Monica Danilevicz

Monica Danilevicz is a Research Fellow at the Australian Herbicide Resistance Initiative (AHRI) within the UWA School of Agriculture and Environment at the University of Western Australia. Her research focuses on integrating emerging technologies like machine learning, computer vision, and remote sensing to support sustainable agriculture, including smart weed management and climate-resilient crop development. She also leverages bioinformatics to incorporate molecular markers and biochemical measurements into her analyses.

Education:

• PhD in Biological Sciences (2023): 'Application of deep learning to leverage high-throughput phenotyping for crop breeding,' University of Western Australia.
• Master's in Plant Biotechnology and Bioprocesses (2019): 'Uncovering non-coding RNA in copaiba and maize,' Universidade Federal do Rio de Janeiro.
• Bachelor's in Biotechnology (2016): 'MicroRNA expression analysis from maize inoculated with endophytic bacteria under hydric stress,' Universidade Federal do Rio de Janeiro.

Research Interests:

• Sustainable agricultural technologies, including precision farming and AI-driven solutions.
• Machine learning applications in crop phenotyping, disease detection, and genomics.
• Climate-resilient crop development through genomic and phenotypic integration.
• Herbicide resistance management and weed ecology.

Articles Trends: Her work emphasizes machine learning in crop improvement, genomics-driven solutions, and predictive modeling for yield stability. Recent studies explore AI applications in disease detection, genomic feature selection, and genotype-environment interactions.

Awards:

• Forrest Research Foundation Scholarship (PhD).

Advising & Grants: Accepting PhD/HDR students in agricultural biotechnology and AI applications. Collaborates on global projects like the Maize Yield Prediction Competition.

Labs/Teams: Active in the Australian Herbicide Resistance Initiative (AHRI) and leads projects on crop phenotyping and genomic analysis.