framework aims to guide sustainable energy transitions and circular economy strategies.
-
Material Flow Accounting and Input-output Analysis for Reducing Energy Demand
This research project aims to reduce energy demand by transforming material and product consumption patterns across the supply chain. By integrating a hybrid model combining monetary-based input-output, physical, and energy data, the project will analyze historical consumption drivers over 20 years. Utilizing digitalization, AI, and data science, the project will inform sustainable consumption and production policies, contributing to climate action and enhancing resource efficiency across Australia's economy.
-
Dynamic System Modelling and Analysis for Pursuing Sustainable Bioeconomy
This project aims to develop a cutting-edge, spatially and temporally explicit systems model for sustainable aviation fuel production in Australia using bioenergy feedstocks such as microalgae, pongamia pinnata, and sugarcane. By integrating digitalization, AI, and data science, the model will assess carbon and water footprints, human health impacts, and economic viability. The project will address uncertainties and optimize bioenergy pathways, contributing to Australia's low-carbon energy future.
-
Socio-Economic and Ethical Implications of Scaling Up Green Hydrogen Production in Australia
This research explores the socio-economic and ethical challenges of scaling up green hydrogen production in Australia, crucial for achieving net-zero emissions. By analyzing current technologies, environmental impacts, and public perceptions, the study aims to develop strategies for equitable and sustainable hydrogen adoption. It integrates quantitative and qualitative methods to assess technical viability, justice issues, and stakeholder engagement, providing insights to guide policy development and promote a socially just energy transition.
-
Integration of Multi Agent Systems (MAS) and LCA for Analysing Australian Agri-food Sector
This project aims to develop a practical and comprehensive methodology for the integration of Multi Agent Systems (MAS) and life cycle assessment (LCA). In order to identify and characterize the Australian agro-system, this project will develop a prototype computational model to simulate Australian agricultural sector. Preferably, applicant has background in computer science or applied mathematics with experience in agent-based systems as well as strong interest in computation, applied mathematics, optimization and scientific programming. Successful applicant will develop skills in modelling, analysis, data management, scenario and policy formulation and the development of sustainable solutions.
-
Pursuing Circular Agriculture and Bioeconomy for Sustainable Industrial Development
This research project aims to transform agri-food systems from linear production to a circular economy by developing a comprehensive database and applying advanced life cycle and systems-based methods. The project will assess biodiversity, land use, water, and phosphorus impacts across selected food sub-sectors. Leveraging digitalization, AI, and data analytics, it will propose circular economy models for sustainable consumption and production, ensuring resilience and environmental efficiency in Australian agriculture.
-
Modelling Urban Metabolism of Cities
This research project aims to develop a holistic multi-agent-based framework to model complex urban systems like Brisbane and assess their sustainability. Leveraging digitalization, AI, data science, and analytics, the project will create a roadmap for sustainable urban development. Through comprehensive literature review, survey development, and statistical analysis, it will provide innovative solutions for urban planners and policymakers to address resource pressure, ecosystem degradation, and sustainable city growth. Keywords: sustainable urban development, multi-agent systems, AI, digitalization, urban sustainability, data science.
-
Agent-Based Modelling of Linked Circular Economies
This project explores innovative waste reduction in urban food-energy-water (FEW) nexus by integrating circular economies through Agent-Based Modeling (ABM). By simulating stakeholder decision-making, the project analyzes resource fluxes as emergent properties, identifying synergies, feedbacks, and thresholds within the FEW nexus. Leveraging digitalization, AI, and data science, the project aims to optimize urban resource management, enhancing sustainability by reducing inefficiencies and minimizing waste across interconnected systems.
-
Stocks and Flows of Metals and Mineral Resources: Quantifying Environmental Impacts and Risks
This research project explores the metal and mineral resource needs of Japanese and Korean industries, with a focus on rare earth metals and other resources supplied by Australia's mining sector. It will develop a comprehensive database to quantify resource usage and propose circular economy models for Queensland’s mining industry, leveraging digitalization, AI, and systems thinking. The project aims to align resource extraction with ecological limits while meeting international demands sustainably.
-
Digitalisation-Enabled Circular Bioeconomy for Global Transformation
This project aims to develop a digitalisation-enabled circular bioeconomy framework, focusing on the integration of advanced digital technologies with circular bioeconomy principles. The research will explore how digital tools such as AI and blockchain can enhance the sustainability of bioeconomic practices, particularly in agricultural value chains. This project will address challenges in environmental valuation, public acceptance of innovative technologies, and governance of sustainable value chains. The outcomes will contribute to policy recommendations and innovative models for the circular bioeconomy, supporting the global sustainability and digitalisation goals.
-
Transformative Approaches to Sustainable Medicines Manufacturing Using AI-Driven Circular Bioeconomy
This research project aims to revolutionize sustainable medicine manufacturing by integrating Artificial Intelligence (AI), digitalisation, data analytics, and machine learning to pursue a net zero, circular bioeconomy. The project will develop and implement innovative AI-driven models to optimize manufacturing processes, reduce waste, and enhance resource efficiency. Digital twins and advanced data analytics will be employed to monitor and improve environmental performance in real time. By aligning with circular economy principles, the project seeks to minimize environmental impact while maintaining economic and social sustainability. The outcomes will provide a scalable framework for the pharmaceutical industry to transition towards sustainable, low-carbon manufacturing.
Supervision history
Current supervision
-
Doctor Philosophy
Enhancing Sustainable Waste Management in Agri-Food Production
Principal Advisor
Other advisors: Dr Rajendra Adhikari
-
Doctor Philosophy
The role of minimalist, zero waste and frugal lifestyles in food waste reduction and prevention
Principal Advisor
Other advisors: Dr Rajendra Adhikari
Completed supervision
-
2022
Doctor Philosophy
Enhancing the sustainability of food production: A methodological framework to assess and improve the sustainability of the Australian food system
Principal Advisor
-
2020
Master Philosophy
Towards better circular economy and life cycle assessment through systems thinking and examining the interrelationships among sustainability, food systems and diet
Principal Advisor
-
2019
Doctor Philosophy
Strengthening Clean Energy Policy to Decarbonize Indonesia's Electricity System: A Hybrid Energy Modelling & Analysis
Principal Advisor
-
2019
Doctor Philosophy
How Sustainable Is Disaster Resilience? Integrating Systems Thinking Approach towards Achieving Sustainable Post-Disaster Housing Reconstruction
Principal Advisor
-
2018
Doctor Philosophy
Moving towards Sustainable Construction in Malaysia: A Holistic Model for Construction and Demolition (C&D) Waste Management
Principal Advisor
-
2017
Doctor Philosophy
Measuring the environmental efficiency of food products: New knowledge for the design of Sustainable Diets
Principal Advisor
-
2020
Doctor Philosophy
Environmental implications of meeting future demand for sugarcane-based ethanol in Brazil.
Associate Advisor
Other advisors: Professor James Watson
-
2017
Doctor Philosophy
A study of carbon dioxide emissions reduction opportunities for airlines on Australian international routes
Associate Advisor
-
2017
Doctor Philosophy
Enhancing the Understanding of Urban Systems for Sustainability Transition: A Study of Urban Environmental Management in the Natural Resource-Based Industrial City of Jinchang, China
Associate Advisor
Other advisors: Dr Thomas Sigler, Dr Bob Beeton
-
2016
Doctor Philosophy
Building a Conceptual Model to Enhance Environmental Adaptive Capacity in Small and Medium Sized Enterprises: A Case Study in Vietnam'sTextile and Garment Industry
Associate Advisor
Other advisors: Dr Bob Beeton
Media
Enquiries
Contact Dr Anthony Halog directly for media enquiries about:
- Bioeconomy
- Carbon Footprint
- Carbon Neutral
- Circular Design
- Circular Economy
- Clean Energy and Hydrogen
- Climate Change
- Decarbonization
- Energy Efficiency
- Environmental Impact
- Environmental Policy
- ESG
- Green Economy
- Green Hydrogen
- Green Manufacturing
- Green Technology
- Industrial Ecology
- Life Cycle Assessment
- Low Carbon Economy
- Net Zero Emission
- Renewable Energy
- Resource Efficiency
- Sustainability
- Sustainable Agriculture
- Sustainable and Circular Innovation
- Sustainable Development
- Sustainable Supply Chain
- Sustinable Business
- Waste Management
Need help?
For help with finding experts, story ideas and media enquiries, contact our Media team: