Our Team

 CEI:AgER is comprised of a number of dedicated and highly qualified academic staff, postdoctoral research fellows, research assistants, research officers, higher degree by research candidates and support staff who are based on-site at the CEI:AgER Shenton Park facility.

 

Area Leads


FOUNDING DIRECTOR
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AGRICULTURAL TECHNOLOGY THEME LEAD
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ECOLOGICAL RESTORATION THEME LEAD

  • A/Prof Guzzomi’s strengths and passion are in engineering innovation related to (mechanical) agricultural engineering, ecological restoration, and engineering education. The Founding Director of CEI:AgER, he is focused on using good engineering design to combat issues within the agricultural and environmental sectors and help ensure Australia’s future prosperity and resilience.

  • Wesley is an engineer and educator passionate about leveraging technology to create a sustainable future in agriculture and food security. His research spans agricultural machinery design, precision agricultural systems and education of emerging technology. Wesley leads the Agricultural Technology Theme of CEI:AgER.

  • Dr Todd Erickson uses his extensive seed biology and restoration ecology background in mining-intensive landscapes to unpack recruitment barriers that limit efficient seed use in restoration settings. Coupling this knowledge with strong industry links enables innovative ecologically-guided seed enhancement and direct seeding equipment solutions to be developed to deliver seeds and improve plant establishment in large-scale degraded landscapes. He leads the Ecological Restoration Theme of CEI:AgER.

PROTOTYPING WORKSHOP LEAD

  • Trent is the CEI:AgER Workshop Technician. As a multitalented fitter and machinist with a background in R&D, engine development, and oil and gas, Trent is responsible for bringing the team’s projects to life in CEI:AgER’s very own prototyping workshop facilities.

WEED TECHNOLOGY THEME LEAD
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  • Professor Walsh uses his weed science foundation and practical understanding to develop implementable alternative weed control technologies aimed at reducing the impact of herbicide resistance on Australian grain cropping systems.


Researchers


RESEARCH FELLOW

  • Carlo is interested in mechanisms and mechanical design, soil/tool interaction, multi body dynamics, and vibrations. He specialises in the design of agricultural machinery.

    He is currently involved in the engineering design of the Mechanical In-Crop Targetted Tillage Project.

RESEARCH FELLOW

  • Monte is interested in the development and testing of engineering machinery to improve restoration outcomes.

    His current work uses fundamental biological research to guide machine design and is interested in implementing research outcomes at an industrial scale in the ecosystem restoration space.

RESEARCH FELLOW

  • Luke’s research focuses on development of seedling enhancement technologies that are tailored towards enhancing seedling development, tolerance to abiotic stress, and seedling recruitment for ecological restoration efforts.

    Luke’s current work investigates the application of bioactive organic compounds and soil amendments to stimulate growth and development of native species during the early phases of seedling establishment in mine site rehabilitation.

RESEARCH FELLOW

  • Stuart is a physicist and software engineer with interests in machine learning, software development and general science.

    He is currently involved in the control systems and electrical design of the Mechanical In-Crop Targeted Tillage Project.

RESEARCH OFFICER

  • Yuval has over 30 years’ experience as a mechanical engineer and tradesperson, with skills in fabrication and manufacturing.

RESEARCH OFFICER

  • Shanika is interested in restoration ecology, plant pathology and environmental conservation.

    Her current research is focused on evaluating seed enhancements to improve seedling establishment and survival in restoration projects

PhD CANDIDATE

  • Hannah is interested in the biological and social contexts that impact ecosystem restoration success.

    Her research aims to identify areas in the restoration lifecycle that could benefit from improved technology, and she is currently working on developing user-friendly seeding equipment for native Australian seeds.

PhD CANDIDATE

  • William is interested in material properties and investigating new materials to work towards a more sustainable future.

    His research aims to provide sustainable alternatives for existing building products through the use of underutilized natural materials.

PhD CANDIDATE

  • Steph is interested in understanding the systems and biological processes that influence environmental restoration outcomes.

    Her research aims to explore engineering principles and techniques to improve seedling emergence from depth.

Interested in doing a PhD in our Centre?
Contact our director,
Dr Andrew Guzzomi.

PhD CANDIDATE

  • Eve is interested in engineering for sustainable ecological restoration.

    Her research aims to understand the influence of mechanical equipment on erosion in mine site restoration for more stable rehabilitation outcomes.

PhD CANDIDATE

  • Ruby is passionate about improving the efficiency and sustainability of agricultural systems.

    Her research aims to develop and evaluate prototype technology for harvesting subterranean clover seed.


Casual Staff


RESEARCH ASSISTANT

  • Lee is studying Pharmacology and Agricultural Science, and works as a Research Assistant on the Subterranean Clover Project.

RESEARCH ASSISTANT

  • Yvonne studies agriculture at UWA and has a particular interest in plant physiology and fungi.

    She is a Research Officer on the Subterranean Clover Project, where she investigates how seed viability and biological characteristics are impacted by different harvesting techniques.

RESEARCH ASSISTANT

  • Erwin is an Electrical & Electronic MPE student interested in electronic design, embedded programming, and artificial intelligence.

    His current work involves extending CEI:AgER's adoption of open-source weed detection techonologies and building machine learning capabilities for computer vision applications.