University of Southern Queensland (UniSQ)

From December 2023 to November 2025, I worked as a Senior Research Fellow at the University of Southern Queensland, where I contributed to major national and international research programs in crop modelling, digital agriculture, climate resilience, and sustainable farming systems. I served as the acting leader of the Agricultural Systems and Catchment Modelling Team within the Centre for Sustainable Agricultural Systems, overseeing the team’s daily operations, coordinating proposal development, and maintaining strong engagement with industry, government, and research partners. My leadership extended across multiple funded projects, including the BACI “Understanding Sesame” project, the AgriFutures “Australian Sesame Program of Research”, the Aus4Innovation (CSIRO/DFAT) Vietnam Crop Monitoring initiative, the IRRI-funded REMET-Rice methane-mitigation program, and the GRDC-funded SMART sodicity-management platform. Across these efforts, I led multi-institutional teams, facilitated co-design processes, and ensured the delivery of high-quality scientific outputs aligned with partner priorities.

A major part of my contribution at UniSQ involved advancing simulation modelling and crop-physiology research, particularly for sesame and rice systems. I designed and conducted a semi-controlled glasshouse experiment in Toowoomba to generate physiological data for parameterising a new APSIM NextGen Sesame module, supporting model calibration and validation across diverse cropping environments. I analysed extensive multi-site field datasets, integrated experimental measurements with simulation outputs, and developed the new APSIM sesame module in C#, incorporating key physiological and environmental processes. In the REMET-Rice project, as project co-leader, I performed literature review and modelling activities using ORYZA to evaluate methane-mitigation strategies based on nature-based solutions. These modelling efforts supported scenario analyses, trait evaluation, and long-term assessments of climate and management impacts on tropical and subtropical cropping systems.

In parallel, I made substantial data-science and digital-agriculture contributions, integrating Python-based workflows and cloud-ready geospatial analytics into UniSQ’s modelling programs. I built semi-automated preprocessing pipelines using rasterio, geopandas, numpy, scipy, and Papermill, and developed Google Earth Engine workflows for Sentinel-2 and Landsat imagery to derive vegetation indices, temporal features, and ML-ready datasets. I performed large-scale data integration by merging remote-sensing, weather, and crop datasets into streamlined analytical tables and trained machine-learning models with scikit-learn and xgboost to support crop monitoring, yield estimation, and decision-support applications. These technical contributions underpinned the delivery of AI-enabled crop-monitoring tools for Vietnam, enhanced APSIM-based modelling capacity for sesame and soil sodicity management, and strengthened UniSQ’s digital-agriculture capability across multiple research themes.

My role also encompassed project management, team leadership, ECR supervision, and stakeholder engagement. I supported and coached HDR students and early-career researchers working in crop modelling and digital agriculture, facilitated collaboration across UniSQ, CSIRO, QLD-DPI, NT-DITT, WA-DPIRD, and other partners, and ensured smooth project delivery through structured planning, risk management, and continuous communication. I regularly represented UniSQ at meetings, workshops, and conferences, providing clear communication of complex modelling and data-science concepts to diverse audiences. Through this combination of scientific, technical, and leadership contributions, I helped advance UniSQ’s position as a national leader in APSIM development, sesame research, and applied digital-agriculture innovation.