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PhD (Queensland University of Technology), BSc (Chemical Engineering) (University of the Philippines)
Dr Jerome Ramirez is a Postdoctoral Research Fellow in the Centre for Agriculture and the Bioeconomy. He has a PhD in Energy and Process Engineering from Queensland University of Technology and a Bachelor of Science in Chemical Engineering from the University of the Philippines - Diliman. His current research focuses on modelling bioprocesses that implement biotechnology and synthetic biology. This research includes techno-economic and environmental impact assessment of new processing technologies. Dr Ramirez conducts industry research in these areas and in assessing the supply of biomass feedstock to production processes to make new products such as alternative proteins, sustainable aviation fuel, precision fermentation chemical products, and others.
His process modelling research enables the adoption of these technologies in view of increased material and energy efficiency, lower cost, and increased economic, environmental and social benefits.
Dr Ramirez' industrial experience includes process evaluation and design, process safety, safety and environmental compliance, and risk assessment. Dr Ramirez has had industry projects with food, fuel, agricultural product, and mineral processing companies.
Additional information
- Jahanian, A., Ramirez, J. & O'Hara, I. (2024). Advancing precision fermentation: Minimizing power demand of industrial scale bioreactors through mechanistic modelling. Computers and Chemical Engineering, 188. https://eprints.qut.edu.au/249346
- Fraga, G., Ramirez, J., Renouf, M. & Batalha, N. (2024). Conceptual Process Design, Techno-Economics, and Greenhouse Gas Analysis of Furfuryl Alcohol Production via Transfer Hydrogenation. ACS Sustainable Chemistry and Engineering, 12(28), 10604–10614. https://eprints.qut.edu.au/250638
- Sakheta, A., Raj, T., Nayak, R., O'Hara, I. & Ramirez, J. (2024). Improved prediction of biomass gasification models through machine learning. Computers and Chemical Engineering, 191. https://eprints.qut.edu.au/251712
- Sakheta, A., Nayak, R., O'Hara, I. & Ramirez, J. (2023). A review on modelling of thermochemical processing of biomass for biofuels and prospects of artificial intelligence-enhanced approaches. Bioresource Technology, 386. https://eprints.qut.edu.au/242071
- Taghipour, A., Ramirez, J., Rakhmetova, O. & Rainey, T. (2022). A method for HTL biocrude simulation using multi-objective optimisation and fractional distillation. Computers and Chemical Engineering, 157. https://eprints.qut.edu.au/226668
- Ramirez, J., McCabe, B., Jensen, P., Speight, R., Harrison, M., van den Berg, L. & O'Hara, I. (2021). Wastes to profit: a circular economy approach to value-addition in livestock industries. Animal Production Science, 61(6), 541–550. https://eprints.qut.edu.au/208027
- Ramirez, J. & Rainey, T. (2019). Comparative techno-economic analysis of biofuel production through gasification, thermal liquefaction and pyrolysis of sugarcane bagasse. Journal of Cleaner Production, 229, 513–527. https://eprints.qut.edu.au/129052
- Ramirez, J., Brown, R. & Rainey, T. (2018). Techno-economic analysis of the thermal liquefaction of sugarcane bagasse in ethanol to produce liquid fuels. Applied Energy, 224, 184–193. https://eprints.qut.edu.au/223888
- Ramirez, J., Brown, R. & Rainey, T. (2017). Liquefaction biocrudes and their petroleum crude blends for processing in conventional distillation units. Fuel Processing Technology, 167, 674–683. https://eprints.qut.edu.au/110170
- Ramirez, J., Brown, R. & Rainey, T. (2015). A review of hydrothermal liquefaction bio-crude properties and prospects for upgrading to transportation fuels. Energies, 8(7), 6765–6794. https://eprints.qut.edu.au/85140
- Title
- Building industry engagement capability for a diversified and adaptable Australian sugarcane industry
- Primary fund type
- CAT 1 - Australian Competitive Grant
- Project ID
- 2022/018
- Start year
- 2023
- Keywords
- Modelling Thermochemical Conversions of Lignocellulosic Biomass to Biofuels with Machine Learning
PhD, Principal Supervisor
Other supervisors: Professor Ian O'Hara, Professor Richi Nayak